From 6df2afb8574c3525ddc46f358a8061c97ee4d1a9 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 16 Feb 2024 16:11:57 -0500 Subject: [PATCH 01/44] Initial implementation of sbml qual processor --- mira/sources/sbml_qual/__init__.py | 0 mira/sources/sbml_qual/processor.py | 565 ++++++++++++++++++++++++++++ 2 files changed, 565 insertions(+) create mode 100644 mira/sources/sbml_qual/__init__.py create mode 100644 mira/sources/sbml_qual/processor.py diff --git a/mira/sources/sbml_qual/__init__.py b/mira/sources/sbml_qual/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/mira/sources/sbml_qual/processor.py b/mira/sources/sbml_qual/processor.py new file mode 100644 index 000000000..ec974d06b --- /dev/null +++ b/mira/sources/sbml_qual/processor.py @@ -0,0 +1,565 @@ +import copy +import csv +from collections import defaultdict +import logging +import math +from typing import Dict, Iterable, List, Mapping, Optional, Tuple + +from mira.sources.biomodels import get_sbml_model +from mira.sources.biomodels import template_model_from_sbml_string +from mira.metamodel import * +from mira.resources import get_resource_file + + +import requests +import bioregistry +import libsbml +from libsbml import SBMLReader +import sympy +from lxml import etree +from tqdm import tqdm + +apoptosis_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules" + "/Apoptosis_qual.sbml?ref_type=heads" +) +apoptosis_file_2 = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/blob/master/Executable%20Modules/model_Apoptosis.sbml?ref_type=heads" +) +drug_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Drugs_mechanisms_qual.sbml?ref_type=heads" +) + +stress_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/ER_stress_qual.sbml?ref_type=heads" +) +interferon_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Interferon_qual.sbml?ref_type=heads" +) +pamp_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/PAMP_signaling_qual.sbml?ref_type=heads" +) +ubiquitination_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Ubiquitination_qual.sbml?ref_type=heads" +) + +virus_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Virus_Replication_qual.sbml?ref_type=heads" +) + + +class TqdmLoggingHandler(logging.Handler): + def __init__(self, level=logging.NOTSET): + super().__init__(level) + + def emit(self, record): + try: + msg = self.format(record) + tqdm.write(msg) + self.flush() + except Exception: + self.handleError(record) + + +logger = logging.getLogger(__name__) +logger.addHandler(TqdmLoggingHandler()) + +PREFIX_MAP = { + "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "dcterms": "http://purl.org/dc/terms/", + "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", + "vCard4": "http://www.w3.org/2006/vcard/ns#", + "bqbiol": "http://biomodels.net/biology-qualifiers/", + "bqmodel": "http://biomodels.net/model-qualifiers/", + "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", + "copasi": "http://www.copasi.org/static/sbml", + "jd": "http://www.sys-bio.org/sbml", +} +RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" +#: This XPath query gets annotations on species for their structured +#: identifiers, typically given as MIRIAM URIs or URNs +IDENTIFIERS_XPATH = f"rdf:RDF/rdf:Description/bqbiol:is/rdf:Bag/rdf:li" +COPASI_DESCR_XPATH = "/annotation/*[2]/rdf:RDF/rdf:Description" +COPASI_IS = "%s/CopasiMT:is" % COPASI_DESCR_XPATH +COPASI_IS_VERSION_OF = "%s/CopasiMT:isVersionOf" % COPASI_DESCR_XPATH +COPASI_HAS_PROPERTY = "%s/bqbiol:hasProperty" % COPASI_DESCR_XPATH +#: This is an alternative XPath for groundings that use the isVersionOf +#: relation and are thus less specific than the one above but can be used +#: as fallback +IDENTIFIERS_VERSION_XPATH = ( + f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" +) +#: This XPath query gets annotations on species about their properties, +#: which typically help ad-hoc create subclasses that are more specific +PROPERTIES_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" +#: This query helps get annotations on reactions, like "this reaction is a +#: _protein-containing complex disassembly_ (GO:0043624)" +IS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" + + +class Converter: + """Wrapper around a curies converter with lazy loading.""" + + def __init__(self): + self.converter = None + + def parse_uri(self, uri): + """Parse a URI into a prefix/identifier pair.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.parse_uri(uri) + + def uri_to_curie(self, uri: str) -> Optional[str]: + """Turn a URI into a CURIE.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.compress(uri) + + +converter = Converter() + + +class SbmlQualProcessor: + def __init__( + self, sbml_model, qual_model_plugin, model_id=None, reporter_ids=None + ): + self.qual_model_plugin = qual_model_plugin + self.sbml_model = sbml_model + self.model_id = model_id + self.reporter_ids = reporter_ids + self.units = get_units(self.sbml_model.unit_definitions) + + self.extract_model() + + def extract_model(self): + # model_id, + if self.model_id is None: + self.model_id = get_model_id(self.sbml_model) + model_annots = get_model_annotations(self.sbml_model) + reporter_ids = set(self.reporter_ids or []) + concepts = self._extract_concepts() + + templates: List[Template] = [] + all_species = { + species.id for species in self.qual_model_plugin.qualitative_species + } + + # parameters and compartment attributes for sbml_model are empty, they don't exist for + # the qual_model_plugin + all_parameters = { + parameter.id: { + "value": parameter.value, + "description": parameter.name, + "units": self.get_object_units(parameter), + } + for parameter in self.sbml_model.parameters + } + + parameter_symbols = { + parameter.id: sympy.Symbol(parameter.id) + for parameter in self.sbml_model.parameters + } + compartment_symbols = { + compartment.id: sympy.Symbol(compartment.id) + for compartment in self.sbml_model.compartments + } + # Add compartment volumes as parameters + for compartment in self.sbml_model.compartments: + all_parameters[compartment.id] = { + "value": compartment.volume, + "description": compartment.name, + "units": self.get_object_units(compartment), + } + + # Handle custom function definitions in the model + function_lambdas = {} + for fun_def in self.sbml_model.function_definitions: + args = [ + fun_def.getArgument(i).getName() + for i in range(fun_def.getNumArguments()) + ] + arg_symbols = {arg: sympy.Symbol(arg) for arg in args} + + signature = tuple(arg_symbols.values()) + formula_str = get_formula_str(fun_def.getBody()) + if isinstance(formula_str, float) and math.isnan(formula_str): + continue + formula = safe_parse_expr(formula_str, local_dict=arg_symbols) + lmbd = sympy.Lambda(signature, formula) + function_lambdas[fun_def.id] = lmbd + + # In formulas, the species ID appears instead of the species name + # and so we have to map these to symbols corresponding to the species name + species_id_map = { + species.id: ( + sympy.Symbol(species.name) + if ( + species.name + and "(" not in species.name + and "-" not in species.name + and "+" not in species.name + ) + else sympy.Symbol(species.id) + ) + for species in self.sbml_model.species + } + + all_locals = { + k: v + for k, v in ( + list(parameter_symbols.items()) + + list(compartment_symbols.items()) + + list(function_lambdas.items()) + + list(species_id_map.items()) + ) + } + + # Handle custom assignment rules in the model + assignment_rules = {} + for rule in self.sbml_model.rules: + rule_expr = parse_assignment_rule(rule.formula, all_locals) + if rule_expr: + assignment_rules[rule.id] = rule_expr + + all_implicit_modifiers = set() + implicit_modifiers = None + + for transition in self.qual_model_plugin.transitions: + pass + + def _extract_concepts(self) -> Mapping[str, Concept]: + concepts = {} + for species in self.qual_model_plugin.getListOfQualitativeSpecies(): + # QualitativeSpecies doesn't have units attribute. Cannot use get_object_units method + units = None + concept = _extract_concept( + species, model_id=self.model_id, units=units + ) + concepts[species.getId()] = concept + return concepts + + def get_object_units(self, object): + if object.units: + if object.units == "dimensionless": + return Unit(expression=sympy.Integer(1)) + else: + return Unit(expression=self.units[object.units]) + else: + return None + + +def parse_assignment_rule(rule, locals): + try: + expr = safe_parse_expr(rule, local_dict=locals) + return expr + except SyntaxError: + return None + + +def _extract_concept(species, units=None, model_id=None): + species_id = species.getId() + species_name = species.getName() + display_name = species_name + + if (model_id, species_name) in grounding_map: + mapped_ids, mapped_context = grounding_map[(model_id, species_name)] + concept = Concept( + name=species_name, + display_name=display_name, + identifiers=copy.deepcopy(mapped_ids), + context=copy.deepcopy(mapped_context), + units=units, + ) + return concept + else: + logger.debug( + f"[{model_id} species:{species_id}] not found in grounding map" + ) + + annotation_string = species.getAnnotationString() + if not annotation_string: + logger.debug(f"[{model_id} species:{species_id}] had no annotations") + concept = Concept( + name=species_name, + display_name=display_name, + identifiers={}, + context={}, + units=units, + ) + return concept + + concept = Concept( + name=species_name, + display_name=display_name, + identifiers={}, + context={}, + units=units, + ) + return concept + + # namespace error when using a species' annotation string + annotation_tree = etree.fromstring(annotation_string) + + +def get_model_annotations(sbml_model) -> Annotations: + """Get the model annotations from the SBML model.""" + + # sbml_model has an empty annotation string, this method doesn't exist for the qual_plugin_model + ann_xml = sbml_model.getAnnotationString() + if not ann_xml: + return None + et = etree.fromstring(ann_xml) + # Publication: bqmodel:isDescribedBy + # Disease: bqbiol:is + # Taxa: bqbiol:hasTaxon + # Model type: bqbiol:hasProperty + annot_structure = { + "publications": "bqmodel:isDescribedBy", + "diseases": "bqbiol:is", + "taxa": "bqbiol:hasTaxon", + "model_type": "bqbiol:hasProperty", + "pathway": "bqbiol:isVersionOf", # points to pathways + # bqbiol:isPartOf used to point to pathways + # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway + "homolog_to": "bqbiol:isHomologTo", + "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel + "has_part": "bqbiol:hasPart", # points to pathways + } + annotations = defaultdict(list) + for key, path in annot_structure.items(): + full_path = f"rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li" + tags = et.findall(full_path, namespaces=PREFIX_MAP) + if not tags: + continue + for tag in tags: + uri = tag.attrib.get(RESOURCE_KEY) + if not uri: + continue + curie = converter.uri_to_curie(uri) + if not curie: + continue + annotations[key].append(curie) + + model_id = get_model_id(sbml_model) + if model_id and model_id.startswith("BIOMD"): + license = "CC0" + else: + license = None + + # TODO smarter split up taxon into pathogens and host organisms + hosts = [] + pathogens = [] + for curie in annotations.get("taxa", []): + if curie == "ncbitaxon:9606": + hosts.append(curie) + else: + pathogens.append(curie) + + model_types = [] + diseases = [] + logged_curie = set() + for curie in annotations.get("model_type", []): + if curie.startswith("mamo:"): + model_types.append(curie) + elif any( + curie.startswith(f"{disease_prefix}:") + for disease_prefix in ["mondo", "doid", "efo"] + ) or _curie_is_ncit_disease(curie): + diseases.append(bioregistry.normalize_curie(curie)) + elif curie not in logged_curie: + logged_curie.add(curie) + logger.debug(f"unhandled model_type: {curie}") + + return Annotations( + name=sbml_model.getModel().getName(), + description=None, # TODO + license=license, + authors=[], # TODO, + references=annotations.get("publications", []), + # no time_scale, time_start, time_end, locations from biomodels + hosts=hosts, + pathogens=pathogens, + diseases=diseases, + model_types=model_types, + ) + + +def _curie_is_ncit_disease(curie: str) -> bool: + prefix, identifier = bioregistry.parse_curie(curie) + if prefix != "ncit": + return False + try: + import pyobo + except ImportError: + return False + else: + # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") + return False + + +def get_model_id(sbml_model): + """Get the model ID from the SBML model annotation.""" + ann_xml = sbml_model.getAnnotationString() + if not ann_xml: + return None + et = etree.fromstring(ann_xml) + id_tags = et.findall( + "rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li", + namespaces=PREFIX_MAP, + ) + for id_tag in id_tags: + uri = id_tag.attrib.get(RESOURCE_KEY) + if uri: + prefix, identifier = converter.parse_uri(uri) + if prefix == "biomodels.db" and identifier.startswith("BIOMD"): + return identifier + return None + + +def get_units(unit_definitions): + """Return units from a list of unit definition blocks.""" + units = {} + for unit_def in unit_definitions: + units[unit_def.id] = process_unit_definition(unit_def) + return units + + +def process_unit_definition(unit_definition): + """Process a unit definition block to extract an expression.""" + full_unit_expr = sympy.Integer(1) + for unit in unit_definition.units: + unit_symbol_str = SBML_UNITS[unit.kind] + # We assume person instead of item here + if unit_symbol_str in unit_symbol_mappings: + unit_symbol_str = unit_symbol_mappings[unit_symbol_str] + unit_symbol = sympy.Symbol(unit_symbol_str) + # We do this to avoid the spurious factors in the expression + if unit.multiplier != 1: + unit_symbol *= unit.multiplier + if unit.exponent != 1: + unit_symbol **= unit.exponent + if unit.scale != 0: + unit_symbol *= 10**unit.scale + full_unit_expr *= unit_symbol + # We apply some mappings for canonical units we want to change + # We use equals here since == in sympy is structural equality + for k, v in unit_expression_mappings.items(): + if full_unit_expr.equals(k): + full_unit_expr = v + return full_unit_expr + + +def get_sbml_units(): + """Build up a mapping of SBML unit kinds to their names. + + This is necessary because units are given as numbers. + """ + module_contents = dir(libsbml) + unit_kinds = { + var: var.split("_")[-1].lower() + for var in module_contents + if var.startswith("UNIT_KIND") and var != "UNIT_KIND_INVALID" + } + unit_kinds = { + getattr(libsbml, var): unit_name + for var, unit_name in unit_kinds.items() + } + return unit_kinds + + +SBML_UNITS = get_sbml_units() +unit_symbol_mappings = { + "item": "person", + "metre": "meter", + "litre": "liter", +} + +unit_expression_mappings = { + 86400.0 * sympy.Symbol("second"): sympy.Symbol("day"), + 1 / (86400.0 * sympy.Symbol("second")): 1 / sympy.Symbol("day"), + 1 + / (86400.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("day") * sympy.Symbol("person")), + 31536000.0 * sympy.Symbol("second"): sympy.Symbol("year"), + 1 / (31536000.0 * sympy.Symbol("second")): 1 / sympy.Symbol("year"), + 1 + / (31536000.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("year") * sympy.Symbol("person")), +} + + +def _get_grounding_map(): + def parse_identifier_grounding(grounding_str): + # Example: ido:0000511/infected population from which we want to get + # {'ido': '0000511'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split(":")) + for grounding in grounding_str.split("|") + ) + + def parse_context_grounding(grounding_str): + # Example: disease_severity=ncit:C25269/Symptomatic| + # diagnosis=ncit:C113725/Undiagnosed + # from which we want to get {'disease_severity': 'ncit:C25269', + # 'diagnosis': 'ncit:C113725'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split("=")) + for grounding in grounding_str.split("|") + ) + + fname = get_resource_file("mapped_biomodels_groundings.csv") + mappings = {} + with open(fname, "r") as fh: + reader = csv.reader(fh) + next(reader) + for name, ids, context, model, mapped_ids, mapped_context in reader: + mappings[(model, name)] = ( + parse_identifier_grounding(mapped_ids), + parse_context_grounding(mapped_context), + ) + + return mappings + + +grounding_map = _get_grounding_map() + + +def get_formula_str(ast_node): + name = ast_node.getName() + if not name: + op = ast_node.getOperatorName() + if op: + if op == "times": + op_str = "*" + elif op == "plus": + op_str = "+" + elif op == "divide": + op_str = "/" + elif op == "minus": + op_str = "-" + else: + print("Unknown op: %s" % op) + assert False + # Special case where we have a unary minus + if op == "minus" and ast_node.isUMinus(): + return "-%s" % get_formula_str(ast_node.getChild(0)) + # More general binary case + return "(%s %s %s)" % ( + get_formula_str(ast_node.getChild(0)), + op_str, + get_formula_str(ast_node.getChild(1)), + ) + val = ast_node.getValue() + if val is not None: + return val + # Exponential doesn't show up as an operator but rather a name + elif name in {"exp"}: + return "%s(%s)" % (name, get_formula_str(ast_node.getChild(0))) + else: + return name + + From ebec10274c89711e8523e0a7e9fe3e9efcd65f75 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 20 Feb 2024 10:05:57 -0500 Subject: [PATCH 02/44] Change location of qual processing and add sample transition processing --- .../{sbml_qual/processor.py => sbml/qual.py} | 68 +++++++++++-------- 1 file changed, 41 insertions(+), 27 deletions(-) rename mira/sources/{sbml_qual/processor.py => sbml/qual.py} (97%) diff --git a/mira/sources/sbml_qual/processor.py b/mira/sources/sbml/qual.py similarity index 97% rename from mira/sources/sbml_qual/processor.py rename to mira/sources/sbml/qual.py index ec974d06b..342073366 100644 --- a/mira/sources/sbml_qual/processor.py +++ b/mira/sources/sbml/qual.py @@ -19,33 +19,7 @@ from lxml import etree from tqdm import tqdm -apoptosis_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules" - "/Apoptosis_qual.sbml?ref_type=heads" -) -apoptosis_file_2 = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/blob/master/Executable%20Modules/model_Apoptosis.sbml?ref_type=heads" -) -drug_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Drugs_mechanisms_qual.sbml?ref_type=heads" -) - -stress_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/ER_stress_qual.sbml?ref_type=heads" -) -interferon_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Interferon_qual.sbml?ref_type=heads" -) -pamp_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/PAMP_signaling_qual.sbml?ref_type=heads" -) -ubiquitination_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Ubiquitination_qual.sbml?ref_type=heads" -) -virus_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Virus_Replication_qual.sbml?ref_type=heads" -) class TqdmLoggingHandler(logging.Handler): @@ -223,8 +197,15 @@ def extract_model(self): all_implicit_modifiers = set() implicit_modifiers = None - for transition in self.qual_model_plugin.transitions: + inputs = [ + qual_species.id for qual_species in transition.getListOfInputs() + ] + outputs = [ + qual_species.id + for qual_species in transition.getListOfOutputs() + ] + pass def _extract_concepts(self) -> Mapping[str, Concept]: @@ -562,4 +543,37 @@ def get_formula_str(ast_node): else: return name +apoptosis_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules" + "/Apoptosis_qual.sbml?ref_type=heads" +) +apoptosis_file_2 = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/blob/master/Executable%20Modules/model_Apoptosis.sbml?ref_type=heads" +) +drug_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Drugs_mechanisms_qual.sbml?ref_type=heads" +) + +stress_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/ER_stress_qual.sbml?ref_type=heads" +) +interferon_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Interferon_qual.sbml?ref_type=heads" +) +pamp_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/PAMP_signaling_qual.sbml?ref_type=heads" +) +ubiquitination_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Ubiquitination_qual.sbml?ref_type=heads" +) +virus_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Virus_Replication_qual.sbml?ref_type=heads" +) +def test_qual_own(): + xml_string = virus_file.text + sbml_document = SBMLReader().readSBMLFromString(xml_string) + sbml_document.setPackageRequired("qual", True) + model = sbml_document.getModel() + qual_model_plugin = model.getPlugin("qual") + processor = SbmlQualProcessor(model, qual_model_plugin) From b0d003b88f92890502c3f55a21485773b0e46a4b Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 20 Feb 2024 10:09:42 -0500 Subject: [PATCH 03/44] Remove old sbml_qual directory --- mira/sources/sbml_qual/__init__.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 mira/sources/sbml_qual/__init__.py diff --git a/mira/sources/sbml_qual/__init__.py b/mira/sources/sbml_qual/__init__.py deleted file mode 100644 index e69de29bb..000000000 From f1d7ae46e7f95be4c6cb4c4bb6bdc9f9fe1e3fe8 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 21 Feb 2024 09:28:21 -0500 Subject: [PATCH 04/44] Add rate law extraction and natural conversion templates --- mira/sources/sbml/qual.py | 481 +++++--------------------------------- 1 file changed, 64 insertions(+), 417 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 342073366..8ae31e5e2 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -15,13 +15,12 @@ import bioregistry import libsbml from libsbml import SBMLReader +from libsbml import formulaToL3String import sympy from lxml import etree from tqdm import tqdm - - class TqdmLoggingHandler(logging.Handler): def __init__(self, level=logging.NOTSET): super().__init__(level) @@ -38,60 +37,6 @@ def emit(self, record): logger = logging.getLogger(__name__) logger.addHandler(TqdmLoggingHandler()) -PREFIX_MAP = { - "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", - "dcterms": "http://purl.org/dc/terms/", - "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", - "vCard4": "http://www.w3.org/2006/vcard/ns#", - "bqbiol": "http://biomodels.net/biology-qualifiers/", - "bqmodel": "http://biomodels.net/model-qualifiers/", - "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", - "copasi": "http://www.copasi.org/static/sbml", - "jd": "http://www.sys-bio.org/sbml", -} -RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" -#: This XPath query gets annotations on species for their structured -#: identifiers, typically given as MIRIAM URIs or URNs -IDENTIFIERS_XPATH = f"rdf:RDF/rdf:Description/bqbiol:is/rdf:Bag/rdf:li" -COPASI_DESCR_XPATH = "/annotation/*[2]/rdf:RDF/rdf:Description" -COPASI_IS = "%s/CopasiMT:is" % COPASI_DESCR_XPATH -COPASI_IS_VERSION_OF = "%s/CopasiMT:isVersionOf" % COPASI_DESCR_XPATH -COPASI_HAS_PROPERTY = "%s/bqbiol:hasProperty" % COPASI_DESCR_XPATH -#: This is an alternative XPath for groundings that use the isVersionOf -#: relation and are thus less specific than the one above but can be used -#: as fallback -IDENTIFIERS_VERSION_XPATH = ( - f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" -) -#: This XPath query gets annotations on species about their properties, -#: which typically help ad-hoc create subclasses that are more specific -PROPERTIES_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" -#: This query helps get annotations on reactions, like "this reaction is a -#: _protein-containing complex disassembly_ (GO:0043624)" -IS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" - - -class Converter: - """Wrapper around a curies converter with lazy loading.""" - - def __init__(self): - self.converter = None - - def parse_uri(self, uri): - """Parse a URI into a prefix/identifier pair.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.parse_uri(uri) - - def uri_to_curie(self, uri: str) -> Optional[str]: - """Turn a URI into a CURIE.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.compress(uri) - - -converter = Converter() - class SbmlQualProcessor: def __init__( @@ -101,10 +46,15 @@ def __init__( self.sbml_model = sbml_model self.model_id = model_id self.reporter_ids = reporter_ids - self.units = get_units(self.sbml_model.unit_definitions) + + # unit_definitions is empty for sbml_model + # self.units = get_units(self.sbml_model.unit_definitions) + self.units = {} self.extract_model() + pass + def extract_model(self): # model_id, if self.model_id is None: @@ -113,9 +63,18 @@ def extract_model(self): reporter_ids = set(self.reporter_ids or []) concepts = self._extract_concepts() + def _lookup_concepts_filtered(species_ids) -> List[Concept]: + return [ + concepts[species_id] + for species_id in species_ids + if species_id not in reporter_ids + and "cumulative" not in species_id + ] + templates: List[Template] = [] all_species = { - species.id for species in self.qual_model_plugin.qualitative_species + species.name + for species in self.qual_model_plugin.qualitative_species } # parameters and compartment attributes for sbml_model are empty, they don't exist for @@ -137,76 +96,36 @@ def extract_model(self): compartment.id: sympy.Symbol(compartment.id) for compartment in self.sbml_model.compartments } - # Add compartment volumes as parameters - for compartment in self.sbml_model.compartments: - all_parameters[compartment.id] = { - "value": compartment.volume, - "description": compartment.name, - "units": self.get_object_units(compartment), - } - - # Handle custom function definitions in the model - function_lambdas = {} - for fun_def in self.sbml_model.function_definitions: - args = [ - fun_def.getArgument(i).getName() - for i in range(fun_def.getNumArguments()) - ] - arg_symbols = {arg: sympy.Symbol(arg) for arg in args} - - signature = tuple(arg_symbols.values()) - formula_str = get_formula_str(fun_def.getBody()) - if isinstance(formula_str, float) and math.isnan(formula_str): - continue - formula = safe_parse_expr(formula_str, local_dict=arg_symbols) - lmbd = sympy.Lambda(signature, formula) - function_lambdas[fun_def.id] = lmbd - - # In formulas, the species ID appears instead of the species name - # and so we have to map these to symbols corresponding to the species name - species_id_map = { - species.id: ( - sympy.Symbol(species.name) - if ( - species.name - and "(" not in species.name - and "-" not in species.name - and "+" not in species.name - ) - else sympy.Symbol(species.id) - ) - for species in self.sbml_model.species - } - - all_locals = { - k: v - for k, v in ( - list(parameter_symbols.items()) - + list(compartment_symbols.items()) - + list(function_lambdas.items()) - + list(species_id_map.items()) - ) - } - - # Handle custom assignment rules in the model - assignment_rules = {} - for rule in self.sbml_model.rules: - rule_expr = parse_assignment_rule(rule.formula, all_locals) - if rule_expr: - assignment_rules[rule.id] = rule_expr all_implicit_modifiers = set() implicit_modifiers = None - for transition in self.qual_model_plugin.transitions: - inputs = [ - qual_species.id for qual_species in transition.getListOfInputs() + for idx, transition in enumerate(self.qual_model_plugin.transitions): + input_names = [ + qual_species.qualitative_species + for qual_species in transition.getListOfInputs() ] - outputs = [ - qual_species.id + output_names = [ + qual_species.qualitative_species for qual_species in transition.getListOfOutputs() ] - pass + # Cannot be parsed by sympy as the formula is conditional + rate_law = formulaToL3String( + transition.getListOfFunctionTerms()[0].getMath() + ) + + inputs = _lookup_concepts_filtered(input_names) + outputs = _lookup_concepts_filtered(output_names) + + # Add a case for modifiers + if len(inputs) == 1 and len(outputs) == 1: + templates.append( + NaturalConversion( + subject=inputs[0], + outcome=outputs[0], + rate_law=None, + ) + ) def _extract_concepts(self) -> Mapping[str, Concept]: concepts = {} @@ -229,35 +148,16 @@ def get_object_units(self, object): return None -def parse_assignment_rule(rule, locals): - try: - expr = safe_parse_expr(rule, local_dict=locals) - return expr - except SyntaxError: - return None - - def _extract_concept(species, units=None, model_id=None): species_id = species.getId() species_name = species.getName() display_name = species_name - if (model_id, species_name) in grounding_map: - mapped_ids, mapped_context = grounding_map[(model_id, species_name)] - concept = Concept( - name=species_name, - display_name=display_name, - identifiers=copy.deepcopy(mapped_ids), - context=copy.deepcopy(mapped_context), - units=units, - ) - return concept - else: - logger.debug( - f"[{model_id} species:{species_id}] not found in grounding map" - ) - annotation_string = species.getAnnotationString() + + # namespace error when using etree with a qualitative species' annotation string + # annotation_tree = etree.fromstring(annotation_string) + if not annotation_string: logger.debug(f"[{model_id} species:{species_id}] had no annotations") concept = Concept( @@ -278,104 +178,11 @@ def _extract_concept(species, units=None, model_id=None): ) return concept - # namespace error when using a species' annotation string - annotation_tree = etree.fromstring(annotation_string) - def get_model_annotations(sbml_model) -> Annotations: - """Get the model annotations from the SBML model.""" - - # sbml_model has an empty annotation string, this method doesn't exist for the qual_plugin_model ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None - et = etree.fromstring(ann_xml) - # Publication: bqmodel:isDescribedBy - # Disease: bqbiol:is - # Taxa: bqbiol:hasTaxon - # Model type: bqbiol:hasProperty - annot_structure = { - "publications": "bqmodel:isDescribedBy", - "diseases": "bqbiol:is", - "taxa": "bqbiol:hasTaxon", - "model_type": "bqbiol:hasProperty", - "pathway": "bqbiol:isVersionOf", # points to pathways - # bqbiol:isPartOf used to point to pathways - # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway - "homolog_to": "bqbiol:isHomologTo", - "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel - "has_part": "bqbiol:hasPart", # points to pathways - } - annotations = defaultdict(list) - for key, path in annot_structure.items(): - full_path = f"rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li" - tags = et.findall(full_path, namespaces=PREFIX_MAP) - if not tags: - continue - for tag in tags: - uri = tag.attrib.get(RESOURCE_KEY) - if not uri: - continue - curie = converter.uri_to_curie(uri) - if not curie: - continue - annotations[key].append(curie) - - model_id = get_model_id(sbml_model) - if model_id and model_id.startswith("BIOMD"): - license = "CC0" - else: - license = None - - # TODO smarter split up taxon into pathogens and host organisms - hosts = [] - pathogens = [] - for curie in annotations.get("taxa", []): - if curie == "ncbitaxon:9606": - hosts.append(curie) - else: - pathogens.append(curie) - - model_types = [] - diseases = [] - logged_curie = set() - for curie in annotations.get("model_type", []): - if curie.startswith("mamo:"): - model_types.append(curie) - elif any( - curie.startswith(f"{disease_prefix}:") - for disease_prefix in ["mondo", "doid", "efo"] - ) or _curie_is_ncit_disease(curie): - diseases.append(bioregistry.normalize_curie(curie)) - elif curie not in logged_curie: - logged_curie.add(curie) - logger.debug(f"unhandled model_type: {curie}") - - return Annotations( - name=sbml_model.getModel().getName(), - description=None, # TODO - license=license, - authors=[], # TODO, - references=annotations.get("publications", []), - # no time_scale, time_start, time_end, locations from biomodels - hosts=hosts, - pathogens=pathogens, - diseases=diseases, - model_types=model_types, - ) - - -def _curie_is_ncit_disease(curie: str) -> bool: - prefix, identifier = bioregistry.parse_curie(curie) - if prefix != "ncit": - return False - try: - import pyobo - except ImportError: - return False - else: - # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") - return False def get_model_id(sbml_model): @@ -383,197 +190,37 @@ def get_model_id(sbml_model): ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None - et = etree.fromstring(ann_xml) - id_tags = et.findall( - "rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li", - namespaces=PREFIX_MAP, - ) - for id_tag in id_tags: - uri = id_tag.attrib.get(RESOURCE_KEY) - if uri: - prefix, identifier = converter.parse_uri(uri) - if prefix == "biomodels.db" and identifier.startswith("BIOMD"): - return identifier - return None - - -def get_units(unit_definitions): - """Return units from a list of unit definition blocks.""" - units = {} - for unit_def in unit_definitions: - units[unit_def.id] = process_unit_definition(unit_def) - return units - - -def process_unit_definition(unit_definition): - """Process a unit definition block to extract an expression.""" - full_unit_expr = sympy.Integer(1) - for unit in unit_definition.units: - unit_symbol_str = SBML_UNITS[unit.kind] - # We assume person instead of item here - if unit_symbol_str in unit_symbol_mappings: - unit_symbol_str = unit_symbol_mappings[unit_symbol_str] - unit_symbol = sympy.Symbol(unit_symbol_str) - # We do this to avoid the spurious factors in the expression - if unit.multiplier != 1: - unit_symbol *= unit.multiplier - if unit.exponent != 1: - unit_symbol **= unit.exponent - if unit.scale != 0: - unit_symbol *= 10**unit.scale - full_unit_expr *= unit_symbol - # We apply some mappings for canonical units we want to change - # We use equals here since == in sympy is structural equality - for k, v in unit_expression_mappings.items(): - if full_unit_expr.equals(k): - full_unit_expr = v - return full_unit_expr - - -def get_sbml_units(): - """Build up a mapping of SBML unit kinds to their names. - - This is necessary because units are given as numbers. - """ - module_contents = dir(libsbml) - unit_kinds = { - var: var.split("_")[-1].lower() - for var in module_contents - if var.startswith("UNIT_KIND") and var != "UNIT_KIND_INVALID" - } - unit_kinds = { - getattr(libsbml, var): unit_name - for var, unit_name in unit_kinds.items() - } - return unit_kinds - - -SBML_UNITS = get_sbml_units() -unit_symbol_mappings = { - "item": "person", - "metre": "meter", - "litre": "liter", -} - -unit_expression_mappings = { - 86400.0 * sympy.Symbol("second"): sympy.Symbol("day"), - 1 / (86400.0 * sympy.Symbol("second")): 1 / sympy.Symbol("day"), - 1 - / (86400.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 - / (sympy.Symbol("day") * sympy.Symbol("person")), - 31536000.0 * sympy.Symbol("second"): sympy.Symbol("year"), - 1 / (31536000.0 * sympy.Symbol("second")): 1 / sympy.Symbol("year"), - 1 - / (31536000.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 - / (sympy.Symbol("year") * sympy.Symbol("person")), -} - - -def _get_grounding_map(): - def parse_identifier_grounding(grounding_str): - # Example: ido:0000511/infected population from which we want to get - # {'ido': '0000511'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split("/")[0].split(":")) - for grounding in grounding_str.split("|") - ) - - def parse_context_grounding(grounding_str): - # Example: disease_severity=ncit:C25269/Symptomatic| - # diagnosis=ncit:C113725/Undiagnosed - # from which we want to get {'disease_severity': 'ncit:C25269', - # 'diagnosis': 'ncit:C113725'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split("/")[0].split("=")) - for grounding in grounding_str.split("|") - ) - - fname = get_resource_file("mapped_biomodels_groundings.csv") - mappings = {} - with open(fname, "r") as fh: - reader = csv.reader(fh) - next(reader) - for name, ids, context, model, mapped_ids, mapped_context in reader: - mappings[(model, name)] = ( - parse_identifier_grounding(mapped_ids), - parse_context_grounding(mapped_context), - ) - return mappings - -grounding_map = _get_grounding_map() - - -def get_formula_str(ast_node): - name = ast_node.getName() - if not name: - op = ast_node.getOperatorName() - if op: - if op == "times": - op_str = "*" - elif op == "plus": - op_str = "+" - elif op == "divide": - op_str = "/" - elif op == "minus": - op_str = "-" - else: - print("Unknown op: %s" % op) - assert False - # Special case where we have a unary minus - if op == "minus" and ast_node.isUMinus(): - return "-%s" % get_formula_str(ast_node.getChild(0)) - # More general binary case - return "(%s %s %s)" % ( - get_formula_str(ast_node.getChild(0)), - op_str, - get_formula_str(ast_node.getChild(1)), - ) - val = ast_node.getValue() - if val is not None: - return val - # Exponential doesn't show up as an operator but rather a name - elif name in {"exp"}: - return "%s(%s)" % (name, get_formula_str(ast_node.getChild(0))) - else: - return name - -apoptosis_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules" - "/Apoptosis_qual.sbml?ref_type=heads" +apoptosis_file_new = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Apoptosis_stable.sbml?ref_type=heads" ) -apoptosis_file_2 = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/blob/master/Executable%20Modules/model_Apoptosis.sbml?ref_type=heads" -) -drug_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Drugs_mechanisms_qual.sbml?ref_type=heads" + +coagulation_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Coagulation-pathway_stable.sbml?ref_type=heads" ) + stress_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/ER_stress_qual.sbml?ref_type=heads" -) -interferon_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Interferon_qual.sbml?ref_type=heads" -) -pamp_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/PAMP_signaling_qual.sbml?ref_type=heads" -) -ubiquitination_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Ubiquitination_qual.sbml?ref_type=heads" + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ER_Stress_stable.sbml?ref_type=heads" ) -virus_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/Virus_Replication_qual.sbml?ref_type=heads" -) + def test_qual_own(): - xml_string = virus_file.text + xml_string = stress_file.text sbml_document = SBMLReader().readSBMLFromString(xml_string) sbml_document.setPackageRequired("qual", True) model = sbml_document.getModel() qual_model_plugin = model.getPlugin("qual") processor = SbmlQualProcessor(model, qual_model_plugin) + + +def test_old(): + model_id = "BIOMD0000000955" + from mira.sources.biomodels import ( + get_sbml_model, + template_model_from_sbml_string, + ) + + xml_string = get_sbml_model(model_id) + model = template_model_from_sbml_string(xml_string) From 11ad4e315ef5e2f6600329fe92a63d537ea95bb7 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 21 Feb 2024 10:29:55 -0500 Subject: [PATCH 05/44] Add initials --- mira/sources/sbml/qual.py | 23 +++++++++++++++++++---- 1 file changed, 19 insertions(+), 4 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 8ae31e5e2..65b345a8b 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -15,7 +15,7 @@ import bioregistry import libsbml from libsbml import SBMLReader -from libsbml import formulaToL3String +from libsbml import formulaToL3String, parseL3Formula import sympy from lxml import etree from tqdm import tqdm @@ -53,8 +53,6 @@ def __init__( self.extract_model() - pass - def extract_model(self): # model_id, if self.model_id is None: @@ -109,11 +107,15 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: for qual_species in transition.getListOfOutputs() ] - # Cannot be parsed by sympy as the formula is conditional + # Cannot be parsed by sympy as every formula is conditional + # transitions only have one function term, use the getMath method to retrieve an + # "ASTNode" object that contains the expression/logic + # formulaToL3String converts an ASTNode object to a string expression rate_law = formulaToL3String( transition.getListOfFunctionTerms()[0].getMath() ) + # find modifiers inputs = _lookup_concepts_filtered(input_names) outputs = _lookup_concepts_filtered(output_names) @@ -127,6 +129,16 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: ) ) + initials = {} + for qual_species in self.qual_model_plugin.qualitative_species: + initials[qual_species.name] = Initial( + concept=concepts[qual_species.id], + expression=SympyExprStr(qual_species.initial_level), + ) + + template_model = TemplateModel(templates=templates, initials=initials) + return template_model + def _extract_concepts(self) -> Mapping[str, Concept]: concepts = {} for species in self.qual_model_plugin.getListOfQualitativeSpecies(): @@ -213,6 +225,9 @@ def test_qual_own(): model = sbml_document.getModel() qual_model_plugin = model.getPlugin("qual") processor = SbmlQualProcessor(model, qual_model_plugin) + tm = processor.extract_model() + + pass def test_old(): From a111c344382761e55d5e1a8136ccdf002e751de0 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 21 Feb 2024 20:52:20 -0500 Subject: [PATCH 06/44] Add template processing --- mira/sources/sbml/qual.py | 295 +++++++++++++++++++++++++++++++------- 1 file changed, 245 insertions(+), 50 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 65b345a8b..20cf5249e 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -77,27 +77,38 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # parameters and compartment attributes for sbml_model are empty, they don't exist for # the qual_model_plugin - all_parameters = { - parameter.id: { - "value": parameter.value, - "description": parameter.name, - "units": self.get_object_units(parameter), - } - for parameter in self.sbml_model.parameters - } - parameter_symbols = { - parameter.id: sympy.Symbol(parameter.id) - for parameter in self.sbml_model.parameters - } - compartment_symbols = { - compartment.id: sympy.Symbol(compartment.id) - for compartment in self.sbml_model.compartments - } + # all_parameters = { + # parameter.id: { + # "value": parameter.value, + # "description": parameter.name, + # "units": self.get_object_units(parameter), + # } + # for parameter in self.sbml_model.parameters + # } + # + # parameter_symbols = { + # parameter.id: sympy.Symbol(parameter.id) + # for parameter in self.sbml_model.parameters + # } + # compartment_symbols = { + # compartment.id: sympy.Symbol(compartment.id) + # for compartment in self.sbml_model.compartments + # } + + # instead of a simple logic formula, there is a flag called qual:sign = positive + # then there exists a formula, positive controller means it controls the prooduction + # of something + # if there's a qual:sign = negative, + # qual negative means there's a controller which controls degradation + # if both positive and negative exists, it is production process, with a list of + # controllers from both the negative and positive side. + + for transition_id, transition in enumerate( + self.qual_model_plugin.transitions + ): + transition_name = transition.id - all_implicit_modifiers = set() - implicit_modifiers = None - for idx, transition in enumerate(self.qual_model_plugin.transitions): input_names = [ qual_species.qualitative_species for qual_species in transition.getListOfInputs() @@ -107,36 +118,136 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: for qual_species in transition.getListOfOutputs() ] - # Cannot be parsed by sympy as every formula is conditional - # transitions only have one function term, use the getMath method to retrieve an - # "ASTNode" object that contains the expression/logic - # formulaToL3String converts an ASTNode object to a string expression - rate_law = formulaToL3String( - transition.getListOfFunctionTerms()[0].getMath() + # negative sign is 0, positive sign is 1 for inputs only + # outputs do not have a sign + # Inputs will always be 0 or 1 + positive_controller_names = [ + qual_species.qualitative_species + for qual_species in transition.getListOfInputs() + if qual_species.getSign() == 0 + ] + + negative_controller_names = [ + qual_species.qualitative_species + for qual_species in transition.getListOfInputs() + if qual_species.getSign() == 1 + ] + + input_concepts = _lookup_concepts_filtered(input_names) + output_concepts = _lookup_concepts_filtered(output_names) + positive_controller_concepts = _lookup_concepts_filtered( + positive_controller_names + ) + negative_controller_concepts = _lookup_concepts_filtered( + negative_controller_names ) - # find modifiers - inputs = _lookup_concepts_filtered(input_names) - outputs = _lookup_concepts_filtered(output_names) - - # Add a case for modifiers - if len(inputs) == 1 and len(outputs) == 1: - templates.append( - NaturalConversion( - subject=inputs[0], - outcome=outputs[0], - rate_law=None, + # transitions always have at least one input and one output + # Since we always have at least one input, there will always be at least + # 1 controller (negative or positive). How does this translate to templates? + if ( + not positive_controller_concepts + and not negative_controller_concepts + ): + if len(input_concepts) == 1 and len(output_concepts) == 0: + templates.append( + NaturalDegradation( + subject=input_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + elif len(input_concepts) == 0 and len(output_concepts) == 1: + templates.append( + NaturalProduction( + outcome=output_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + elif len(input_concepts) == 1 and len(output_concepts) == 1: + templates.append( + NaturalConversion( + subject=input_concepts[0], + outcome=output_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + else: + if ( + len(positive_controller_concepts) >= 1 + and len(negative_controller_concepts) == 0 + ): + if len(positive_controller_concepts) == 1: + templates.append( + ControlledProduction( + controller=positive_controller_concepts[0], + outcome=output_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + else: + templates.append( + GroupedControlledProduction( + controllers=positive_controller_concepts, + outcome=output_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + elif ( + len(positive_controller_concepts) == 0 + and len(negative_controller_concepts) >= 1 + ): + if len(negative_controller_concepts) == 1: + templates.append( + ControlledDegradation( + controller=negative_controller_concepts[0], + subject=input_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + else: + templates.append( + GroupedControlledDegradation( + controllers=negative_controller_concepts, + subject=input_concepts[0], + name=transition_id, + display_name=transition_name, + ) + ) + elif ( + len(positive_controller_concepts) >= 1 + and len(negative_controller_concepts) >= 1 + ): + # Since inputs are only positive or negative, won't have overlapping concepts + # when adding the two lists together + templates.append( + GroupedControlledProduction( + controllers=positive_controller_concepts + + negative_controller_concepts, + outcome=output_concepts[0], + name=transition_id, + display_name=transition_name, + ) ) - ) + # initial level for each species is intMax, due to libsbml processing, not actually + # stored in the model + # use current level of species for now initials = {} for qual_species in self.qual_model_plugin.qualitative_species: initials[qual_species.name] = Initial( concept=concepts[qual_species.id], - expression=SympyExprStr(qual_species.initial_level), + expression=SympyExprStr(qual_species.level), ) - template_model = TemplateModel(templates=templates, initials=initials) + template_model = TemplateModel( + templates=templates, initials=initials, annotations=model_annots + ) return template_model def _extract_concepts(self) -> Mapping[str, Concept]: @@ -191,7 +302,7 @@ def _extract_concept(species, units=None, model_id=None): return concept -def get_model_annotations(sbml_model) -> Annotations: +def get_model_annotations(sbml_model): ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None @@ -212,22 +323,106 @@ def get_model_id(sbml_model): "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Coagulation-pathway_stable.sbml?ref_type=heads" ) - stress_file = requests.get( "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ER_Stress_stable.sbml?ref_type=heads" ) +etc_stable_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ETC_stable.sbml?ref_type=heads" +) + +e_protein_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/E_protein_stable.sbml?ref_type=heads" +) + +hmox1_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/HMOX1_Pathway_stable.sbml?ref_type=heads" +) + +ifn_lambda_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/IFN-lambda_stable.sbml?ref_type=heads" +) -def test_qual_own(): - xml_string = stress_file.text - sbml_document = SBMLReader().readSBMLFromString(xml_string) - sbml_document.setPackageRequired("qual", True) - model = sbml_document.getModel() - qual_model_plugin = model.getPlugin("qual") - processor = SbmlQualProcessor(model, qual_model_plugin) - tm = processor.extract_model() +interferon_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Interferon1_stable.sbml?ref_type=heads" +) - pass +jnk_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/JNK_pathway_stable.sbml?ref_type=heads" +) +kyu_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Kynurenine_pathway_stable.sbml?ref_type=heads" +) +nlrp3_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/NLRP3_Activation_stable.sbml?ref_type=heads" +) +nsp_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp14_stable.sbml?ref_type=heads" +) +nsp4_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp4_Nsp6_stable.sbml?ref_type=heads" +) +nsp9_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp9_protein_stable.sbml?ref_type=heads" +) +orf10_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf10_Cul2_pathway_stable.sbml?ref_type=heads" +) +orf3a_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads" +) +pamp_signal_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/PAMP_signaling_stable.sbml?ref_type=heads" +) +pyrimidine_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Pyrimidine_deprivation_stable.sbml?ref_type=heads" +) +rtc_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/RTC-and-transcription_stable.sbml?ref_type=heads" +) +renin_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Renin_angiotensin_stable.sbml?ref_type=heads" +) +tgfb_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/TGFB_pathway_stable.sbml?ref_type=heads" +) +virus_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Virus_replication_cycle_stable.sbml?ref_type=heads" +) +file_list = [ + stress_file, + # apoptosis_file_new, + # coagulation_file, + # etc_stable_file, + # e_protein_file, + # hmox1_file, + # ifn_lambda_file, + # jnk_file, + # kyu_file, + # nlrp3_file, + # nsp_file, + # nsp4_file, + # nsp9_file, + # orf10_file, + # orf3a_file, + # pamp_signal_file, + # pyrimidine_file, + # rtc_file, + # renin_file, + # tgfb_file, + # virus_file, +] + + +def test_qual(): + for file in file_list: + xml_string = file.text + sbml_document = SBMLReader().readSBMLFromString(xml_string) + sbml_document.setPackageRequired("qual", True) + model = sbml_document.getModel() + qual_model_plugin = model.getPlugin("qual") + processor = SbmlQualProcessor(model, qual_model_plugin) + tm = processor.extract_model() def test_old(): From 1b7b4444004f212aa91176f51bb70ae10d710b70 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 21 Feb 2024 21:01:02 -0500 Subject: [PATCH 07/44] Add comments to template processing --- mira/sources/sbml/qual.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 20cf5249e..86ba09ec6 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -144,7 +144,11 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # transitions always have at least one input and one output # Since we always have at least one input, there will always be at least - # 1 controller (negative or positive). How does this translate to templates? + # 1 controller (negative or positive). How does this translate to templates as + # currently it means we won't have any natural templates. + + # Since we always have at least one input and one output, won't ever have a + # degradation or production template usually. if ( not positive_controller_concepts and not negative_controller_concepts @@ -202,6 +206,9 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: and len(negative_controller_concepts) >= 1 ): if len(negative_controller_concepts) == 1: + + # for degradation, we sometimes have more than one input, how to handle + # this? templates.append( ControlledDegradation( controller=negative_controller_concepts[0], From 23f8853df93262a74f65dd5d02fde121a1f13fc4 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 9 Apr 2024 10:42:23 -0400 Subject: [PATCH 08/44] Clean up comments and remove testing code --- mira/sources/sbml/qual.py | 190 +++----------------------------------- 1 file changed, 14 insertions(+), 176 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 86ba09ec6..644585565 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -1,23 +1,9 @@ -import copy -import csv -from collections import defaultdict import logging -import math -from typing import Dict, Iterable, List, Mapping, Optional, Tuple +from typing import List, Mapping -from mira.sources.biomodels import get_sbml_model -from mira.sources.biomodels import template_model_from_sbml_string from mira.metamodel import * -from mira.resources import get_resource_file - -import requests -import bioregistry -import libsbml -from libsbml import SBMLReader -from libsbml import formulaToL3String, parseL3Formula import sympy -from lxml import etree from tqdm import tqdm @@ -49,9 +35,6 @@ def __init__( # unit_definitions is empty for sbml_model # self.units = get_units(self.sbml_model.unit_definitions) - self.units = {} - - self.extract_model() def extract_model(self): # model_id, @@ -70,32 +53,10 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: ] templates: List[Template] = [] - all_species = { - species.name - for species in self.qual_model_plugin.qualitative_species - } # parameters and compartment attributes for sbml_model are empty, they don't exist for # the qual_model_plugin - # all_parameters = { - # parameter.id: { - # "value": parameter.value, - # "description": parameter.name, - # "units": self.get_object_units(parameter), - # } - # for parameter in self.sbml_model.parameters - # } - # - # parameter_symbols = { - # parameter.id: sympy.Symbol(parameter.id) - # for parameter in self.sbml_model.parameters - # } - # compartment_symbols = { - # compartment.id: sympy.Symbol(compartment.id) - # for compartment in self.sbml_model.compartments - # } - # instead of a simple logic formula, there is a flag called qual:sign = positive # then there exists a formula, positive controller means it controls the prooduction # of something @@ -144,11 +105,10 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # transitions always have at least one input and one output # Since we always have at least one input, there will always be at least - # 1 controller (negative or positive). How does this translate to templates as - # currently it means we won't have any natural templates. + # 1 controller (negative or positive). Will never have a natural template - # Since we always have at least one input and one output, won't ever have a - # degradation or production template usually. + # Since we always have at least one input and one output, not expecting any + # degradation or production templates. if ( not positive_controller_concepts and not negative_controller_concepts @@ -206,9 +166,6 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: and len(negative_controller_concepts) >= 1 ): if len(negative_controller_concepts) == 1: - - # for degradation, we sometimes have more than one input, how to handle - # this? templates.append( ControlledDegradation( controller=negative_controller_concepts[0], @@ -242,14 +199,11 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: ) ) - # initial level for each species is intMax, due to libsbml processing, not actually - # stored in the model - # use current level of species for now initials = {} for qual_species in self.qual_model_plugin.qualitative_species: initials[qual_species.name] = Initial( concept=concepts[qual_species.id], - expression=SympyExprStr(qual_species.level), + expression=qual_species.level, ) template_model = TemplateModel( @@ -260,8 +214,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: def _extract_concepts(self) -> Mapping[str, Concept]: concepts = {} for species in self.qual_model_plugin.getListOfQualitativeSpecies(): - # QualitativeSpecies doesn't have units attribute. Cannot use get_object_units method - units = None + units = self.get_object_units(species) concept = _extract_concept( species, model_id=self.model_id, units=units ) @@ -269,7 +222,8 @@ def _extract_concepts(self) -> Mapping[str, Concept]: return concepts def get_object_units(self, object): - if object.units: + # QualitativeSpecies object does not have units attribute + if hasattr(object, "units"): if object.units == "dimensionless": return Unit(expression=sympy.Integer(1)) else: @@ -283,7 +237,9 @@ def _extract_concept(species, units=None, model_id=None): species_name = species.getName() display_name = species_name - annotation_string = species.getAnnotationString() + annotation_string = None + + # annotation_string = species.getAnnotationString() # namespace error when using etree with a qualitative species' annotation string # annotation_tree = etree.fromstring(annotation_string) @@ -309,135 +265,17 @@ def _extract_concept(species, units=None, model_id=None): return concept +# models do not have an annotation string def get_model_annotations(sbml_model): + """Get the model annotations from the SBML model.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None +# models do not have an annotation string def get_model_id(sbml_model): """Get the model ID from the SBML model annotation.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None - - -apoptosis_file_new = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Apoptosis_stable.sbml?ref_type=heads" -) - -coagulation_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Coagulation-pathway_stable.sbml?ref_type=heads" -) - -stress_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ER_Stress_stable.sbml?ref_type=heads" -) - -etc_stable_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ETC_stable.sbml?ref_type=heads" -) - -e_protein_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/E_protein_stable.sbml?ref_type=heads" -) - -hmox1_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/HMOX1_Pathway_stable.sbml?ref_type=heads" -) - -ifn_lambda_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/IFN-lambda_stable.sbml?ref_type=heads" -) - -interferon_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Interferon1_stable.sbml?ref_type=heads" -) - -jnk_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/JNK_pathway_stable.sbml?ref_type=heads" -) -kyu_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Kynurenine_pathway_stable.sbml?ref_type=heads" -) -nlrp3_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/NLRP3_Activation_stable.sbml?ref_type=heads" -) -nsp_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp14_stable.sbml?ref_type=heads" -) -nsp4_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp4_Nsp6_stable.sbml?ref_type=heads" -) -nsp9_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp9_protein_stable.sbml?ref_type=heads" -) -orf10_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf10_Cul2_pathway_stable.sbml?ref_type=heads" -) -orf3a_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads" -) -pamp_signal_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/PAMP_signaling_stable.sbml?ref_type=heads" -) -pyrimidine_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Pyrimidine_deprivation_stable.sbml?ref_type=heads" -) -rtc_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/RTC-and-transcription_stable.sbml?ref_type=heads" -) -renin_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Renin_angiotensin_stable.sbml?ref_type=heads" -) -tgfb_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/TGFB_pathway_stable.sbml?ref_type=heads" -) -virus_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Virus_replication_cycle_stable.sbml?ref_type=heads" -) -file_list = [ - stress_file, - # apoptosis_file_new, - # coagulation_file, - # etc_stable_file, - # e_protein_file, - # hmox1_file, - # ifn_lambda_file, - # jnk_file, - # kyu_file, - # nlrp3_file, - # nsp_file, - # nsp4_file, - # nsp9_file, - # orf10_file, - # orf3a_file, - # pamp_signal_file, - # pyrimidine_file, - # rtc_file, - # renin_file, - # tgfb_file, - # virus_file, -] - - -def test_qual(): - for file in file_list: - xml_string = file.text - sbml_document = SBMLReader().readSBMLFromString(xml_string) - sbml_document.setPackageRequired("qual", True) - model = sbml_document.getModel() - qual_model_plugin = model.getPlugin("qual") - processor = SbmlQualProcessor(model, qual_model_plugin) - tm = processor.extract_model() - - -def test_old(): - model_id = "BIOMD0000000955" - from mira.sources.biomodels import ( - get_sbml_model, - template_model_from_sbml_string, - ) - - xml_string = get_sbml_model(model_id) - model = template_model_from_sbml_string(xml_string) From d073ea04e63d36ef1482a9bf73bb7d894c775544 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 9 Apr 2024 13:45:05 -0400 Subject: [PATCH 09/44] Add api for sbml qual models --- mira/sources/sbml/qual_api.py | 165 ++++++++++++++++++++++++++++++++++ 1 file changed, 165 insertions(+) create mode 100644 mira/sources/sbml/qual_api.py diff --git a/mira/sources/sbml/qual_api.py b/mira/sources/sbml/qual_api.py new file mode 100644 index 000000000..70cc2ee19 --- /dev/null +++ b/mira/sources/sbml/qual_api.py @@ -0,0 +1,165 @@ +from typing import Iterable, Optional + +from libsbml import SBMLReader + +from mira.metamodel import TemplateModel +from .qual import SbmlQualProcessor + +__all__ = [ + "template_model_from_sbml_qual_file", + "template_model_from_sbml_qual_file_obj", + "template_model_from_sbml_qual_string", + "template_model_from_sbml_qual_model", + "sbml_qual_model_from_file", +] + + +def template_model_from_sbml_qual_file( + file_path, + *, + model_id: Optional[str] = None, + reporter_ids: Optional[Iterable[str]] = None, +) -> TemplateModel: + """Extract a MIRA template model from a file containing SBML Qual XML. + + Parameters + ---------- + file_path : + The path to the SBML Qual file. + model_id : + The ID of the model to extract. (Optional) If not provided, an attempt + will be made to extract an ID from the SBML Qual file if it's a BIOMODELS + model. + reporter_ids : + An iterable of reporter IDs + + Returns + ------- + : + The extracted MIRA template model. + """ + sbml_model, qual_model = sbml_qual_model_from_file(file_path) + return template_model_from_sbml_qual_model( + sbml_model, qual_model, model_id=model_id, reporter_ids=reporter_ids + ) + + +def template_model_from_sbml_qual_file_obj( + file, + *, + model_id: Optional[str] = None, + reporter_ids: Optional[Iterable[str]] = None, +) -> TemplateModel: + """Extract a MIRA template model from a file object containing SBML Qual XML. + + Parameters + ---------- + file : + The open file object containing the SBML Qual XML. + model_id : + The ID of the model to extract. (Optional) If not provided, an attempt + will be made to extract an ID from the SBML Qual file if it's a BIOMODELS + model. + reporter_ids : + An iterable of reporter IDs + + Returns + ------- + : + The extracted MIRA template model. + """ + return template_model_from_sbml_qual_string( + file.read().decode("utf-8"), + model_id=model_id, + reporter_ids=reporter_ids, + ) + + +def sbml_qual_model_from_file(fname): + """Return an SBML model object and SBML Qual model object from an SBML Qual file. + + Parameters + ---------- + fname : + The path to the SBML Qual file. + + Returns + ------- + : + An SBML model object. + : + An SBMl Qual Model object. + """ + with open(fname, "rb") as fh: + sbml_string = fh.read().decode("utf-8") + sbml_document = SBMLReader().readSBMLFromString(sbml_string) + sbml_model = sbml_document.getModel() + qual_model_plugin = sbml_model.getPlugin("qual") + return sbml_model, qual_model_plugin + + +def template_model_from_sbml_qual_string( + s: str, + *, + model_id: Optional[str] = None, + reporter_ids: Optional[Iterable[str]] = None, +) -> TemplateModel: + """Extract a MIRA template model from a string representing SBML Qual XML. + + Parameters + ---------- + s : + The string containing the SBML Qual XML. + model_id : + The ID of the model to extract. (Optional) If not provided, an attempt + will be made to extract an ID from the SBML Qual xml if it's a BIOMODELS + model. + reporter_ids : + An iterable of reporter IDs + + Returns + ------- + : + The extracted TemplateModel. + """ + sbml_document = SBMLReader().readSBMLFromString(s) + sbml_model = sbml_document.getModel() + qual_model_plugin = sbml_model.getPlugin("qual") + return template_model_from_sbml_qual_model( + sbml_model, + qual_model_plugin, + model_id=model_id, + reporter_ids=reporter_ids, + ) + + +def template_model_from_sbml_qual_model( + sbml_model, + qual_model, + *, + model_id: Optional[str] = None, + reporter_ids: Optional[Iterable[str]] = None, +) -> TemplateModel: + """Extract a MIRA template model from an SBML Qual model object. + + Parameters + ---------- + sbml_model : + The SBML model object. + qual_model : + The SBML Qual model object + model_id : + The ID of the model to extract. (Optional) If not provided, an attempt + will be made to extract an ID from the SBML Qual model if it's a BIOMODELS + model. + + Returns + ------- + : + The extracted TemplateModel. + """ + processor = SbmlQualProcessor( + sbml_model, qual_model, model_id=model_id, reporter_ids=reporter_ids + ) + tm = processor.extract_model() + return tm From 6bf00b9d9d3a647553c85dd2a89e6b06cf4c5993 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 9 Apr 2024 13:52:18 -0400 Subject: [PATCH 10/44] Add qual api to sources documentation --- docs/source/sources.rst | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/docs/source/sources.rst b/docs/source/sources.rst index 3ab48fc50..f19fe6576 100644 --- a/docs/source/sources.rst +++ b/docs/source/sources.rst @@ -41,6 +41,13 @@ SBML extraction (:py:mod:`mira.sources.sbml`) :members: :show-inheritance: +SBML qual extraction (:py:mod:`mira.sources.sbml.qual_api`) +----------------------------------------------------------- +.. automodule:: mira.sources.sbml.qual_api + :members: + :show-inheritance: + + BioModels client (:py:mod:`mira.sources.biomodels`) --------------------------------------------------- .. automodule:: mira.sources.biomodels From 798d5fd234c1b1564083eeaf51c2c694c71847c2 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 9 Apr 2024 15:06:19 -0400 Subject: [PATCH 11/44] Clean comments and add unit processing --- mira/sources/sbml/qual.py | 125 ++++++++++++++++++++++++++++++-------- 1 file changed, 98 insertions(+), 27 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 644585565..22626b80f 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -5,6 +5,9 @@ import sympy from tqdm import tqdm +from lxml import etree +import xml.etree.ElementTree as ET +import libsbml class TqdmLoggingHandler(logging.Handler): @@ -34,13 +37,16 @@ def __init__( self.reporter_ids = reporter_ids # unit_definitions is empty for sbml_model - # self.units = get_units(self.sbml_model.unit_definitions) + self.units = get_units(self.sbml_model.unit_definitions) def extract_model(self): - # model_id, if self.model_id is None: - self.model_id = get_model_id(self.sbml_model) - model_annots = get_model_annotations(self.sbml_model) + self.model_id = get_model_id( + self.sbml_model, self.qual_model_plugin + ) + model_annots = get_model_annotations( + self.sbml_model, self.qual_model_plugin + ) reporter_ids = set(self.reporter_ids or []) concepts = self._extract_concepts() @@ -57,14 +63,15 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # parameters and compartment attributes for sbml_model are empty, they don't exist for # the qual_model_plugin - # instead of a simple logic formula, there is a flag called qual:sign = positive - # then there exists a formula, positive controller means it controls the prooduction - # of something - # if there's a qual:sign = negative, - # qual negative means there's a controller which controls degradation + # each input to a transition can have a negative or positive sign + # qual:sign = positive in source file indicates it controls the production of something + # qual:sign = negative in source file indicates it controls the degradation of something # if both positive and negative exists, it is production process, with a list of # controllers from both the negative and positive side. + # Transitions always have at least one input and one output + # Since we always have at least one input, there will always be at least + # 1 controller (negative or positive). Will never have a natural template for transition_id, transition in enumerate( self.qual_model_plugin.transitions ): @@ -81,7 +88,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # negative sign is 0, positive sign is 1 for inputs only # outputs do not have a sign - # Inputs will always be 0 or 1 + # inputs will always be 0 or 1 positive_controller_names = [ qual_species.qualitative_species for qual_species in transition.getListOfInputs() @@ -103,12 +110,6 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: negative_controller_names ) - # transitions always have at least one input and one output - # Since we always have at least one input, there will always be at least - # 1 controller (negative or positive). Will never have a natural template - - # Since we always have at least one input and one output, not expecting any - # degradation or production templates. if ( not positive_controller_concepts and not negative_controller_concepts @@ -187,8 +188,6 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: len(positive_controller_concepts) >= 1 and len(negative_controller_concepts) >= 1 ): - # Since inputs are only positive or negative, won't have overlapping concepts - # when adding the two lists together templates.append( GroupedControlledProduction( controllers=positive_controller_concepts @@ -237,13 +236,11 @@ def _extract_concept(species, units=None, model_id=None): species_name = species.getName() display_name = species_name - annotation_string = None - - # annotation_string = species.getAnnotationString() + annotation_string = species.getAnnotationString() # namespace error when using etree with a qualitative species' annotation string # annotation_tree = etree.fromstring(annotation_string) - + if not annotation_string: logger.debug(f"[{model_id} species:{species_id}] had no annotations") concept = Concept( @@ -265,17 +262,91 @@ def _extract_concept(species, units=None, model_id=None): return concept -# models do not have an annotation string -def get_model_annotations(sbml_model): - """Get the model annotations from the SBML model.""" +# qual_model doesn't have any attribute or method to retrieve annotation. sbml_model annotation +# is an empty string +def get_model_annotations(sbml_model, qual_model): + """Get the model annotations from the SBML qual model.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None # models do not have an annotation string -def get_model_id(sbml_model): - """Get the model ID from the SBML model annotation.""" +def get_model_id(sbml_model, qual_model): + """Get the model ID from the SBML qual model annotation.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None + + +def get_units(unit_definitions): + """Return units from a list of unit definition blocks.""" + units = {} + for unit_def in unit_definitions: + units[unit_def.id] = process_unit_definition(unit_def) + return units + + +unit_symbol_mappings = { + "item": "person", + "metre": "meter", + "litre": "liter", +} +unit_expression_mappings = { + 86400.0 * sympy.Symbol("second"): sympy.Symbol("day"), + 1 / (86400.0 * sympy.Symbol("second")): 1 / sympy.Symbol("day"), + 1 + / (86400.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("day") * sympy.Symbol("person")), + 31536000.0 * sympy.Symbol("second"): sympy.Symbol("year"), + 1 / (31536000.0 * sympy.Symbol("second")): 1 / sympy.Symbol("year"), + 1 + / (31536000.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("year") * sympy.Symbol("person")), +} + + +def process_unit_definition(unit_definition): + """Process a unit definition block to extract an expression.""" + full_unit_expr = sympy.Integer(1) + for unit in unit_definition.units: + unit_symbol_str = SBML_UNITS[unit.kind] + # We assume person instead of item here + if unit_symbol_str in unit_symbol_mappings: + unit_symbol_str = unit_symbol_mappings[unit_symbol_str] + unit_symbol = sympy.Symbol(unit_symbol_str) + # We do this to avoid the spurious factors in the expression + if unit.multiplier != 1: + unit_symbol *= unit.multiplier + if unit.exponent != 1: + unit_symbol **= unit.exponent + if unit.scale != 0: + unit_symbol *= 10**unit.scale + full_unit_expr *= unit_symbol + # We apply some mappings for canonical units we want to change + # We use equals here since == in sympy is structural equality + for k, v in unit_expression_mappings.items(): + if full_unit_expr.equals(k): + full_unit_expr = v + return full_unit_expr + + +def get_sbml_units(): + """Build up a mapping of SBML unit kinds to their names. + + This is necessary because units are given as numbers. + """ + module_contents = dir(libsbml) + unit_kinds = { + var: var.split("_")[-1].lower() + for var in module_contents + if var.startswith("UNIT_KIND") and var != "UNIT_KIND_INVALID" + } + unit_kinds = { + getattr(libsbml, var): unit_name + for var, unit_name in unit_kinds.items() + } + return unit_kinds + + +SBML_UNITS = get_sbml_units() From 58ebf2d1a26e5f09c9fdd88d91232a3b4b800108 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 10 Apr 2024 10:16:47 -0400 Subject: [PATCH 12/44] Add resources and Converter class --- mira/sources/sbml/qual.py | 59 +++++++++++++++++++++++++++++++++++++-- 1 file changed, 57 insertions(+), 2 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 22626b80f..6039d87e8 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -1,8 +1,9 @@ import logging -from typing import List, Mapping +from typing import List, Mapping, Optional from mira.metamodel import * +import bioregistry import sympy from tqdm import tqdm from lxml import etree @@ -26,6 +27,60 @@ def emit(self, record): logger = logging.getLogger(__name__) logger.addHandler(TqdmLoggingHandler()) +PREFIX_MAP = { + "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "dcterms": "http://purl.org/dc/terms/", + "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", + "vCard4": "http://www.w3.org/2006/vcard/ns#", + "bqbiol": "http://biomodels.net/biology-qualifiers/", + "bqmodel": "http://biomodels.net/model-qualifiers/", + "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", + "copasi": "http://www.copasi.org/static/sbml", + "jd": "http://www.sys-bio.org/sbml", +} +RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" +#: This XPath query gets annotations on species for their structured +#: identifiers, typically given as MIRIAM URIs or URNs +IDENTIFIERS_XPATH = f"rdf:RDF/rdf:Description/bqbiol:is/rdf:Bag/rdf:li" +COPASI_DESCR_XPATH = "/annotation/*[2]/rdf:RDF/rdf:Description" +COPASI_IS = "%s/CopasiMT:is" % COPASI_DESCR_XPATH +COPASI_IS_VERSION_OF = "%s/CopasiMT:isVersionOf" % COPASI_DESCR_XPATH +COPASI_HAS_PROPERTY = "%s/bqbiol:hasProperty" % COPASI_DESCR_XPATH +#: This is an alternative XPath for groundings that use the isVersionOf +#: relation and are thus less specific than the one above but can be used +#: as fallback +IDENTIFIERS_VERSION_XPATH = ( + f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" +) +#: This XPath query gets annotations on species about their properties, +#: which typically help ad-hoc create subclasses that are more specific +PROPERTIES_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" +#: This query helps get annotations on reactions, like "this reaction is a +#: _protein-containing complex disassembly_ (GO:0043624)" +IS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" + + +class Converter: + """Wrapper around a curies converter with lazy loading.""" + + def __init__(self): + self.converter = None + + def parse_uri(self, uri): + """Parse a URI into a prefix/identifier pair.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.parse_uri(uri) + + def uri_to_curie(self, uri: str) -> Optional[str]: + """Turn a URI into a CURIE.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.compress(uri) + + +converter = Converter() + class SbmlQualProcessor: def __init__( @@ -240,7 +295,7 @@ def _extract_concept(species, units=None, model_id=None): # namespace error when using etree with a qualitative species' annotation string # annotation_tree = etree.fromstring(annotation_string) - + if not annotation_string: logger.debug(f"[{model_id} species:{species_id}] had no annotations") concept = Concept( From fdd45d0e3b93f22bfaf23d5ea9813ce2a117793b Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 12 Apr 2024 14:19:04 -0400 Subject: [PATCH 13/44] Add grounding for concepts --- mira/sources/sbml/qual.py | 236 +++++++++++++++++++++++++++++++++----- 1 file changed, 209 insertions(+), 27 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 6039d87e8..0e14fbf57 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -1,7 +1,12 @@ import logging +import csv +import copy +import re from typing import List, Mapping, Optional +from copy import deepcopy from mira.metamodel import * +from mira.resources import get_resource_file import bioregistry import sympy @@ -38,26 +43,11 @@ def emit(self, record): "copasi": "http://www.copasi.org/static/sbml", "jd": "http://www.sys-bio.org/sbml", } + + RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" -#: This XPath query gets annotations on species for their structured -#: identifiers, typically given as MIRIAM URIs or URNs -IDENTIFIERS_XPATH = f"rdf:RDF/rdf:Description/bqbiol:is/rdf:Bag/rdf:li" -COPASI_DESCR_XPATH = "/annotation/*[2]/rdf:RDF/rdf:Description" -COPASI_IS = "%s/CopasiMT:is" % COPASI_DESCR_XPATH -COPASI_IS_VERSION_OF = "%s/CopasiMT:isVersionOf" % COPASI_DESCR_XPATH -COPASI_HAS_PROPERTY = "%s/bqbiol:hasProperty" % COPASI_DESCR_XPATH -#: This is an alternative XPath for groundings that use the isVersionOf -#: relation and are thus less specific than the one above but can be used -#: as fallback -IDENTIFIERS_VERSION_XPATH = ( - f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" -) -#: This XPath query gets annotations on species about their properties, -#: which typically help ad-hoc create subclasses that are more specific -PROPERTIES_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" -#: This query helps get annotations on reactions, like "this reaction is a -#: _protein-containing complex disassembly_ (GO:0043624)" -IS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" +DESCRIPTION_XPATH = f".//bqbiol:isDescribedBy/rdf:Bag/rdf:li" +ENCODED_XPATH = f".//bqbiol:isEncodedBy/rdf:Bag/rdf:li" class Converter: @@ -291,12 +281,34 @@ def _extract_concept(species, units=None, model_id=None): species_name = species.getName() display_name = species_name - annotation_string = species.getAnnotationString() + if (model_id, species_name) in grounding_map: + mapped_ids, mapped_context = grounding_map[(model_id, species_name)] + concept = Concept( + name=species_name, + display_name=display_name, + identifiers=copy.deepcopy(mapped_ids), + context=copy.deepcopy(mapped_context), + units=units, + ) + return concept + else: + logger.debug( + f"[{model_id} species:{species_id}] not found in grounding map" + ) + + old_annotation_string = species.getAnnotationString() - # namespace error when using etree with a qualitative species' annotation string - # annotation_tree = etree.fromstring(annotation_string) + # current annotation misses a namespace for the rdf tag and cannot be used to create an etree + # we add a new tag arbitrarily named "element" and add a namespace to create valid xml + # such that it can be parsed by the etree.fromstring() method + new_annotation_string = ( + """""" + + old_annotation_string + + "" + ) - if not annotation_string: + if not old_annotation_string: logger.debug(f"[{model_id} species:{species_id}] had no annotations") concept = Concept( name=species_name, @@ -307,13 +319,111 @@ def _extract_concept(species, units=None, model_id=None): ) return concept + annotation_tree = etree.fromstring(new_annotation_string) + + # Instead of URIs found in regular SBML, the resources found in the annotation strings for + # these qualitative species are already in CURIE format + + description_strings = [ + desc.attrib[RESOURCE_KEY] + for desc in annotation_tree.findall( + DESCRIPTION_XPATH, namespaces=PREFIX_MAP + ) + ] + + encoded_strings = [ + desc.attrib[RESOURCE_KEY] + for desc in annotation_tree.findall( + ENCODED_XPATH, namespaces=PREFIX_MAP + ) + ] + + description_curies_list, encoded_curies_list = [], [] + + # identifiers, typically given as MIRIAM URIs or URNs + # remove URNs, meta-prefixes and extract only prefixes and identifiers in tuple format + # for descriptions and encodings strings for a qualitative species + for description_annotation in description_strings: + if "miriam" and "hgnc.symbol" in description_annotation: + pattern = r"hgnc\.symbol:(.*)" + match = re.search(pattern, description_annotation) + curie = ("hgnc", match.group(1)) + description_curies_list.append(curie) + elif "miriam" in description_annotation: + pattern = r":([^:]+):([^:]+)$" + match = re.search(pattern, description_annotation) + curie = tuple(match.groups()) + description_curies_list.append(curie) + + for encoded_annotation in encoded_strings: + if "miriam" and "hgnc.symbol" in encoded_annotation: + pattern = r"hgnc\.symbol:(.*)" + match = re.search(pattern, encoded_annotation) + curie = ("hgnc", match.group(1)) + encoded_curies_list.append(curie) + elif "miriam" in encoded_annotation: + pattern = r":([^:]+):([^:]+)$" + match = re.search(pattern, encoded_annotation) + curie = tuple(match.groups()) + encoded_curies_list.append(curie) + + context = {} + + if ("ido", "C101887") in encoded_curies_list: + encoded_curies_list.remove(("ido", "C101887")) + encoded_curies_list.append(("ncit", "C101887")) + if ("ncit", "C171133") in encoded_curies_list: + encoded_curies_list.remove(("ncit", "C171133")) + # Reclassify asymptomatic as a disease status + if ("ido", "0000569") in encoded_curies_list and ( + "ido", + "0000511", + ) in encoded_curies_list: + encoded_curies_list.remove(("ido", "0000569")) + context["disease_status"] = "ncit:C3833" + # Exposed shouldn't be susceptible + if ("ido", "0000514") in encoded_curies_list and ( + "ido", + "0000597", + ) in encoded_curies_list: + encoded_curies_list.remove(("ido", "0000514")) + # Break apoart hospitalized and ICU + if ("ncit", "C25179") in encoded_curies_list and ( + "ncit", + "C53511", + ) in encoded_curies_list: + encoded_curies_list.remove(("ncit", "C53511")) + context["disease_status"] = "ncit:C53511" + # Remove redundant term for deceased due to disease progression + if ("ncit", "C28554") in encoded_curies_list and ( + "ncit", + "C168970", + ) in encoded_curies_list: + encoded_curies_list.remove(("ncit", "C168970")) + + encodings = dict(encoded_curies_list) + + for idx, description_property in enumerate(sorted(description_curies_list)): + if description_property[0] == "ncit" and description_property[ + 1 + ].startswith("000"): + prop = ("ido", description_property[1]) + elif description_property[0] == "ido" and description_property[ + 1 + ].startswith("C"): + prop = ("ncit", description_property[1]) + else: + prop = description_property + context[f'property{"" if idx == 0 else idx}'] = ":".join(prop) + concept = Concept( - name=species_name, + name=species_name or species_id, display_name=display_name, - identifiers={}, - context={}, + identifiers=encodings, + context=context, units=units, ) + concept = grounding_normalize(concept) return concept @@ -326,7 +436,8 @@ def get_model_annotations(sbml_model, qual_model): return None -# models do not have an annotation string +# qual_model doesn't have any attribute or method to retrieve annotation. sbml_model annotation +# is an empty string def get_model_id(sbml_model, qual_model): """Get the model ID from the SBML qual model annotation.""" ann_xml = sbml_model.getAnnotationString() @@ -405,3 +516,74 @@ def get_sbml_units(): SBML_UNITS = get_sbml_units() + + +def _get_grounding_map(): + def parse_identifier_grounding(grounding_str): + # Example: ido:0000511/infected population from which we want to get + # {'ido': '0000511'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split(":")) + for grounding in grounding_str.split("|") + ) + + def parse_context_grounding(grounding_str): + # Example: disease_severity=ncit:C25269/Symptomatic| + # diagnosis=ncit:C113725/Undiagnosed + # from which we want to get {'disease_severity': 'ncit:C25269', + # 'diagnosis': 'ncit:C113725'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split("=")) + for grounding in grounding_str.split("|") + ) + + fname = get_resource_file("mapped_biomodels_groundings.csv") + mappings = {} + with open(fname, "r") as fh: + reader = csv.reader(fh) + next(reader) + for name, ids, context, model, mapped_ids, mapped_context in reader: + mappings[(model, name)] = ( + parse_identifier_grounding(mapped_ids), + parse_context_grounding(mapped_context), + ) + + return mappings + + +grounding_map = _get_grounding_map() + + +def grounding_normalize(concept): + # A common curation mistake in BioModels: mixing up IDO and NCIT identifiers + for k, v in deepcopy(concept.identifiers).items(): + if k == "ncit" and v.startswith("000"): + concept.identifiers.pop(k) + concept.identifiers["ido"] = v + elif k == "ido" and v.startswith("C"): + concept.identifiers.pop(k) + concept.identifiers["ncit"] = v + # Has property acquired immunity == immune population + if not concept.get_curie()[0] and concept.context == { + "property": "ido:0000621" + }: + concept.identifiers["ido"] = "0000592" + concept.context = {} + elif concept.get_curie() == ("ido", "0000514") and concept.context == { + "property": "ido:0000468" + }: + concept.context = {} + # Different ways of expression immune/recovered + elif concept.get_curie() == ("ncit", "C171133") and concept.context == { + "property": "ido:0000621" + }: + concept.identifiers = {"ido": "0000592"} + concept.context = {} + # Different terms for dead/deceased + elif concept.get_curie() == ("ncit", "C168970"): + concept.identifiers = {"ncit": "C28554"} + return concept From 96784cf9b63f7fb48a8407ac6900bf0b703638ed Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 12 Apr 2024 15:58:34 -0400 Subject: [PATCH 14/44] Assign identifiers and deterministically select identifier by alphabetical order for a concept --- mira/sources/sbml/qual.py | 77 ++++++++++++++++++++++++++------------- 1 file changed, 51 insertions(+), 26 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 0e14fbf57..19802bdde 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -338,22 +338,28 @@ def _extract_concept(species, units=None, model_id=None): ) ] - description_curies_list, encoded_curies_list = [], [] + identifiers_curie_list, encoded_curies_list = [], [] # identifiers, typically given as MIRIAM URIs or URNs # remove URNs, meta-prefixes and extract only prefixes and identifiers in tuple format # for descriptions and encodings strings for a qualitative species for description_annotation in description_strings: + # for resources in the format of urn:{metaprefix}:hgnc.symbol:{identifier} if "miriam" and "hgnc.symbol" in description_annotation: pattern = r"hgnc\.symbol:(.*)" match = re.search(pattern, description_annotation) curie = ("hgnc", match.group(1)) - description_curies_list.append(curie) + identifiers_curie_list.append(curie) + + # hacky fix to eliminate processing resources such as 'urn:miriam:ec-code:3.4.22.62' + # where ec-code isn't a valid prefix and 3.4.22.62 is not a valid identifier + # if we are not processing a hgnc.symbol, we then look for a resource with format + # urn:{metaprefix}:{prefix}:{identifier} by counting number of ":" which should be 4 elif "miriam" in description_annotation: pattern = r":([^:]+):([^:]+)$" match = re.search(pattern, description_annotation) curie = tuple(match.groups()) - description_curies_list.append(curie) + identifiers_curie_list.append(curie) for encoded_annotation in encoded_strings: if "miriam" and "hgnc.symbol" in encoded_annotation: @@ -361,7 +367,11 @@ def _extract_concept(species, units=None, model_id=None): match = re.search(pattern, encoded_annotation) curie = ("hgnc", match.group(1)) encoded_curies_list.append(curie) - elif "miriam" in encoded_annotation: + + elif ( + "miriam" in encoded_annotation + and encoded_annotation.count(":") == 4 + ): pattern = r":([^:]+):([^:]+)$" match = re.search(pattern, encoded_annotation) curie = tuple(match.groups()) @@ -369,41 +379,56 @@ def _extract_concept(species, units=None, model_id=None): context = {} - if ("ido", "C101887") in encoded_curies_list: - encoded_curies_list.remove(("ido", "C101887")) - encoded_curies_list.append(("ncit", "C101887")) - if ("ncit", "C171133") in encoded_curies_list: - encoded_curies_list.remove(("ncit", "C171133")) - # Reclassify asymptomatic as a disease status - if ("ido", "0000569") in encoded_curies_list and ( + if ("ido", "C101887") in identifiers_curie_list: + identifiers_curie_list.remove(("ido", "C101887")) + identifiers_curie_list.append(("ncit", "C101887")) + if ("ncit", "C171133") in identifiers_curie_list: + identifiers_curie_list.remove(("ncit", "C171133")) + # Reclassify asymptomatic as a disease status + if ("ido", "0000569") in identifiers_curie_list and ( "ido", "0000511", - ) in encoded_curies_list: - encoded_curies_list.remove(("ido", "0000569")) + ) in identifiers_curie_list: + identifiers_curie_list.remove(("ido", "0000569")) context["disease_status"] = "ncit:C3833" - # Exposed shouldn't be susceptible - if ("ido", "0000514") in encoded_curies_list and ( + # Exposed shouldn't be susceptible + if ("ido", "0000514") in identifiers_curie_list and ( "ido", "0000597", - ) in encoded_curies_list: - encoded_curies_list.remove(("ido", "0000514")) - # Break apoart hospitalized and ICU - if ("ncit", "C25179") in encoded_curies_list and ( + ) in identifiers_curie_list: + identifiers_curie_list.remove(("ido", "0000514")) + # Break apoart hospitalized and ICU + if ("ncit", "C25179") in identifiers_curie_list and ( "ncit", "C53511", - ) in encoded_curies_list: - encoded_curies_list.remove(("ncit", "C53511")) + ) in identifiers_curie_list: + identifiers_curie_list.remove(("ncit", "C53511")) context["disease_status"] = "ncit:C53511" - # Remove redundant term for deceased due to disease progression - if ("ncit", "C28554") in encoded_curies_list and ( + # Remove redundant term for deceased due to disease progression + if ("ncit", "C28554") in identifiers_curie_list and ( "ncit", "C168970", ) in encoded_curies_list: encoded_curies_list.remove(("ncit", "C168970")) - encodings = dict(encoded_curies_list) + #TODO: Currently multiple CURIEs are extracted with the same prefix but different + # identifier. For example, the list of identifier CURIEs may contain ncbigene:596 (BCL2) and + # ncbigene:4170 (MCL1). This seems to indicate that the all the list contains CURIEs for + # different agents involved in the transition. + + # Multiple CURIEs associated with a single concept. These concepts have different prefixes + # but semantically map to the same agent. They are stored in the all_identifiers dictionary + # deterministically choose the CURIE to use as the identifier by sorting the keys of the + # identifiers dictionary (prefix) alphabetically + all_identifiers = dict(sorted(dict(identifiers_curie_list).items())) + if all_identifiers: + chosen_key = next(iter(all_identifiers)) + identifiers = {chosen_key: all_identifiers[chosen_key]} + else: + identifiers = {} - for idx, description_property in enumerate(sorted(description_curies_list)): + # we capture context using the encoding curies as a set of generic properties + for idx, description_property in enumerate(sorted(encoded_curies_list)): if description_property[0] == "ncit" and description_property[ 1 ].startswith("000"): @@ -419,7 +444,7 @@ def _extract_concept(species, units=None, model_id=None): concept = Concept( name=species_name or species_id, display_name=display_name, - identifiers=encodings, + identifiers=identifiers, context=context, units=units, ) From 3838a52b754bac5b963faa973d49b9625dd5012a Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 16 Apr 2024 13:48:00 -0400 Subject: [PATCH 15/44] Add preprocessing for CURIEs, update variable names to be more informative --- mira/sources/sbml/qual.py | 62 +++++++++++++++++++-------------------- 1 file changed, 30 insertions(+), 32 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 19802bdde..2773b18cb 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -4,16 +4,16 @@ import re from typing import List, Mapping, Optional from copy import deepcopy +from urllib.parse import unquote from mira.metamodel import * from mira.resources import get_resource_file import bioregistry import sympy +import libsbml from tqdm import tqdm from lxml import etree -import xml.etree.ElementTree as ET -import libsbml class TqdmLoggingHandler(logging.Handler): @@ -277,9 +277,8 @@ def get_object_units(self, object): def _extract_concept(species, units=None, model_id=None): - species_id = species.getId() - species_name = species.getName() - display_name = species_name + species_name = species.getId() + display_name = species.getName() if (model_id, species_name) in grounding_map: mapped_ids, mapped_context = grounding_map[(model_id, species_name)] @@ -293,7 +292,7 @@ def _extract_concept(species, units=None, model_id=None): return concept else: logger.debug( - f"[{model_id} species:{species_id}] not found in grounding map" + f"[{model_id} species:{species_name}] not found in grounding map" ) old_annotation_string = species.getAnnotationString() @@ -309,7 +308,7 @@ def _extract_concept(species, units=None, model_id=None): ) if not old_annotation_string: - logger.debug(f"[{model_id} species:{species_id}] had no annotations") + logger.debug(f"[{model_id} species:{species_name}] had no annotations") concept = Concept( name=species_name, display_name=display_name, @@ -322,16 +321,17 @@ def _extract_concept(species, units=None, model_id=None): annotation_tree = etree.fromstring(new_annotation_string) # Instead of URIs found in regular SBML, the resources found in the annotation strings for - # these qualitative species are already in CURIE format + # these qualitative species are already in CURIE format with the "urn" prefix and meta prefix + # attached. We remove the "urn" identifier and metaprefix later - description_strings = [ + description_strings_list = [ desc.attrib[RESOURCE_KEY] for desc in annotation_tree.findall( DESCRIPTION_XPATH, namespaces=PREFIX_MAP ) ] - encoded_strings = [ + encoded_strings_list = [ desc.attrib[RESOURCE_KEY] for desc in annotation_tree.findall( ENCODED_XPATH, namespaces=PREFIX_MAP @@ -343,37 +343,34 @@ def _extract_concept(species, units=None, model_id=None): # identifiers, typically given as MIRIAM URIs or URNs # remove URNs, meta-prefixes and extract only prefixes and identifiers in tuple format # for descriptions and encodings strings for a qualitative species - for description_annotation in description_strings: + for description_string in description_strings_list: + description_string = unquote(description_string) + # for resources in the format of urn:{metaprefix}:hgnc.symbol:{identifier} - if "miriam" and "hgnc.symbol" in description_annotation: + if "miriam" and "hgnc.symbol" in description_string: pattern = r"hgnc\.symbol:(.*)" - match = re.search(pattern, description_annotation) + match = re.search(pattern, description_string) curie = ("hgnc", match.group(1)) identifiers_curie_list.append(curie) - # hacky fix to eliminate processing resources such as 'urn:miriam:ec-code:3.4.22.62' - # where ec-code isn't a valid prefix and 3.4.22.62 is not a valid identifier - # if we are not processing a hgnc.symbol, we then look for a resource with format - # urn:{metaprefix}:{prefix}:{identifier} by counting number of ":" which should be 4 - elif "miriam" in description_annotation: + # for all other resources + elif "miriam" in description_string: pattern = r":([^:]+):([^:]+)$" - match = re.search(pattern, description_annotation) + match = re.search(pattern, description_string) curie = tuple(match.groups()) identifiers_curie_list.append(curie) - for encoded_annotation in encoded_strings: - if "miriam" and "hgnc.symbol" in encoded_annotation: + for encoded_string in encoded_strings_list: + encoded_string = unquote(encoded_string) + if "miriam" and "hgnc.symbol" in encoded_string: pattern = r"hgnc\.symbol:(.*)" - match = re.search(pattern, encoded_annotation) + match = re.search(pattern, encoded_string) curie = ("hgnc", match.group(1)) encoded_curies_list.append(curie) - elif ( - "miriam" in encoded_annotation - and encoded_annotation.count(":") == 4 - ): + elif "miriam" in encoded_string: pattern = r":([^:]+):([^:]+)$" - match = re.search(pattern, encoded_annotation) + match = re.search(pattern, encoded_string) curie = tuple(match.groups()) encoded_curies_list.append(curie) @@ -397,7 +394,7 @@ def _extract_concept(species, units=None, model_id=None): "0000597", ) in identifiers_curie_list: identifiers_curie_list.remove(("ido", "0000514")) - # Break apoart hospitalized and ICU + # Break apart hospitalized and ICU if ("ncit", "C25179") in identifiers_curie_list and ( "ncit", "C53511", @@ -408,10 +405,10 @@ def _extract_concept(species, units=None, model_id=None): if ("ncit", "C28554") in identifiers_curie_list and ( "ncit", "C168970", - ) in encoded_curies_list: - encoded_curies_list.remove(("ncit", "C168970")) + ) in identifiers_curie_list: + identifiers_curie_list.remove(("ncit", "C168970")) - #TODO: Currently multiple CURIEs are extracted with the same prefix but different + # TODO: Currently multiple CURIEs are extracted with the same prefix but different # identifier. For example, the list of identifier CURIEs may contain ncbigene:596 (BCL2) and # ncbigene:4170 (MCL1). This seems to indicate that the all the list contains CURIEs for # different agents involved in the transition. @@ -421,6 +418,7 @@ def _extract_concept(species, units=None, model_id=None): # deterministically choose the CURIE to use as the identifier by sorting the keys of the # identifiers dictionary (prefix) alphabetically all_identifiers = dict(sorted(dict(identifiers_curie_list).items())) + if all_identifiers: chosen_key = next(iter(all_identifiers)) identifiers = {chosen_key: all_identifiers[chosen_key]} @@ -442,7 +440,7 @@ def _extract_concept(species, units=None, model_id=None): context[f'property{"" if idx == 0 else idx}'] = ":".join(prop) concept = Concept( - name=species_name or species_id, + name=species_name, display_name=display_name, identifiers=identifiers, context=context, From 9567a1ffac7b1baedb20a6f149e818f80993651d Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 16 Apr 2024 14:46:18 -0400 Subject: [PATCH 16/44] Update comments about species naming and id --- mira/sources/sbml/qual.py | 39 +++++++++++++++++++-------------------- 1 file changed, 19 insertions(+), 20 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 2773b18cb..a08848277 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -277,14 +277,16 @@ def get_object_units(self, object): def _extract_concept(species, units=None, model_id=None): - species_name = species.getId() - display_name = species.getName() + # retrieve local name for species that is only used a reference in the sbml qual model + local_qual_name_reference = species.getId() + # retrieve name of the species that can be used for look up in external resources + external_name = species.getName() - if (model_id, species_name) in grounding_map: - mapped_ids, mapped_context = grounding_map[(model_id, species_name)] + if (model_id, external_name) in grounding_map: + mapped_ids, mapped_context = grounding_map[(model_id, external_name)] concept = Concept( - name=species_name, - display_name=display_name, + name=external_name, + display_name=local_qual_name_reference, identifiers=copy.deepcopy(mapped_ids), context=copy.deepcopy(mapped_context), units=units, @@ -292,7 +294,7 @@ def _extract_concept(species, units=None, model_id=None): return concept else: logger.debug( - f"[{model_id} species:{species_name}] not found in grounding map" + f"[{model_id} species:{external_name}] not found in grounding map" ) old_annotation_string = species.getAnnotationString() @@ -308,10 +310,10 @@ def _extract_concept(species, units=None, model_id=None): ) if not old_annotation_string: - logger.debug(f"[{model_id} species:{species_name}] had no annotations") + logger.debug(f"[{model_id} species:{external_name}] had no annotations") concept = Concept( - name=species_name, - display_name=display_name, + name=external_name, + display_name=local_qual_name_reference, identifiers={}, context={}, units=units, @@ -344,6 +346,7 @@ def _extract_concept(species, units=None, model_id=None): # remove URNs, meta-prefixes and extract only prefixes and identifiers in tuple format # for descriptions and encodings strings for a qualitative species for description_string in description_strings_list: + # remove url quoting description_string = unquote(description_string) # for resources in the format of urn:{metaprefix}:hgnc.symbol:{identifier} @@ -408,15 +411,11 @@ def _extract_concept(species, units=None, model_id=None): ) in identifiers_curie_list: identifiers_curie_list.remove(("ncit", "C168970")) - # TODO: Currently multiple CURIEs are extracted with the same prefix but different - # identifier. For example, the list of identifier CURIEs may contain ncbigene:596 (BCL2) and - # ncbigene:4170 (MCL1). This seems to indicate that the all the list contains CURIEs for - # different agents involved in the transition. + # Multiple semantically identical CURIEs with different prefixes associated with a species. + # Additionally, some species involve multiple agents and thus contain CURIEs for all agents + # involved. Deterministically choose the CURIE to use as the identifier for the concept by + # sorting the keys of the identifiers dictionary (prefix) alphabetically - # Multiple CURIEs associated with a single concept. These concepts have different prefixes - # but semantically map to the same agent. They are stored in the all_identifiers dictionary - # deterministically choose the CURIE to use as the identifier by sorting the keys of the - # identifiers dictionary (prefix) alphabetically all_identifiers = dict(sorted(dict(identifiers_curie_list).items())) if all_identifiers: @@ -440,8 +439,8 @@ def _extract_concept(species, units=None, model_id=None): context[f'property{"" if idx == 0 else idx}'] = ":".join(prop) concept = Concept( - name=species_name, - display_name=display_name, + name=external_name, + display_name=local_qual_name_reference, identifiers=identifiers, context=context, units=units, From bc804c735c9d46dfb288193dde741e7ecb1a20eb Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 16 Apr 2024 15:25:12 -0400 Subject: [PATCH 17/44] Add smoke tests for ingesting series of sbml qual models --- tests/test_sbml_qual.py | 108 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 108 insertions(+) create mode 100644 tests/test_sbml_qual.py diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py new file mode 100644 index 000000000..89faf5b29 --- /dev/null +++ b/tests/test_sbml_qual.py @@ -0,0 +1,108 @@ +import requests + +from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string + +apoptosis_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Apoptosis_stable.sbml?ref_type=heads" +) + +coagulation_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Coagulation-pathway_stable.sbml?ref_type=heads" +) + +stress_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ER_Stress_stable.sbml?ref_type=heads" +) + +etc_stable_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ETC_stable.sbml?ref_type=heads" +) + +e_protein_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/E_protein_stable.sbml?ref_type=heads" +) + +hmox1_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/HMOX1_Pathway_stable.sbml?ref_type=heads" +) + +ifn_lambda_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/IFN-lambda_stable.sbml?ref_type=heads" +) + +interferon_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Interferon1_stable.sbml?ref_type=heads" +) + +jnk_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/JNK_pathway_stable.sbml?ref_type=heads" +) +kyu_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Kynurenine_pathway_stable.sbml?ref_type=heads" +) +nlrp3_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/NLRP3_Activation_stable.sbml?ref_type=heads" +) +nsp_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp14_stable.sbml?ref_type=heads" +) +nsp4_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp4_Nsp6_stable.sbml?ref_type=heads" +) +nsp9_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp9_protein_stable.sbml?ref_type=heads" +) +orf10_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf10_Cul2_pathway_stable.sbml?ref_type=heads" +) +orf3a_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads" +) +pamp_signal_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/PAMP_signaling_stable.sbml?ref_type=heads" +) +pyrimidine_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Pyrimidine_deprivation_stable.sbml?ref_type=heads" +) +rtc_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/RTC-and-transcription_stable.sbml?ref_type=heads" +) +renin_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Renin_angiotensin_stable.sbml?ref_type=heads" +) +tgfb_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/TGFB_pathway_stable.sbml?ref_type=heads" +) +virus_file = requests.get( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Virus_replication_cycle_stable.sbml?ref_type=heads" +) + +file_list = [ + apoptosis_file, + stress_file, + coagulation_file, + etc_stable_file, + e_protein_file, + hmox1_file, + ifn_lambda_file, + jnk_file, + kyu_file, + nlrp3_file, + nsp_file, + nsp4_file, + nsp9_file, + orf10_file, + orf3a_file, + pamp_signal_file, + pyrimidine_file, + rtc_file, + renin_file, + tgfb_file, + virus_file, +] + + +def test_sbml_qual_string_ingestion(): + for file in file_list: + xml_string = file.text + tm = template_model_from_sbml_qual_string(xml_string) From 65ad5cf8ab31cc4da85192713594aa805bd9267f Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 17 Apr 2024 13:20:58 -0400 Subject: [PATCH 18/44] Add smoke test for ingesting qual models from the biomodels website and refer to species id rather than the name field --- mira/sources/sbml/qual.py | 20 ++++++++++---------- tests/test_sbml_qual.py | 10 +++++++++- 2 files changed, 19 insertions(+), 11 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index a08848277..85e9fe6d2 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -245,7 +245,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: initials = {} for qual_species in self.qual_model_plugin.qualitative_species: - initials[qual_species.name] = Initial( + initials[qual_species.id] = Initial( concept=concepts[qual_species.id], expression=qual_species.level, ) @@ -262,7 +262,7 @@ def _extract_concepts(self) -> Mapping[str, Concept]: concept = _extract_concept( species, model_id=self.model_id, units=units ) - concepts[species.getId()] = concept + concepts[species.id] = concept return concepts def get_object_units(self, object): @@ -278,15 +278,15 @@ def get_object_units(self, object): def _extract_concept(species, units=None, model_id=None): # retrieve local name for species that is only used a reference in the sbml qual model - local_qual_name_reference = species.getId() + local_qual_name_reference = species.id # retrieve name of the species that can be used for look up in external resources - external_name = species.getName() + external_name = species.name if (model_id, external_name) in grounding_map: mapped_ids, mapped_context = grounding_map[(model_id, external_name)] concept = Concept( - name=external_name, - display_name=local_qual_name_reference, + name=local_qual_name_reference, + display_name=external_name, identifiers=copy.deepcopy(mapped_ids), context=copy.deepcopy(mapped_context), units=units, @@ -312,8 +312,8 @@ def _extract_concept(species, units=None, model_id=None): if not old_annotation_string: logger.debug(f"[{model_id} species:{external_name}] had no annotations") concept = Concept( - name=external_name, - display_name=local_qual_name_reference, + name=local_qual_name_reference, + display_name=external_name, identifiers={}, context={}, units=units, @@ -439,8 +439,8 @@ def _extract_concept(species, units=None, model_id=None): context[f'property{"" if idx == 0 else idx}'] = ":".join(prop) concept = Concept( - name=external_name, - display_name=local_qual_name_reference, + name=local_qual_name_reference, + display_name=external_name, identifiers=identifiers, context=context, units=units, diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index 89faf5b29..bbbb6a873 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -1,6 +1,7 @@ import requests from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string +from mira.sources.biomodels import get_sbml_model apoptosis_file = requests.get( "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Apoptosis_stable.sbml?ref_type=heads" @@ -102,7 +103,14 @@ ] -def test_sbml_qual_string_ingestion(): +def test_qual_models_from_example_repo(): for file in file_list: xml_string = file.text tm = template_model_from_sbml_qual_string(xml_string) + + +def test_qual_models_from_biomodels(): + model_ids = ["BIOMD0000000562", "BIOMD0000000592", "BIOMD0000000593"] + for model_id in model_ids: + model_text = get_sbml_model(model_id) + tm = template_model_from_sbml_qual_string(model_text) From 57827a3266864ae12d047e009bfa234455480aaa Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 17 Apr 2024 13:50:55 -0400 Subject: [PATCH 19/44] Extract annotations and model id --- mira/sources/sbml/qual.py | 120 +++++++++++++++++++++++++++++++++----- 1 file changed, 104 insertions(+), 16 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 85e9fe6d2..c5dd3871f 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -4,6 +4,7 @@ import re from typing import List, Mapping, Optional from copy import deepcopy +from collections import defaultdict from urllib.parse import unquote from mira.metamodel import * @@ -76,22 +77,18 @@ class SbmlQualProcessor: def __init__( self, sbml_model, qual_model_plugin, model_id=None, reporter_ids=None ): + # unit_definitions,parameters, and compartment attributes are empty for an sbml_model that + # comes from a qual plugin + self.qual_model_plugin = qual_model_plugin self.sbml_model = sbml_model self.model_id = model_id self.reporter_ids = reporter_ids - # unit_definitions is empty for sbml_model - self.units = get_units(self.sbml_model.unit_definitions) - def extract_model(self): if self.model_id is None: - self.model_id = get_model_id( - self.sbml_model, self.qual_model_plugin - ) - model_annots = get_model_annotations( - self.sbml_model, self.qual_model_plugin - ) + self.model_id = get_model_id(self.sbml_model) + model_annots = get_model_annotations(self.sbml_model) reporter_ids = set(self.reporter_ids or []) concepts = self._extract_concepts() @@ -449,22 +446,113 @@ def _extract_concept(species, units=None, model_id=None): return concept -# qual_model doesn't have any attribute or method to retrieve annotation. sbml_model annotation -# is an empty string -def get_model_annotations(sbml_model, qual_model): +def get_model_annotations(sbml_model): """Get the model annotations from the SBML qual model.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None + et = etree.fromstring(ann_xml) + annot_structure = { + "publications": "bqmodel:isDescribedBy", + "diseases": "bqbiol:is", + "taxa": "bqbiol:hasTaxon", + "model_type": "bqbiol:hasProperty", + "pathway": "bqbiol:isVersionOf", # points to pathways + # bqbiol:isPartOf used to point to pathways + # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway + "homolog_to": "bqbiol:isHomologTo", + "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel + "has_part": "bqbiol:hasPart", # points to pathways + } + annotations = defaultdict(list) + for key, path in annot_structure.items(): + full_path = f"rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li" + tags = et.findall(full_path, namespaces=PREFIX_MAP) + if not tags: + continue + for tag in tags: + uri = tag.attrib.get(RESOURCE_KEY) + if not uri: + continue + curie = converter.uri_to_curie(uri) + if not curie: + continue + annotations[key].append(curie) + + model_id = get_model_id(sbml_model) + if model_id and model_id.startswith("BIOMD"): + license = "CC0" + else: + license = None + + # TODO smarter split up taxon into pathogens and host organisms + hosts = [] + pathogens = [] + for curie in annotations.get("taxa", []): + if curie == "ncbitaxon:9606": + hosts.append(curie) + else: + pathogens.append(curie) + + model_types = [] + diseases = [] + logged_curie = set() + for curie in annotations.get("model_type", []): + if curie.startswith("mamo:"): + model_types.append(curie) + elif any( + curie.startswith(f"{disease_prefix}:") + for disease_prefix in ["mondo", "doid", "efo"] + ) or _curie_is_ncit_disease(curie): + diseases.append(bioregistry.normalize_curie(curie)) + elif curie not in logged_curie: + logged_curie.add(curie) + logger.debug(f"unhandled model_type: {curie}") + + return Annotations( + name=sbml_model.getModel().getName(), + description=None, # TODO + license=license, + authors=[], # TODO, + references=annotations.get("publications", []), + # no time_scale, time_start, time_end, locations from biomodels + hosts=hosts, + pathogens=pathogens, + diseases=diseases, + model_types=model_types, + ) -# qual_model doesn't have any attribute or method to retrieve annotation. sbml_model annotation -# is an empty string -def get_model_id(sbml_model, qual_model): - """Get the model ID from the SBML qual model annotation.""" +def get_model_id(sbml_model): + """Get the model ID from the SBML model annotation.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None + et = etree.fromstring(ann_xml) + id_tags = et.findall( + "rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li", + namespaces=PREFIX_MAP, + ) + for id_tag in id_tags: + uri = id_tag.attrib.get(RESOURCE_KEY) + if uri: + prefix, identifier = converter.parse_uri(uri) + if prefix == "biomodels.db" and identifier.startswith("BIOMD"): + return identifier + return None + + +def _curie_is_ncit_disease(curie: str) -> bool: + prefix, identifier = bioregistry.parse_curie(curie) + if prefix != "ncit": + return False + try: + import pyobo + except ImportError: + return False + else: + # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") + return False def get_units(unit_definitions): From 502b63b55c801f5c6d45ca91efebfaf00e9678a1 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Thu, 18 Apr 2024 13:30:55 -0400 Subject: [PATCH 20/44] Add updated comments --- mira/sources/sbml/qual.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index c5dd3871f..d38ab40e5 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -105,7 +105,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # parameters and compartment attributes for sbml_model are empty, they don't exist for # the qual_model_plugin - # each input to a transition can have a negative or positive sign + # each input to a transition can have a negative or positive sign or no sign # qual:sign = positive in source file indicates it controls the production of something # qual:sign = negative in source file indicates it controls the degradation of something # if both positive and negative exists, it is production process, with a list of @@ -128,9 +128,8 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: for qual_species in transition.getListOfOutputs() ] - # negative sign is 0, positive sign is 1 for inputs only + # positive sign is 0, negative sign is 1 for inputs only # outputs do not have a sign - # inputs will always be 0 or 1 positive_controller_names = [ qual_species.qualitative_species for qual_species in transition.getListOfInputs() From b54aecbb76b097341eb295af78d5d04aa2a60a04 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 09:43:31 -0400 Subject: [PATCH 21/44] Default to positive input if no sign is given --- mira/sources/sbml/qual.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index d38ab40e5..85b24cdcc 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -133,7 +133,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: positive_controller_names = [ qual_species.qualitative_species for qual_species in transition.getListOfInputs() - if qual_species.getSign() == 0 + if qual_species.getSign() != 1 ] negative_controller_names = [ From 2083a4f21f15580cb921dc6efddff9d2580c2170 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 09:48:03 -0400 Subject: [PATCH 22/44] Update tests for sbml qual module for models from example repo --- tests/test_sbml_qual.py | 126 +++++++++------------------------------- 1 file changed, 27 insertions(+), 99 deletions(-) diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index bbbb6a873..1cb16261e 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -3,109 +3,37 @@ from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string from mira.sources.biomodels import get_sbml_model -apoptosis_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Apoptosis_stable.sbml?ref_type=heads" -) - -coagulation_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Coagulation-pathway_stable.sbml?ref_type=heads" -) - -stress_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ER_Stress_stable.sbml?ref_type=heads" -) - -etc_stable_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/ETC_stable.sbml?ref_type=heads" -) - -e_protein_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/E_protein_stable.sbml?ref_type=heads" -) - -hmox1_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/HMOX1_Pathway_stable.sbml?ref_type=heads" -) - -ifn_lambda_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/IFN-lambda_stable.sbml?ref_type=heads" -) - -interferon_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Interferon1_stable.sbml?ref_type=heads" -) - -jnk_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/JNK_pathway_stable.sbml?ref_type=heads" -) -kyu_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Kynurenine_pathway_stable.sbml?ref_type=heads" -) -nlrp3_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/NLRP3_Activation_stable.sbml?ref_type=heads" -) -nsp_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp14_stable.sbml?ref_type=heads" -) -nsp4_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp4_Nsp6_stable.sbml?ref_type=heads" -) -nsp9_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Nsp9_protein_stable.sbml?ref_type=heads" -) -orf10_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf10_Cul2_pathway_stable.sbml?ref_type=heads" -) -orf3a_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads" -) -pamp_signal_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/PAMP_signaling_stable.sbml?ref_type=heads" -) -pyrimidine_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Pyrimidine_deprivation_stable.sbml?ref_type=heads" -) -rtc_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/RTC-and-transcription_stable.sbml?ref_type=heads" -) -renin_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Renin_angiotensin_stable.sbml?ref_type=heads" -) -tgfb_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/TGFB_pathway_stable.sbml?ref_type=heads" -) -virus_file = requests.get( - "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Virus_replication_cycle_stable.sbml?ref_type=heads" -) - -file_list = [ - apoptosis_file, - stress_file, - coagulation_file, - etc_stable_file, - e_protein_file, - hmox1_file, - ifn_lambda_file, - jnk_file, - kyu_file, - nlrp3_file, - nsp_file, - nsp4_file, - nsp9_file, - orf10_file, - orf3a_file, - pamp_signal_file, - pyrimidine_file, - rtc_file, - renin_file, - tgfb_file, - virus_file, +models = [ + "Apoptosis", + "Coagulation-pathway", + "ER_Stress", + "ETC", + "E_protein", + "HMOX1_Pathway", + "IFN-lambda", + "Interferon1", + "JNK_pathway", + "Kynurenine_pathway", + "NLRP3_Activation", + "Nsp14", + "Nsp4_Nsp6", + "Nsp9_protein", + "Orf10_Cul2_pathway", + "Orf3a", + "PAMP_signaling", + "Pyrimidine_deprivation", + "RTC-and-transcription", + "Renin_angiotensin", + "TGFB_pathway", + "Virus_replication_cycle", ] +BASE_URL = "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml" def test_qual_models_from_example_repo(): - for file in file_list: - xml_string = file.text + for model in models: + url = f"{BASE_URL}/{model}_stable.sbml" + xml_string = requests.get(url).text tm = template_model_from_sbml_qual_string(xml_string) From 0b2f8ab70381f0959bb892fa60d4467ba6d54c3f Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 13:24:23 -0400 Subject: [PATCH 23/44] Create util file for shared code between sbml and sbml qual processors --- mira/sources/sbml/processor.py | 734 ++++++++++++--------------------- mira/sources/sbml/qual.py | 325 +-------------- mira/sources/sbml/utils.py | 311 ++++++++++++++ 3 files changed, 584 insertions(+), 786 deletions(-) create mode 100644 mira/sources/sbml/utils.py diff --git a/mira/sources/sbml/processor.py b/mira/sources/sbml/processor.py index 04dd9ff00..f07ec935b 100644 --- a/mira/sources/sbml/processor.py +++ b/mira/sources/sbml/processor.py @@ -6,51 +6,17 @@ """ import copy -import csv -from collections import defaultdict -from copy import deepcopy -import logging import math -from typing import Dict, Iterable, List, Mapping, Optional, Tuple - -import bioregistry -import libsbml -import sympy -from lxml import etree -from tqdm import tqdm - -from mira.metamodel import * -from mira.resources import get_resource_file - - -class TqdmLoggingHandler(logging.Handler): - def __init__(self, level=logging.NOTSET): - super().__init__(level) - - def emit(self, record): - try: - msg = self.format(record) - tqdm.write(msg) - self.flush() - except Exception: - self.handleError(record) +from typing import Dict, Iterable, List, Mapping, Tuple +from mira.sources.sbml.utils import * logger = logging.getLogger(__name__) logger.addHandler(TqdmLoggingHandler()) +grounding_map = get_grounding_map() +converter = Converter() + -PREFIX_MAP = { - "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", - "dcterms": "http://purl.org/dc/terms/", - "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", - "vCard4": "http://www.w3.org/2006/vcard/ns#", - "bqbiol": "http://biomodels.net/biology-qualifiers/", - "bqmodel": "http://biomodels.net/model-qualifiers/", - "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", - "copasi": "http://www.copasi.org/static/sbml", - "jd": "http://www.sys-bio.org/sbml", -} -RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" #: This XPath query gets annotations on species for their structured #: identifiers, typically given as MIRIAM URIs or URNs IDENTIFIERS_XPATH = f"rdf:RDF/rdf:Description/bqbiol:is/rdf:Bag/rdf:li" @@ -61,7 +27,9 @@ def emit(self, record): #: This is an alternative XPath for groundings that use the isVersionOf #: relation and are thus less specific than the one above but can be used #: as fallback -IDENTIFIERS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" +IDENTIFIERS_VERSION_XPATH = ( + f"rdf:RDF/rdf:Description/bqbiol:isVersionOf/rdf:Bag/rdf:li" +) #: This XPath query gets annotations on species about their properties, #: which typically help ad-hoc create subclasses that are more specific PROPERTIES_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" @@ -70,28 +38,6 @@ def emit(self, record): IS_VERSION_XPATH = f"rdf:RDF/rdf:Description/bqbiol:hasProperty/rdf:Bag/rdf:li" -class Converter: - """Wrapper around a curies converter with lazy loading.""" - - def __init__(self): - self.converter = None - - def parse_uri(self, uri): - """Parse a URI into a prefix/identifier pair.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.parse_uri(uri) - - def uri_to_curie(self, uri: str) -> Optional[str]: - """Turn a URI into a CURIE.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.compress(uri) - - -converter = Converter() - - class SbmlProcessor: """Traverse an SBML document generated by libSBML and extract a MIRA Template model.""" @@ -104,15 +50,19 @@ def __init__(self, sbml_model, model_id=None, reporter_ids=None): def extract_model(self): if self.model_id is None: - self.model_id = get_model_id(self.sbml_model) - model_annots = get_model_annotations(self.sbml_model) + self.model_id = get_model_id(self.sbml_model, converter=converter) + model_annots = get_model_annotations( + self.sbml_model, converter=converter, logger=logger + ) reporter_ids = set(self.reporter_ids or []) concepts = self._extract_concepts() def _lookup_concepts_filtered(species_ids) -> List[Concept]: return [ - concepts[species_id] for species_id in species_ids - if species_id not in reporter_ids and 'cumulative' not in species_id + concepts[species_id] + for species_id in species_ids + if species_id not in reporter_ids + and "cumulative" not in species_id ] # Iterate thorugh all reactions and piecewise convert to templates @@ -124,31 +74,36 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: all_parameters = { parameter.id: { - 'value': parameter.value, - 'description': parameter.name, - 'units': self.get_object_units(parameter) + "value": parameter.value, + "description": parameter.name, + "units": self.get_object_units(parameter), } for parameter in self.sbml_model.parameters } - parameter_symbols = \ - {parameter.id: sympy.Symbol(parameter.id) - for parameter in self.sbml_model.parameters} - compartment_symbols = {compartment.id: sympy.Symbol(compartment.id) - for compartment in self.sbml_model.compartments} + parameter_symbols = { + parameter.id: sympy.Symbol(parameter.id) + for parameter in self.sbml_model.parameters + } + compartment_symbols = { + compartment.id: sympy.Symbol(compartment.id) + for compartment in self.sbml_model.compartments + } # Add compartment volumes as parameters for compartment in self.sbml_model.compartments: - all_parameters[compartment.id] = {'value': compartment.volume, - 'description': compartment.name, - 'units': self.get_object_units(compartment)} + all_parameters[compartment.id] = { + "value": compartment.volume, + "description": compartment.name, + "units": self.get_object_units(compartment), + } # Handle custom function definitions in the model function_lambdas = {} for fun_def in self.sbml_model.function_definitions: - args = [fun_def.getArgument(i).getName() - for i in range(fun_def.getNumArguments())] - arg_symbols = { - arg: sympy.Symbol(arg) for arg in args - } + args = [ + fun_def.getArgument(i).getName() + for i in range(fun_def.getNumArguments()) + ] + arg_symbols = {arg: sympy.Symbol(arg) for arg in args} signature = tuple(arg_symbols.values()) formula_str = get_formula_str(fun_def.getBody()) @@ -161,18 +116,28 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # In formulas, the species ID appears instead of the species name # and so we have to map these to symbols corresponding to the species name species_id_map = { - species.id: (sympy.Symbol(species.name) - if (species.name and '(' not in species.name - and '-' not in species.name - and '+' not in species.name) - else sympy.Symbol(species.id)) + species.id: ( + sympy.Symbol(species.name) + if ( + species.name + and "(" not in species.name + and "-" not in species.name + and "+" not in species.name + ) + else sympy.Symbol(species.id) + ) for species in self.sbml_model.species } - all_locals = {k: v for k, v in (list(parameter_symbols.items()) + - list(compartment_symbols.items()) + - list(function_lambdas.items()) + - list(species_id_map.items()))} + all_locals = { + k: v + for k, v in ( + list(parameter_symbols.items()) + + list(compartment_symbols.items()) + + list(function_lambdas.items()) + + list(species_id_map.items()) + ) + } # Handle custom assignment rules in the model assignment_rules = {} @@ -184,8 +149,12 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: all_implicit_modifiers = set() implicit_modifiers = None for reaction in self.sbml_model.reactions: - modifier_species = [species.species for species in reaction.modifiers] - reactant_species = [species.species for species in reaction.reactants] + modifier_species = [ + species.species for species in reaction.modifiers + ] + reactant_species = [ + species.species for species in reaction.reactants + ] product_species = [species.species for species in reaction.products] # In some models, modifiers are defined as both input and output @@ -204,13 +173,14 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # Some rate laws define parameters locally and so we need to # extract them and add them to the global parameter list for parameter in rate_law.parameters: - all_parameters[parameter.id] = {'value': parameter.value, - 'description': parameter.name if parameter.name else None, - 'units': self.get_object_units(parameter)} + all_parameters[parameter.id] = { + "value": parameter.value, + "description": parameter.name if parameter.name else None, + "units": self.get_object_units(parameter), + } parameter_symbols[parameter.id] = sympy.Symbol(parameter.id) - rate_expr = safe_parse_expr(rate_law.formula, - local_dict=all_locals) + rate_expr = safe_parse_expr(rate_law.formula, local_dict=all_locals) # At this point we need to make sure we substitute the assignments rate_expr = rate_expr.subs(assignment_rules) @@ -221,21 +191,26 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # and explicit 1.0 will be carried around in the rate expression comp_one = False if comp_symbol in rate_expr.free_symbols: - if rate_expr not in rate_expr.diff(comp_symbol).free_symbols: - if all_parameters[comp]['value'] == 1.0: + if ( + rate_expr + not in rate_expr.diff(comp_symbol).free_symbols + ): + if all_parameters[comp]["value"] == 1.0: comp_one = True rate_expr /= comp_symbol if not comp_one: - rate_expr = rate_expr.subs(comp_symbol, - all_parameters[comp]['value']) + rate_expr = rate_expr.subs( + comp_symbol, all_parameters[comp]["value"] + ) rate_law_variables = variables_from_sympy_expr(rate_expr) # Implicit modifiers appear in the rate law but are not reactants and # aren't listed explicitly as modifiers. They have to be proper species # though (since the rate law also contains parameters). - implicit_modifiers = ((set(rate_law_variables) & all_species) - - (set(reactant_species) | set(modifier_species))) + implicit_modifiers = (set(rate_law_variables) & all_species) - ( + set(reactant_species) | set(modifier_species) + ) # We extend modifiers with implicit ones modifier_species += sorted(implicit_modifiers) all_implicit_modifiers |= implicit_modifiers @@ -286,29 +261,43 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: ) ) elif not reactants and not products: - logger.debug(f"[{self.model_id} reaction:{reaction.id}] missing reactants and products") + logger.debug( + f"[{self.model_id} reaction:{reaction.id}] missing reactants and products" + ) continue # We either have a production or a degradation elif bool(products) != bool(reactants): - kwargs = {'rate_law': rate_expr} + kwargs = {"rate_law": rate_expr} if not modifiers: contr = {} elif len(modifiers) == 1: - contr = {'controller': modifiers[0]} + contr = {"controller": modifiers[0]} else: - contr = {'controllers': modifiers} + contr = {"controllers": modifiers} kwargs.update(contr) if products: - cls = NaturalProduction if not modifiers else \ - (ControlledProduction if len(modifiers) == 1 - else GroupedControlledProduction) - kwargs.update({'outcome': products[0]}) + cls = ( + NaturalProduction + if not modifiers + else ( + ControlledProduction + if len(modifiers) == 1 + else GroupedControlledProduction + ) + ) + kwargs.update({"outcome": products[0]}) else: - cls = NaturalDegradation if not modifiers else \ - (ControlledDegradation if len(modifiers) == 1 - else GroupedControlledDegradation) - kwargs.update({'subject': reactants[0]}) + cls = ( + NaturalDegradation + if not modifiers + else ( + ControlledDegradation + if len(modifiers) == 1 + else GroupedControlledDegradation + ) + ) + kwargs.update({"subject": reactants[0]}) templates.append(cls(**kwargs)) else: logger.debug( @@ -327,21 +316,31 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: # initial concentration is of type float initials[species.name] = Initial( concept=concepts[species.getId()], - expression=SympyExprStr(sympy.Float(species.initial_concentration)), + expression=SympyExprStr( + sympy.Float(species.initial_concentration) + ), ) - param_objs = {k: Parameter(name=k, value=v['value'], - description=v['description'], - units=v['units']) - for k, v in all_parameters.items()} + param_objs = { + k: Parameter( + name=k, + value=v["value"], + description=v["description"], + units=v["units"], + ) + for k, v in all_parameters.items() + } - template_model = TemplateModel(templates=templates, - parameters=param_objs, - initials=initials, - annotations=model_annots) + template_model = TemplateModel( + templates=templates, + parameters=param_objs, + initials=initials, + annotations=model_annots, + ) # Replace constant concepts by their initial value - template_model = replace_constant_concepts(template_model, - implicit_modifiers) + template_model = replace_constant_concepts( + template_model, implicit_modifiers + ) return template_model def _extract_concepts(self) -> Mapping[str, Concept]: @@ -351,15 +350,16 @@ def _extract_concepts(self) -> Mapping[str, Concept]: for species in self.sbml_model.getListOfSpecies(): # Extract the units for the species units = self.get_object_units(species) - concept = _extract_concept(species, model_id=self.model_id, - units=units) + concept = _extract_concept( + species, model_id=self.model_id, units=units + ) concepts[species.getId()] = concept return concepts def get_object_units(self, object): if object.units: - if object.units == 'dimensionless': + if object.units == "dimensionless": return Unit(expression=sympy.Integer(1)) else: return Unit(expression=self.units[object.units]) @@ -367,168 +367,6 @@ def get_object_units(self, object): return None -def get_units(unit_definitions): - """Return units from a list of unit definition blocks.""" - units = {} - for unit_def in unit_definitions: - units[unit_def.id] = process_unit_definition(unit_def) - return units - - -unit_symbol_mappings = { - 'item': 'person', - 'metre': 'meter', - 'litre': 'liter', -} - -unit_expression_mappings = { - 86400.0 * sympy.Symbol('second'): sympy.Symbol('day'), - 1 / (86400.0 * sympy.Symbol('second')): 1 / sympy.Symbol('day'), - 1 / (86400.0 * sympy.Symbol('second') * sympy.Symbol('person')): - 1 / (sympy.Symbol('day') * sympy.Symbol('person')), - 31536000.0 * sympy.Symbol('second'): sympy.Symbol('year'), - 1 / (31536000.0 * sympy.Symbol('second')): 1 / sympy.Symbol('year'), - 1 / (31536000.0 * sympy.Symbol('second') * sympy.Symbol('person')): - 1 / (sympy.Symbol('year') * sympy.Symbol('person')), -} - - -def process_unit_definition(unit_definition): - """Process a unit definition block to extract an expression.""" - full_unit_expr = sympy.Integer(1) - for unit in unit_definition.units: - unit_symbol_str = SBML_UNITS[unit.kind] - # We assume person instead of item here - if unit_symbol_str in unit_symbol_mappings: - unit_symbol_str = unit_symbol_mappings[unit_symbol_str] - unit_symbol = sympy.Symbol(unit_symbol_str) - # We do this to avoid the spurious factors in the expression - if unit.multiplier != 1: - unit_symbol *= unit.multiplier - if unit.exponent != 1: - unit_symbol **= unit.exponent - if unit.scale != 0: - unit_symbol *= 10 ** unit.scale - full_unit_expr *= unit_symbol - # We apply some mappings for canonical units we want to change - # We use equals here since == in sympy is structural equality - for k, v in unit_expression_mappings.items(): - if full_unit_expr.equals(k): - full_unit_expr = v - return full_unit_expr - - -def get_model_annotations(sbml_model) -> Annotations: - """Get the model annotations from the SBML model.""" - ann_xml = sbml_model.getAnnotationString() - if not ann_xml: - return None - et = etree.fromstring(ann_xml) - # Publication: bqmodel:isDescribedBy - # Disease: bqbiol:is - # Taxa: bqbiol:hasTaxon - # Model type: bqbiol:hasProperty - annot_structure = { - 'publications': 'bqmodel:isDescribedBy', - 'diseases': 'bqbiol:is', - 'taxa': 'bqbiol:hasTaxon', - 'model_type': 'bqbiol:hasProperty', - 'pathway': 'bqbiol:isVersionOf', # points to pathways - # bqbiol:isPartOf used to point to pathways - # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway - 'homolog_to': "bqbiol:isHomologTo", - "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel - 'has_part': "bqbiol:hasPart", # points to pathways - } - annotations = defaultdict(list) - for key, path in annot_structure.items(): - full_path = f'rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li' - tags = et.findall(full_path, namespaces=PREFIX_MAP) - if not tags: - continue - for tag in tags: - uri = tag.attrib.get(RESOURCE_KEY) - if not uri: - continue - curie = converter.uri_to_curie(uri) - if not curie: - continue - annotations[key].append(curie) - - model_id = get_model_id(sbml_model) - if model_id and model_id.startswith("BIOMD"): - license = "CC0" - else: - license = None - - # TODO smarter split up taxon into pathogens and host organisms - hosts = [] - pathogens = [] - for curie in annotations.get("taxa", []): - if curie == "ncbitaxon:9606": - hosts.append(curie) - else: - pathogens.append(curie) - - model_types = [] - diseases = [] - logged_curie = set() - for curie in annotations.get("model_type", []): - if curie.startswith("mamo:"): - model_types.append(curie) - elif any( - curie.startswith(f"{disease_prefix}:") - for disease_prefix in ["mondo", "doid", "efo"] - ) or _curie_is_ncit_disease(curie): - diseases.append(bioregistry.normalize_curie(curie)) - elif curie not in logged_curie: - logged_curie.add(curie) - logger.debug(f"unhandled model_type: {curie}") - - return Annotations( - name=sbml_model.getModel().getName(), - description=None, # TODO - license=license, - authors=[], # TODO, - references=annotations.get("publications", []), - # no time_scale, time_start, time_end, locations from biomodels - hosts=hosts, - pathogens=pathogens, - diseases=diseases, - model_types=model_types, - ) - - -def _curie_is_ncit_disease(curie: str) -> bool: - prefix, identifier = bioregistry.parse_curie(curie) - if prefix != "ncit": - return False - try: - import pyobo - except ImportError: - return False - else: - # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") - return False - - -def get_model_id(sbml_model): - """Get the model ID from the SBML model annotation.""" - ann_xml = sbml_model.getAnnotationString() - if not ann_xml: - return None - et = etree.fromstring(ann_xml) - id_tags = et.findall('rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li', - namespaces=PREFIX_MAP) - for id_tag in id_tags: - uri = id_tag.attrib.get(RESOURCE_KEY) - if uri: - prefix, identifier = converter.parse_uri(uri) - if prefix == 'biomodels.db' and identifier.startswith('BIOMD'): - return identifier - return None - - def find_constant_concepts(template_model: TemplateModel) -> Iterable[str]: # Find concepts that are unchanged, just appear as controllers or not at all all_concepts = set() @@ -536,9 +374,12 @@ def find_constant_concepts(template_model: TemplateModel) -> Iterable[str]: for template in template_model.templates: concepts_by_role = template.get_concepts_by_role() for role, concepts in concepts_by_role.items(): - names = {c.name for c in concepts} if \ - isinstance(concepts, list) else {concepts.name} - if role in {'subject', 'outcome'}: + names = ( + {c.name for c in concepts} + if isinstance(concepts, list) + else {concepts.name} + ) + if role in {"subject", "outcome"}: changing_concepts |= names all_concepts |= names non_changing_concepts = all_concepts - changing_concepts @@ -561,13 +402,14 @@ def replace_constant_concepts(template_model: TemplateModel, candidates=None): # Fixme, do we need more grounding (identifiers, concept) # for the concept here? # Get the units of the concept here - template_model.parameters[constant_concept] = \ - Parameter(name=constant_concept, value=float(initial_expression.args[0])) + template_model.parameters[constant_concept] = Parameter( + name=constant_concept, value=float(initial_expression.args[0]) + ) new_templates = [] for template in template_model.templates: - new_template = replace_controller_by_constant(template, - constant_concept, - initial_expression.args[0]) + new_template = replace_controller_by_constant( + template, constant_concept, initial_expression.args[0] + ) if new_template: new_templates.append(new_template) else: @@ -583,16 +425,22 @@ def replace_controller_by_constant(template, controller_name, value): subject=template.subject, outcome=template.outcome, ) - new_template.rate_law = template.rate_law.subs(controller_name, value) + new_template.rate_law = template.rate_law.subs( + controller_name, value + ) return new_template elif isinstance(template, GroupedControlledConversion): if len(template.controllers) > 2: new_template = GroupedControlledConversion( subject=template.subject, outcome=template.outcome, - controllers=[c for c in template.controllers if c.name != controller_name], + controllers=[ + c for c in template.controllers if c.name != controller_name + ], + ) + new_template.rate_law = template.rate_law.subs( + controller_name, value ) - new_template.rate_law = template.rate_law.subs(controller_name, value) return new_template else: # If there are only two controllers, we can replace the @@ -602,7 +450,9 @@ def replace_controller_by_constant(template, controller_name, value): outcome=template.outcome, controller=template.controllers[0], ) - new_template.rate_law = template.rate_law.subs(controller_name, value) + new_template.rate_law = template.rate_law.subs( + controller_name, value + ) return new_template # TODO: potentially handle other template types return @@ -621,30 +471,32 @@ def get_formula_str(ast_node): if not name: op = ast_node.getOperatorName() if op: - if op == 'times': - op_str = '*' - elif op == 'plus': - op_str = '+' - elif op == 'divide': - op_str = '/' - elif op == 'minus': - op_str = '-' + if op == "times": + op_str = "*" + elif op == "plus": + op_str = "+" + elif op == "divide": + op_str = "/" + elif op == "minus": + op_str = "-" else: - print('Unknown op: %s' % op) + print("Unknown op: %s" % op) assert False # Special case where we have a unary minus - if op == 'minus' and ast_node.isUMinus(): - return '-%s' % get_formula_str(ast_node.getChild(0)) + if op == "minus" and ast_node.isUMinus(): + return "-%s" % get_formula_str(ast_node.getChild(0)) # More general binary case - return '(%s %s %s)' % (get_formula_str(ast_node.getChild(0)), - op_str, - get_formula_str(ast_node.getChild(1))) + return "(%s %s %s)" % ( + get_formula_str(ast_node.getChild(0)), + op_str, + get_formula_str(ast_node.getChild(1)), + ) val = ast_node.getValue() if val is not None: return val # Exponential doesn't show up as an operator but rather a name - elif name in {'exp'}: - return '%s(%s)' % (name, get_formula_str(ast_node.getChild(0))) + elif name in {"exp"}: + return "%s(%s)" % (name, get_formula_str(ast_node.getChild(0))) else: return name @@ -689,7 +541,7 @@ def _extract_concept(species, units=None, model_id=None): species_id = species.getId() species_name = species.getName() display_name = species_name - if '(' in species_name: + if "(" in species_name: species_name = species_id # If we have curated a grounding for this species we return the concept @@ -701,11 +553,13 @@ def _extract_concept(species, units=None, model_id=None): display_name=display_name, identifiers=copy.deepcopy(mapped_ids), context=copy.deepcopy(mapped_context), - units=units + units=units, ) return concept else: - logger.debug(f"[{model_id} species:{species_id}] not found in grounding map") + logger.debug( + f"[{model_id} species:{species_id}] not found in grounding map" + ) # Otherwise we try to create a Concept with all its groundings and apply # various normalizations and clean up. @@ -715,50 +569,65 @@ def _extract_concept(species, units=None, model_id=None): annotation_string = species.getAnnotationString() if not annotation_string: logger.debug(f"[{model_id} species:{species_id}] had no annotations") - concept = Concept(name=species_name, display_name=display_name, - identifiers={}, context={}, units=units) + concept = Concept( + name=species_name, + display_name=display_name, + identifiers={}, + context={}, + units=units, + ) return concept annotation_tree = etree.fromstring(annotation_string) rdf_properties = [ converter.parse_uri(desc.attrib[RESOURCE_KEY]) - for desc in - annotation_tree.findall(PROPERTIES_XPATH, namespaces=PREFIX_MAP) + for desc in annotation_tree.findall( + PROPERTIES_XPATH, namespaces=PREFIX_MAP + ) ] # First we check identifiers with a specific relation representing # equivalence identifiers_list = [] - for element in annotation_tree.findall(IDENTIFIERS_XPATH, - namespaces=PREFIX_MAP): + for element in annotation_tree.findall( + IDENTIFIERS_XPATH, namespaces=PREFIX_MAP + ): curie = converter.parse_uri(element.attrib[RESOURCE_KEY]) identifiers_list.append(curie) context = {} - if ('ido', 'C101887') in identifiers_list: - identifiers_list.remove(('ido', 'C101887')) - identifiers_list.append(('ncit', 'C101887')) - if ('ncit', 'C171133') in identifiers_list: - identifiers_list.remove(('ncit', 'C171133')) + if ("ido", "C101887") in identifiers_list: + identifiers_list.remove(("ido", "C101887")) + identifiers_list.append(("ncit", "C101887")) + if ("ncit", "C171133") in identifiers_list: + identifiers_list.remove(("ncit", "C171133")) # Reclassify asymptomatic as a disease status - if ('ido', '0000569') in identifiers_list and \ - ('ido', '0000511') in identifiers_list: - identifiers_list.remove(('ido', '0000569')) - context['disease_status'] = 'ncit:C3833' + if ("ido", "0000569") in identifiers_list and ( + "ido", + "0000511", + ) in identifiers_list: + identifiers_list.remove(("ido", "0000569")) + context["disease_status"] = "ncit:C3833" # Exposed shouldn't be susceptible - if ('ido', '0000514') in identifiers_list and \ - ('ido', '0000597') in identifiers_list: - identifiers_list.remove(('ido', '0000514')) + if ("ido", "0000514") in identifiers_list and ( + "ido", + "0000597", + ) in identifiers_list: + identifiers_list.remove(("ido", "0000514")) # Break apoart hospitalized and ICU - if ('ncit', 'C25179') in identifiers_list and \ - ('ncit', 'C53511') in identifiers_list: - identifiers_list.remove(('ncit', 'C53511')) - context['disease_status'] = 'ncit:C53511' + if ("ncit", "C25179") in identifiers_list and ( + "ncit", + "C53511", + ) in identifiers_list: + identifiers_list.remove(("ncit", "C53511")) + context["disease_status"] = "ncit:C53511" # Remove redundant term for deceased due to disease progression - if ('ncit', 'C28554') in identifiers_list and \ - ('ncit', 'C168970') in identifiers_list: - identifiers_list.remove(('ncit', 'C168970')) + if ("ncit", "C28554") in identifiers_list and ( + "ncit", + "C168970", + ) in identifiers_list: + identifiers_list.remove(("ncit", "C168970")) identifiers = dict(identifiers_list) if len(identifiers) != len(identifiers_list): @@ -766,43 +635,47 @@ def _extract_concept(species, units=None, model_id=None): # We capture context here as a set of generic properties for idx, rdf_property in enumerate(sorted(rdf_properties)): - if rdf_property[0] == 'ncit' and rdf_property[1].startswith('000'): - prop = ('ido', rdf_property[1]) - elif rdf_property[0] == 'ido' and rdf_property[1].startswith('C'): - prop = ('ncit', rdf_property[1]) + if rdf_property[0] == "ncit" and rdf_property[1].startswith("000"): + prop = ("ido", rdf_property[1]) + elif rdf_property[0] == "ido" and rdf_property[1].startswith("C"): + prop = ("ncit", rdf_property[1]) else: prop = rdf_property context[f'property{"" if idx == 0 else idx}'] = ":".join(prop) # As a fallback, we also check if identifiers are available with # a less specific relation if not identifiers: - elements = sorted([ - converter.parse_uri(element.attrib[RESOURCE_KEY]) - for element in annotation_tree.findall(IDENTIFIERS_VERSION_XPATH, - namespaces=PREFIX_MAP) - ], reverse=True) + elements = sorted( + [ + converter.parse_uri(element.attrib[RESOURCE_KEY]) + for element in annotation_tree.findall( + IDENTIFIERS_VERSION_XPATH, namespaces=PREFIX_MAP + ) + ], + reverse=True, + ) # This is generic COVID-19 infection, generally not needed - if ('ncit', 'C171133') in elements: - elements.remove(('ncit', 'C171133')) + if ("ncit", "C171133") in elements: + elements.remove(("ncit", "C171133")) # Remap inconsistent groundings - if ('ido', '0000569') in elements: - elements.remove(('ido', '0000569')) - elements.append(('ido', '0000511')) - context['disease_status'] = 'ncit:C3833' - elif ('ido', '0000573') in elements: - elements.remove(('ido', '0000573')) - elements.append(('ido', '0000511')) - context['disease_status'] = 'ncit:C25269' + if ("ido", "0000569") in elements: + elements.remove(("ido", "0000569")) + elements.append(("ido", "0000511")) + context["disease_status"] = "ncit:C3833" + elif ("ido", "0000573") in elements: + elements.remove(("ido", "0000573")) + elements.append(("ido", "0000511")) + context["disease_status"] = "ncit:C25269" # Make transmissibility a context instead of identity - if ('ido', '0000463') in elements: - if ('ncit', 'C49508') in elements: - context['transmissibility'] = 'ncit:C49508' - elements.remove(('ido', '0000463')) - elements.remove(('ncit', 'C49508')) - elif ('ncit', 'C171549') in elements: - context['transmissibility'] = 'ncit:C171549' - elements.remove(('ido', '0000463')) - elements.remove(('ncit', 'C171549')) + if ("ido", "0000463") in elements: + if ("ncit", "C49508") in elements: + context["transmissibility"] = "ncit:C49508" + elements.remove(("ido", "0000463")) + elements.remove(("ncit", "C49508")) + elif ("ncit", "C171549") in elements: + context["transmissibility"] = "ncit:C171549" + elements.remove(("ido", "0000463")) + elements.remove(("ncit", "C171549")) identifiers = dict(elements) @@ -820,52 +693,31 @@ def _extract_concept(species, units=None, model_id=None): return concept -def grounding_normalize(concept): - # A common curation mistake in BioModels: mixing up IDO and NCIT identifiers - for k, v in deepcopy(concept.identifiers).items(): - if k == 'ncit' and v.startswith('000'): - concept.identifiers.pop(k) - concept.identifiers['ido'] = v - elif k == 'ido' and v.startswith('C'): - concept.identifiers.pop(k) - concept.identifiers['ncit'] = v - # Has property acquired immunity == immune population - if not concept.get_curie()[0] and \ - concept.context == {'property': 'ido:0000621'}: - concept.identifiers['ido'] = '0000592' - concept.context = {} - elif concept.get_curie() == ('ido', '0000514') and \ - concept.context == {'property': 'ido:0000468'}: - concept.context = {} - # Different ways of expression immune/recovered - elif concept.get_curie() == ('ncit', 'C171133') and \ - concept.context == {'property': 'ido:0000621'}: - concept.identifiers = {'ido': '0000592'} - concept.context = {} - # Different terms for dead/deceased - elif concept.get_curie() == ('ncit', 'C168970'): - concept.identifiers = {'ncit': 'C28554'} - return concept - - -def _get_copasi_identifiers(annotation_tree: etree, xpath: str) -> Dict[str, str]: +def _get_copasi_identifiers( + annotation_tree: etree, xpath: str +) -> Dict[str, str]: # Use COPASI_IS or COPASI_IS_VERSION_OF for xpath depending on use case return dict( - tuple(el.attrib[RESOURCE_KEY].split(':')[-2:]) for el in - annotation_tree.xpath(xpath, namespaces=PREFIX_MAP) + tuple(el.attrib[RESOURCE_KEY].split(":")[-2:]) + for el in annotation_tree.xpath(xpath, namespaces=PREFIX_MAP) ) def _get_copasi_props(annotation_tree: etree) -> List[Tuple[str, str]]: return [ - tuple(el.attrib[RESOURCE_KEY].split(':')[-2:]) for el in - annotation_tree.xpath(COPASI_HAS_PROPERTY, namespaces=PREFIX_MAP) + tuple(el.attrib[RESOURCE_KEY].split(":")[-2:]) + for el in annotation_tree.xpath( + COPASI_HAS_PROPERTY, namespaces=PREFIX_MAP + ) ] -def _extract_all_copasi_attrib(species_annot_etree: etree) -> List[Tuple[str, str]]: - descr_tags = species_annot_etree.xpath(COPASI_DESCR_XPATH, - namespaces=PREFIX_MAP) +def _extract_all_copasi_attrib( + species_annot_etree: etree, +) -> List[Tuple[str, str]]: + descr_tags = species_annot_etree.xpath( + COPASI_DESCR_XPATH, namespaces=PREFIX_MAP + ) resources = [] for descr_tag in descr_tags: for element in descr_tag.iter(): @@ -885,61 +737,3 @@ def _extract_all_copasi_attrib(species_annot_etree: etree) -> List[Tuple[str, st assert value != "{}" resources.append((key, value)) return resources - - -def _get_grounding_map(): - def parse_identifier_grounding(grounding_str): - # Example: ido:0000511/infected population from which we want to get - # {'ido': '0000511'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split('/')[0].split(':')) - for grounding in grounding_str.split('|') - ) - - def parse_context_grounding(grounding_str): - # Example: disease_severity=ncit:C25269/Symptomatic| - # diagnosis=ncit:C113725/Undiagnosed - # from which we want to get {'disease_severity': 'ncit:C25269', - # 'diagnosis': 'ncit:C113725'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split('/')[0].split('=')) - for grounding in grounding_str.split('|') - ) - - fname = get_resource_file('mapped_biomodels_groundings.csv') - mappings = {} - with open(fname, 'r') as fh: - reader = csv.reader(fh) - next(reader) - for name, ids, context, model, mapped_ids, mapped_context in reader: - mappings[(model, name)] = ( - parse_identifier_grounding(mapped_ids), - parse_context_grounding(mapped_context) - ) - - return mappings - - -grounding_map = _get_grounding_map() - - -def get_sbml_units(): - """Build up a mapping of SBML unit kinds to their names. - - This is necessary because units are given as numbers. - """ - module_contents = dir(libsbml) - unit_kinds = {var: var.split('_')[-1].lower() - for var in module_contents - if var.startswith("UNIT_KIND") - and var != "UNIT_KIND_INVALID"} - unit_kinds = {getattr(libsbml, var): unit_name - for var, unit_name in unit_kinds.items()} - return unit_kinds - - -SBML_UNITS = get_sbml_units() diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual.py index 85b24cdcc..f756e4519 100644 --- a/mira/sources/sbml/qual.py +++ b/mira/sources/sbml/qual.py @@ -1,75 +1,19 @@ -import logging -import csv import copy import re -from typing import List, Mapping, Optional -from copy import deepcopy -from collections import defaultdict +from typing import List, Mapping from urllib.parse import unquote -from mira.metamodel import * -from mira.resources import get_resource_file +from mira.sources.sbml.utils import * -import bioregistry -import sympy -import libsbml -from tqdm import tqdm from lxml import etree -class TqdmLoggingHandler(logging.Handler): - def __init__(self, level=logging.NOTSET): - super().__init__(level) - - def emit(self, record): - try: - msg = self.format(record) - tqdm.write(msg) - self.flush() - except Exception: - self.handleError(record) - - -logger = logging.getLogger(__name__) -logger.addHandler(TqdmLoggingHandler()) - -PREFIX_MAP = { - "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", - "dcterms": "http://purl.org/dc/terms/", - "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", - "vCard4": "http://www.w3.org/2006/vcard/ns#", - "bqbiol": "http://biomodels.net/biology-qualifiers/", - "bqmodel": "http://biomodels.net/model-qualifiers/", - "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", - "copasi": "http://www.copasi.org/static/sbml", - "jd": "http://www.sys-bio.org/sbml", -} - - -RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" DESCRIPTION_XPATH = f".//bqbiol:isDescribedBy/rdf:Bag/rdf:li" ENCODED_XPATH = f".//bqbiol:isEncodedBy/rdf:Bag/rdf:li" - -class Converter: - """Wrapper around a curies converter with lazy loading.""" - - def __init__(self): - self.converter = None - - def parse_uri(self, uri): - """Parse a URI into a prefix/identifier pair.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.parse_uri(uri) - - def uri_to_curie(self, uri: str) -> Optional[str]: - """Turn a URI into a CURIE.""" - if self.converter is None: - self.converter = bioregistry.get_converter(include_prefixes=True) - return self.converter.compress(uri) - - +logger = logging.getLogger(__name__) +logger.addHandler(TqdmLoggingHandler()) +grounding_map = get_grounding_map() converter = Converter() @@ -87,8 +31,10 @@ def __init__( def extract_model(self): if self.model_id is None: - self.model_id = get_model_id(self.sbml_model) - model_annots = get_model_annotations(self.sbml_model) + self.model_id = get_model_id(self.sbml_model, converter=converter) + model_annots = get_model_annotations( + self.sbml_model, converter=converter, logger=logger + ) reporter_ids = set(self.reporter_ids or []) concepts = self._extract_concepts() @@ -443,256 +389,3 @@ def _extract_concept(species, units=None, model_id=None): ) concept = grounding_normalize(concept) return concept - - -def get_model_annotations(sbml_model): - """Get the model annotations from the SBML qual model.""" - ann_xml = sbml_model.getAnnotationString() - if not ann_xml: - return None - et = etree.fromstring(ann_xml) - annot_structure = { - "publications": "bqmodel:isDescribedBy", - "diseases": "bqbiol:is", - "taxa": "bqbiol:hasTaxon", - "model_type": "bqbiol:hasProperty", - "pathway": "bqbiol:isVersionOf", # points to pathways - # bqbiol:isPartOf used to point to pathways - # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway - "homolog_to": "bqbiol:isHomologTo", - "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel - "has_part": "bqbiol:hasPart", # points to pathways - } - annotations = defaultdict(list) - for key, path in annot_structure.items(): - full_path = f"rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li" - tags = et.findall(full_path, namespaces=PREFIX_MAP) - if not tags: - continue - for tag in tags: - uri = tag.attrib.get(RESOURCE_KEY) - if not uri: - continue - curie = converter.uri_to_curie(uri) - if not curie: - continue - annotations[key].append(curie) - - model_id = get_model_id(sbml_model) - if model_id and model_id.startswith("BIOMD"): - license = "CC0" - else: - license = None - - # TODO smarter split up taxon into pathogens and host organisms - hosts = [] - pathogens = [] - for curie in annotations.get("taxa", []): - if curie == "ncbitaxon:9606": - hosts.append(curie) - else: - pathogens.append(curie) - - model_types = [] - diseases = [] - logged_curie = set() - for curie in annotations.get("model_type", []): - if curie.startswith("mamo:"): - model_types.append(curie) - elif any( - curie.startswith(f"{disease_prefix}:") - for disease_prefix in ["mondo", "doid", "efo"] - ) or _curie_is_ncit_disease(curie): - diseases.append(bioregistry.normalize_curie(curie)) - elif curie not in logged_curie: - logged_curie.add(curie) - logger.debug(f"unhandled model_type: {curie}") - - return Annotations( - name=sbml_model.getModel().getName(), - description=None, # TODO - license=license, - authors=[], # TODO, - references=annotations.get("publications", []), - # no time_scale, time_start, time_end, locations from biomodels - hosts=hosts, - pathogens=pathogens, - diseases=diseases, - model_types=model_types, - ) - - -def get_model_id(sbml_model): - """Get the model ID from the SBML model annotation.""" - ann_xml = sbml_model.getAnnotationString() - if not ann_xml: - return None - et = etree.fromstring(ann_xml) - id_tags = et.findall( - "rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li", - namespaces=PREFIX_MAP, - ) - for id_tag in id_tags: - uri = id_tag.attrib.get(RESOURCE_KEY) - if uri: - prefix, identifier = converter.parse_uri(uri) - if prefix == "biomodels.db" and identifier.startswith("BIOMD"): - return identifier - return None - - -def _curie_is_ncit_disease(curie: str) -> bool: - prefix, identifier = bioregistry.parse_curie(curie) - if prefix != "ncit": - return False - try: - import pyobo - except ImportError: - return False - else: - # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") - return False - - -def get_units(unit_definitions): - """Return units from a list of unit definition blocks.""" - units = {} - for unit_def in unit_definitions: - units[unit_def.id] = process_unit_definition(unit_def) - return units - - -unit_symbol_mappings = { - "item": "person", - "metre": "meter", - "litre": "liter", -} -unit_expression_mappings = { - 86400.0 * sympy.Symbol("second"): sympy.Symbol("day"), - 1 / (86400.0 * sympy.Symbol("second")): 1 / sympy.Symbol("day"), - 1 - / (86400.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 - / (sympy.Symbol("day") * sympy.Symbol("person")), - 31536000.0 * sympy.Symbol("second"): sympy.Symbol("year"), - 1 / (31536000.0 * sympy.Symbol("second")): 1 / sympy.Symbol("year"), - 1 - / (31536000.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 - / (sympy.Symbol("year") * sympy.Symbol("person")), -} - - -def process_unit_definition(unit_definition): - """Process a unit definition block to extract an expression.""" - full_unit_expr = sympy.Integer(1) - for unit in unit_definition.units: - unit_symbol_str = SBML_UNITS[unit.kind] - # We assume person instead of item here - if unit_symbol_str in unit_symbol_mappings: - unit_symbol_str = unit_symbol_mappings[unit_symbol_str] - unit_symbol = sympy.Symbol(unit_symbol_str) - # We do this to avoid the spurious factors in the expression - if unit.multiplier != 1: - unit_symbol *= unit.multiplier - if unit.exponent != 1: - unit_symbol **= unit.exponent - if unit.scale != 0: - unit_symbol *= 10**unit.scale - full_unit_expr *= unit_symbol - # We apply some mappings for canonical units we want to change - # We use equals here since == in sympy is structural equality - for k, v in unit_expression_mappings.items(): - if full_unit_expr.equals(k): - full_unit_expr = v - return full_unit_expr - - -def get_sbml_units(): - """Build up a mapping of SBML unit kinds to their names. - - This is necessary because units are given as numbers. - """ - module_contents = dir(libsbml) - unit_kinds = { - var: var.split("_")[-1].lower() - for var in module_contents - if var.startswith("UNIT_KIND") and var != "UNIT_KIND_INVALID" - } - unit_kinds = { - getattr(libsbml, var): unit_name - for var, unit_name in unit_kinds.items() - } - return unit_kinds - - -SBML_UNITS = get_sbml_units() - - -def _get_grounding_map(): - def parse_identifier_grounding(grounding_str): - # Example: ido:0000511/infected population from which we want to get - # {'ido': '0000511'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split("/")[0].split(":")) - for grounding in grounding_str.split("|") - ) - - def parse_context_grounding(grounding_str): - # Example: disease_severity=ncit:C25269/Symptomatic| - # diagnosis=ncit:C113725/Undiagnosed - # from which we want to get {'disease_severity': 'ncit:C25269', - # 'diagnosis': 'ncit:C113725'} - if not grounding_str: - return {} - return dict( - tuple(grounding.split("/")[0].split("=")) - for grounding in grounding_str.split("|") - ) - - fname = get_resource_file("mapped_biomodels_groundings.csv") - mappings = {} - with open(fname, "r") as fh: - reader = csv.reader(fh) - next(reader) - for name, ids, context, model, mapped_ids, mapped_context in reader: - mappings[(model, name)] = ( - parse_identifier_grounding(mapped_ids), - parse_context_grounding(mapped_context), - ) - - return mappings - - -grounding_map = _get_grounding_map() - - -def grounding_normalize(concept): - # A common curation mistake in BioModels: mixing up IDO and NCIT identifiers - for k, v in deepcopy(concept.identifiers).items(): - if k == "ncit" and v.startswith("000"): - concept.identifiers.pop(k) - concept.identifiers["ido"] = v - elif k == "ido" and v.startswith("C"): - concept.identifiers.pop(k) - concept.identifiers["ncit"] = v - # Has property acquired immunity == immune population - if not concept.get_curie()[0] and concept.context == { - "property": "ido:0000621" - }: - concept.identifiers["ido"] = "0000592" - concept.context = {} - elif concept.get_curie() == ("ido", "0000514") and concept.context == { - "property": "ido:0000468" - }: - concept.context = {} - # Different ways of expression immune/recovered - elif concept.get_curie() == ("ncit", "C171133") and concept.context == { - "property": "ido:0000621" - }: - concept.identifiers = {"ido": "0000592"} - concept.context = {} - # Different terms for dead/deceased - elif concept.get_curie() == ("ncit", "C168970"): - concept.identifiers = {"ncit": "C28554"} - return concept diff --git a/mira/sources/sbml/utils.py b/mira/sources/sbml/utils.py new file mode 100644 index 000000000..25400b26b --- /dev/null +++ b/mira/sources/sbml/utils.py @@ -0,0 +1,311 @@ +import csv +from collections import defaultdict +from copy import deepcopy +import logging +from typing import Optional + +import bioregistry +import libsbml +import sympy +from lxml import etree +from tqdm import tqdm + +from mira.metamodel import * +from mira.resources import get_resource_file + + +class TqdmLoggingHandler(logging.Handler): + def __init__(self, level=logging.NOTSET): + super().__init__(level) + + def emit(self, record): + try: + msg = self.format(record) + tqdm.write(msg) + self.flush() + except Exception: + self.handleError(record) + + +PREFIX_MAP = { + "rdf": "http://www.w3.org/1999/02/22-rdf-syntax-ns#", + "dcterms": "http://purl.org/dc/terms/", + "vCard": "http://www.w3.org/2001/vcard-rdf/3.0#", + "vCard4": "http://www.w3.org/2006/vcard/ns#", + "bqbiol": "http://biomodels.net/biology-qualifiers/", + "bqmodel": "http://biomodels.net/model-qualifiers/", + "CopasiMT": "http://www.copasi.org/RDF/MiriamTerms#", + "copasi": "http://www.copasi.org/static/sbml", + "jd": "http://www.sys-bio.org/sbml", +} + +RESOURCE_KEY = "{http://www.w3.org/1999/02/22-rdf-syntax-ns#}resource" + + +class Converter: + """Wrapper around a curies converter with lazy loading.""" + + def __init__(self): + self.converter = None + + def parse_uri(self, uri): + """Parse a URI into a prefix/identifier pair.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.parse_uri(uri) + + def uri_to_curie(self, uri: str) -> Optional[str]: + """Turn a URI into a CURIE.""" + if self.converter is None: + self.converter = bioregistry.get_converter(include_prefixes=True) + return self.converter.compress(uri) + + +def get_model_annotations(sbml_model, *, converter, logger): + """Get the model annotations from the SBML qual model.""" + ann_xml = sbml_model.getAnnotationString() + if not ann_xml: + return None + et = etree.fromstring(ann_xml) + annot_structure = { + "publications": "bqmodel:isDescribedBy", + "diseases": "bqbiol:is", + "taxa": "bqbiol:hasTaxon", + "model_type": "bqbiol:hasProperty", + "pathway": "bqbiol:isVersionOf", # points to pathways + # bqbiol:isPartOf used to point to pathways + # bqbiol:occursIn used to point to pathways - might be subtle distinction with process vs. pathway + "homolog_to": "bqbiol:isHomologTo", + "base_model": "bqmodel:isDerivedFrom", # derived from other biomodel + "has_part": "bqbiol:hasPart", # points to pathways + } + annotations = defaultdict(list) + for key, path in annot_structure.items(): + full_path = f"rdf:RDF/rdf:Description/{path}/rdf:Bag/rdf:li" + tags = et.findall(full_path, namespaces=PREFIX_MAP) + if not tags: + continue + for tag in tags: + uri = tag.attrib.get(RESOURCE_KEY) + if not uri: + continue + curie = converter.uri_to_curie(uri) + if not curie: + continue + annotations[key].append(curie) + + model_id = get_model_id(sbml_model, converter=converter) + if model_id and model_id.startswith("BIOMD"): + license = "CC0" + else: + license = None + + # TODO smarter split up taxon into pathogens and host organisms + hosts = [] + pathogens = [] + for curie in annotations.get("taxa", []): + if curie == "ncbitaxon:9606": + hosts.append(curie) + else: + pathogens.append(curie) + + model_types = [] + diseases = [] + logged_curie = set() + for curie in annotations.get("model_type", []): + if curie.startswith("mamo:"): + model_types.append(curie) + elif any( + curie.startswith(f"{disease_prefix}:") + for disease_prefix in ["mondo", "doid", "efo"] + ) or _curie_is_ncit_disease(curie): + diseases.append(bioregistry.normalize_curie(curie)) + elif curie not in logged_curie: + logged_curie.add(curie) + logger.debug(f"unhandled model_type: {curie}") + + return Annotations( + name=sbml_model.getModel().getName(), + description=None, # TODO + license=license, + authors=[], # TODO, + references=annotations.get("publications", []), + # no time_scale, time_start, time_end, locations from biomodels + hosts=hosts, + pathogens=pathogens, + diseases=diseases, + model_types=model_types, + ) + + +def get_model_id(sbml_model, *, converter): + """Get the model ID from the SBML model annotation.""" + ann_xml = sbml_model.getAnnotationString() + if not ann_xml: + return None + et = etree.fromstring(ann_xml) + id_tags = et.findall( + "rdf:RDF/rdf:Description/bqmodel:is/rdf:Bag/rdf:li", + namespaces=PREFIX_MAP, + ) + for id_tag in id_tags: + uri = id_tag.attrib.get(RESOURCE_KEY) + if uri: + prefix, identifier = converter.parse_uri(uri) + if prefix == "biomodels.db" and identifier.startswith("BIOMD"): + return identifier + return None + + +def _curie_is_ncit_disease(curie: str) -> bool: + prefix, identifier = bioregistry.parse_curie(curie) + if prefix != "ncit": + return False + try: + import pyobo + except ImportError: + return False + else: + # return pyobo.has_ancestor("ncit", identifier, "ncit", "C2991") + return False + + +def get_grounding_map(): + def parse_identifier_grounding(grounding_str): + # Example: ido:0000511/infected population from which we want to get + # {'ido': '0000511'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split(":")) + for grounding in grounding_str.split("|") + ) + + def parse_context_grounding(grounding_str): + # Example: disease_severity=ncit:C25269/Symptomatic| + # diagnosis=ncit:C113725/Undiagnosed + # from which we want to get {'disease_severity': 'ncit:C25269', + # 'diagnosis': 'ncit:C113725'} + if not grounding_str: + return {} + return dict( + tuple(grounding.split("/")[0].split("=")) + for grounding in grounding_str.split("|") + ) + + fname = get_resource_file("mapped_biomodels_groundings.csv") + mappings = {} + with open(fname, "r") as fh: + reader = csv.reader(fh) + next(reader) + for name, ids, context, model, mapped_ids, mapped_context in reader: + mappings[(model, name)] = ( + parse_identifier_grounding(mapped_ids), + parse_context_grounding(mapped_context), + ) + + return mappings + + +def get_sbml_units(): + """Build up a mapping of SBML unit kinds to their names. + + This is necessary because units are given as numbers. + """ + module_contents = dir(libsbml) + unit_kinds = { + var: var.split("_")[-1].lower() + for var in module_contents + if var.startswith("UNIT_KIND") and var != "UNIT_KIND_INVALID" + } + unit_kinds = { + getattr(libsbml, var): unit_name + for var, unit_name in unit_kinds.items() + } + return unit_kinds + + +SBML_UNITS = get_sbml_units() + + +def grounding_normalize(concept): + # A common curation mistake in BioModels: mixing up IDO and NCIT identifiers + for k, v in deepcopy(concept.identifiers).items(): + if k == "ncit" and v.startswith("000"): + concept.identifiers.pop(k) + concept.identifiers["ido"] = v + elif k == "ido" and v.startswith("C"): + concept.identifiers.pop(k) + concept.identifiers["ncit"] = v + # Has property acquired immunity == immune population + if not concept.get_curie()[0] and concept.context == { + "property": "ido:0000621" + }: + concept.identifiers["ido"] = "0000592" + concept.context = {} + elif concept.get_curie() == ("ido", "0000514") and concept.context == { + "property": "ido:0000468" + }: + concept.context = {} + # Different ways of expression immune/recovered + elif concept.get_curie() == ("ncit", "C171133") and concept.context == { + "property": "ido:0000621" + }: + concept.identifiers = {"ido": "0000592"} + concept.context = {} + # Different terms for dead/deceased + elif concept.get_curie() == ("ncit", "C168970"): + concept.identifiers = {"ncit": "C28554"} + return concept + + +def get_units(unit_definitions): + """Return units from a list of unit definition blocks.""" + units = {} + for unit_def in unit_definitions: + units[unit_def.id] = process_unit_definition(unit_def) + return units + + +def process_unit_definition(unit_definition): + """Process a unit definition block to extract an expression.""" + full_unit_expr = sympy.Integer(1) + for unit in unit_definition.units: + unit_symbol_str = SBML_UNITS[unit.kind] + # We assume person instead of item here + if unit_symbol_str in unit_symbol_mappings: + unit_symbol_str = unit_symbol_mappings[unit_symbol_str] + unit_symbol = sympy.Symbol(unit_symbol_str) + # We do this to avoid the spurious factors in the expression + if unit.multiplier != 1: + unit_symbol *= unit.multiplier + if unit.exponent != 1: + unit_symbol **= unit.exponent + if unit.scale != 0: + unit_symbol *= 10**unit.scale + full_unit_expr *= unit_symbol + # We apply some mappings for canonical units we want to change + # We use equals here since == in sympy is structural equality + for k, v in unit_expression_mappings.items(): + if full_unit_expr.equals(k): + full_unit_expr = v + return full_unit_expr + + +unit_symbol_mappings = { + "item": "person", + "metre": "meter", + "litre": "liter", +} +unit_expression_mappings = { + 86400.0 * sympy.Symbol("second"): sympy.Symbol("day"), + 1 / (86400.0 * sympy.Symbol("second")): 1 / sympy.Symbol("day"), + 1 + / (86400.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("day") * sympy.Symbol("person")), + 31536000.0 * sympy.Symbol("second"): sympy.Symbol("year"), + 1 / (31536000.0 * sympy.Symbol("second")): 1 / sympy.Symbol("year"), + 1 + / (31536000.0 * sympy.Symbol("second") * sympy.Symbol("person")): 1 + / (sympy.Symbol("year") * sympy.Symbol("person")), +} From 3989e085812eb3d83d331f6a3d340a3218f07468 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 13:25:34 -0400 Subject: [PATCH 24/44] Change name of qual processor file --- mira/sources/sbml/{qual.py => qual_processor.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename mira/sources/sbml/{qual.py => qual_processor.py} (100%) diff --git a/mira/sources/sbml/qual.py b/mira/sources/sbml/qual_processor.py similarity index 100% rename from mira/sources/sbml/qual.py rename to mira/sources/sbml/qual_processor.py From b300c7f744699bab3afb824f6af4b787a8a28fe4 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 13:29:42 -0400 Subject: [PATCH 25/44] Change name of import for qual processing api --- mira/sources/sbml/qual_api.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mira/sources/sbml/qual_api.py b/mira/sources/sbml/qual_api.py index 70cc2ee19..ef5c854b9 100644 --- a/mira/sources/sbml/qual_api.py +++ b/mira/sources/sbml/qual_api.py @@ -3,7 +3,7 @@ from libsbml import SBMLReader from mira.metamodel import TemplateModel -from .qual import SbmlQualProcessor +from .qual_processor import SbmlQualProcessor __all__ = [ "template_model_from_sbml_qual_file", From 865b23ca2a66038977d7fc5a6972d722da6e19bd Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 13:34:13 -0400 Subject: [PATCH 26/44] Capitalize Qual in docs --- docs/source/sources.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/sources.rst b/docs/source/sources.rst index f19fe6576..bc808b755 100644 --- a/docs/source/sources.rst +++ b/docs/source/sources.rst @@ -41,7 +41,7 @@ SBML extraction (:py:mod:`mira.sources.sbml`) :members: :show-inheritance: -SBML qual extraction (:py:mod:`mira.sources.sbml.qual_api`) +SBML Qual extraction (:py:mod:`mira.sources.sbml.qual_api`) ----------------------------------------------------------- .. automodule:: mira.sources.sbml.qual_api :members: From 7bf0398857082fb783c9d2c444c0e1c7a9545f9d Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 13:47:41 -0400 Subject: [PATCH 27/44] Add qual api to be exposed in init. Add converter and grounding map to utils --- mira/sources/sbml/__init__.py | 1 + mira/sources/sbml/processor.py | 2 -- mira/sources/sbml/qual_processor.py | 3 +-- mira/sources/sbml/utils.py | 6 ++++++ 4 files changed, 8 insertions(+), 4 deletions(-) diff --git a/mira/sources/sbml/__init__.py b/mira/sources/sbml/__init__.py index 0a0e47b0b..27d5326ff 100644 --- a/mira/sources/sbml/__init__.py +++ b/mira/sources/sbml/__init__.py @@ -1 +1,2 @@ from .api import * +from .qual_api import * diff --git a/mira/sources/sbml/processor.py b/mira/sources/sbml/processor.py index f07ec935b..8f37a9044 100644 --- a/mira/sources/sbml/processor.py +++ b/mira/sources/sbml/processor.py @@ -13,8 +13,6 @@ logger = logging.getLogger(__name__) logger.addHandler(TqdmLoggingHandler()) -grounding_map = get_grounding_map() -converter = Converter() #: This XPath query gets annotations on species for their structured diff --git a/mira/sources/sbml/qual_processor.py b/mira/sources/sbml/qual_processor.py index f756e4519..921d654d8 100644 --- a/mira/sources/sbml/qual_processor.py +++ b/mira/sources/sbml/qual_processor.py @@ -13,8 +13,7 @@ logger = logging.getLogger(__name__) logger.addHandler(TqdmLoggingHandler()) -grounding_map = get_grounding_map() -converter = Converter() + class SbmlQualProcessor: diff --git a/mira/sources/sbml/utils.py b/mira/sources/sbml/utils.py index 25400b26b..a4e21a755 100644 --- a/mira/sources/sbml/utils.py +++ b/mira/sources/sbml/utils.py @@ -61,6 +61,9 @@ def uri_to_curie(self, uri: str) -> Optional[str]: return self.converter.compress(uri) +converter = Converter() + + def get_model_annotations(sbml_model, *, converter, logger): """Get the model annotations from the SBML qual model.""" ann_xml = sbml_model.getAnnotationString() @@ -207,6 +210,9 @@ def parse_context_grounding(grounding_str): return mappings +grounding_map = get_grounding_map() + + def get_sbml_units(): """Build up a mapping of SBML unit kinds to their names. From 6db4b40dafbe655ca135c3360e14329d1ae08099 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 14:08:54 -0400 Subject: [PATCH 28/44] Add docstrings --- mira/sources/sbml/qual_processor.py | 29 +++++++++++++++++++---------- mira/sources/sbml/utils.py | 5 +++++ 2 files changed, 24 insertions(+), 10 deletions(-) diff --git a/mira/sources/sbml/qual_processor.py b/mira/sources/sbml/qual_processor.py index 921d654d8..0d4f13742 100644 --- a/mira/sources/sbml/qual_processor.py +++ b/mira/sources/sbml/qual_processor.py @@ -1,3 +1,10 @@ +""" +This module extracts an equivalent MIRA template model from an SBML Qual document. As +opposed to a regular SBML document, models derived from an SBML Qual document have empty +unit_definitions, parameters, and compartment attributes. + +This module extracts templates, initials and concepts from SBML Qual documents. +""" import copy import re from typing import List, Mapping @@ -15,14 +22,13 @@ logger.addHandler(TqdmLoggingHandler()) - class SbmlQualProcessor: + + """Traverse an SBML Qual document generated by libSBML and extract a MIRA Template model.""" + def __init__( self, sbml_model, qual_model_plugin, model_id=None, reporter_ids=None ): - # unit_definitions,parameters, and compartment attributes are empty for an sbml_model that - # comes from a qual plugin - self.qual_model_plugin = qual_model_plugin self.sbml_model = sbml_model self.model_id = model_id @@ -47,14 +53,12 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: templates: List[Template] = [] - # parameters and compartment attributes for sbml_model are empty, they don't exist for - # the qual_model_plugin - # each input to a transition can have a negative or positive sign or no sign # qual:sign = positive in source file indicates it controls the production of something # qual:sign = negative in source file indicates it controls the degradation of something # if both positive and negative exists, it is production process, with a list of # controllers from both the negative and positive side. + # if no sign is given, we default to positive sign # Transitions always have at least one input and one output # Since we always have at least one input, there will always be at least @@ -73,7 +77,7 @@ def _lookup_concepts_filtered(species_ids) -> List[Concept]: for qual_species in transition.getListOfOutputs() ] - # positive sign is 0, negative sign is 1 for inputs only + # positive sign is anything other than 1, negative sign is 1 for inputs only # outputs do not have a sign positive_controller_names = [ qual_species.qualitative_species @@ -207,7 +211,7 @@ def _extract_concepts(self) -> Mapping[str, Concept]: return concepts def get_object_units(self, object): - # QualitativeSpecies object does not have units attribute + # QualitativeSpecies object does not have a units attribute if hasattr(object, "units"): if object.units == "dimensionless": return Unit(expression=sympy.Integer(1)) @@ -218,6 +222,7 @@ def get_object_units(self, object): def _extract_concept(species, units=None, model_id=None): + """Extract a concept and its accompanying annotation from a qualitative species""" # retrieve local name for species that is only used a reference in the sbml qual model local_qual_name_reference = species.id # retrieve name of the species that can be used for look up in external resources @@ -245,7 +250,11 @@ def _extract_concept(species, units=None, model_id=None): # such that it can be parsed by the etree.fromstring() method new_annotation_string = ( """""" + xmlns:dcterms="http://purl.org/dc/terms/" + xmlns:vCard="http://www.w3.org/2001/vcard-rdf/3.0#" + xmlns:vCard4="http://www.w3.org/2006/vcard/ns#" + xmlns:bqbiol="http://biomodels.net/biology-qualifiers/" + xmlns:bqmodel="http://biomodels.net/model-qualifiers/">""" + old_annotation_string + "" ) diff --git a/mira/sources/sbml/utils.py b/mira/sources/sbml/utils.py index a4e21a755..b379085cc 100644 --- a/mira/sources/sbml/utils.py +++ b/mira/sources/sbml/utils.py @@ -1,3 +1,8 @@ +""" +Module to define shared functionality between processing SBML and SBML Qual documents. +""" + + import csv from collections import defaultdict from copy import deepcopy From fd188ca9554639a01363cebd205a5229fbb2a10c Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 14:09:47 -0400 Subject: [PATCH 29/44] Update docstring for shared model_id and model_annotation methods --- mira/sources/sbml/utils.py | 4 ++-- tests/test_sbml_qual.py | 6 ++++++ 2 files changed, 8 insertions(+), 2 deletions(-) diff --git a/mira/sources/sbml/utils.py b/mira/sources/sbml/utils.py index b379085cc..b918eb549 100644 --- a/mira/sources/sbml/utils.py +++ b/mira/sources/sbml/utils.py @@ -70,7 +70,7 @@ def uri_to_curie(self, uri: str) -> Optional[str]: def get_model_annotations(sbml_model, *, converter, logger): - """Get the model annotations from the SBML qual model.""" + """Get the model annotations from an SBML model.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None @@ -147,7 +147,7 @@ def get_model_annotations(sbml_model, *, converter, logger): def get_model_id(sbml_model, *, converter): - """Get the model ID from the SBML model annotation.""" + """Get the model ID from the model annotation.""" ann_xml = sbml_model.getAnnotationString() if not ann_xml: return None diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index 1cb16261e..746bf1031 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -31,14 +31,20 @@ def test_qual_models_from_example_repo(): + tms = [] for model in models: url = f"{BASE_URL}/{model}_stable.sbml" xml_string = requests.get(url).text tm = template_model_from_sbml_qual_string(xml_string) + tms.append(tm) + return tms def test_qual_models_from_biomodels(): model_ids = ["BIOMD0000000562", "BIOMD0000000592", "BIOMD0000000593"] + tms = [] for model_id in model_ids: model_text = get_sbml_model(model_id) tm = template_model_from_sbml_qual_string(model_text) + tms.append(tm) + return tms \ No newline at end of file From ae94904b77dc490fca1f96e0c93c3a1df9a192d6 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 14:10:56 -0400 Subject: [PATCH 30/44] Revert testing code for sbml qual --- tests/test_sbml_qual.py | 6 ------ 1 file changed, 6 deletions(-) diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index 746bf1031..1cb16261e 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -31,20 +31,14 @@ def test_qual_models_from_example_repo(): - tms = [] for model in models: url = f"{BASE_URL}/{model}_stable.sbml" xml_string = requests.get(url).text tm = template_model_from_sbml_qual_string(xml_string) - tms.append(tm) - return tms def test_qual_models_from_biomodels(): model_ids = ["BIOMD0000000562", "BIOMD0000000592", "BIOMD0000000593"] - tms = [] for model_id in model_ids: model_text = get_sbml_model(model_id) tm = template_model_from_sbml_qual_string(model_text) - tms.append(tm) - return tms \ No newline at end of file From e9fcf0626cf5644ccbaaa11379728d821e6ebb1f Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 19 Apr 2024 16:01:36 -0400 Subject: [PATCH 31/44] Add notebook --- notebooks/SBML Qual Demo.ipynb | 279 +++++++++++++++++++++++++++++++++ 1 file changed, 279 insertions(+) create mode 100644 notebooks/SBML Qual Demo.ipynb diff --git a/notebooks/SBML Qual Demo.ipynb b/notebooks/SBML Qual Demo.ipynb new file mode 100644 index 000000000..23814076d --- /dev/null +++ b/notebooks/SBML Qual Demo.ipynb @@ -0,0 +1,279 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 8, + "id": "e462d2ab-9a9b-412e-a85c-6020cc89c226", + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "\n", + "from mira.sources.biomodels import get_sbml_model\n", + "from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string\n", + "\n", + "MODEL_URL = \"https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads\"\n", + "BIOMODEL_ID = \"BIOMD0000000562\"" + ] + }, + { + "cell_type": "markdown", + "id": "c74ce658-5971-44d5-afdf-cf78c0526198", + "metadata": {}, + "source": [ + "## We load in biomodel BIOMD0000000562 from the biomodel's database and convert it to a semantically similar MIRA template model" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fb528cb1-5a93-4092-858b-be3e7daa0779", + "metadata": {}, + "outputs": [], + "source": [ + "model_text = get_sbml_model(BIOMODEL_ID)\n", + "tm = template_model_from_sbml_qual_string(model_text)" + ] + }, + { + "cell_type": "markdown", + "id": "a7283cf9-1821-4ba2-9cf9-c5eb94d15d68", + "metadata": {}, + "source": [ + "## Identify all concepts loaded in from the biomodel\n", + "\n", + "Qualitative species' annotations are not provided for models on the biomodel's website" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "6a446a48-7f96-4b63-8ef7-e27bb52a0cd0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "erk\n", + "ikk\n", + "gsk3\n", + "nfkb\n", + "ask1\n", + "ras\n", + "egf\n", + "egfr\n", + "traf2\n", + "ikb\n", + "map3k1\n", + "tnfr\n", + "ap1\n", + "mek\n", + "mkk4\n", + "ex\n", + "tnfa\n", + "raf1\n", + "map3k7\n", + "mkk7\n", + "cjun\n", + "sos\n", + "jnk\n", + "pi3k\n", + "p38\n", + "akt\n", + "ph\n", + "nik\n" + ] + } + ], + "source": [ + "for initial in tm.initials:\n", + " print(initial)" + ] + }, + { + "cell_type": "markdown", + "id": "70bcc3e5-0561-44da-b0f6-63546f23ee6f", + "metadata": {}, + "source": [ + "## Qualitative models do not have parameters" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "fe438910-9775-4a53-abf8-58627c2687b5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tm.parameters" + ] + }, + { + "cell_type": "markdown", + "id": "4f106e1a-05ec-4da1-bf42-ab75dceaeb7d", + "metadata": {}, + "source": [ + "## Visualize the template model structure loaded in from a SBML Qual document from the biomodels website" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "748485f3-a5b9-42af-9279-35cce125ea08", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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AAAA30TRHozz22GOKiIjQzJkz7Y4CBKWcnBxddNFFLBYGAEAAOXXqlDIyMpSbm6ulS5eqc+fOdkcCAABAI9A0R6M0a9ZMjz/+uP76178qNzfX7jhA0MnJyWFqFgAAAkhZWZmuuOIKrV27Vu+//7569epldyQAAAA0Ek1zNNr06dPVq1cv3XfffXZHwf9n777Do6jWP4B/N70nEEIISSgJJXQQaRIMCBG4VFGqdCmKiArY4KLSFIQroHhRVFAuivEHCFIFFFECSKT3GloKhJDes3t+fxwTjAkIsrNnsvv9PE8eyOxk5t09M2fOvnPmHLIq+fn5OHLkCCcBJSIiKieMRiOGDh2KnTt3YuPGjWjWrJnqkIiIiIjoATBpTv+Yvb09Fi5ciI0bN2Lr1q2qwyGyGocPH0ZeXh57mhMREZUDQgg899xzWL9+PTZu3Ijw8HDVIRERERHRA2LSnB5Ihw4d0KtXL0ycOBEFBQWqwyGyCvv374e3tzdq1aqlOhQiIiL6G6+++iq++OILfPvtt2jfvr3qcIiIiIjIDJg0pwf2/vvv4+LFi1i6dKnqUIisQtF45nZ2rKKJiIj0bNq0aViwYAFWrFiB7t27qw6HiIiIiMyEGRl6YCEhIZgwYQKmTZuG5ORk1eEQlXv79+/n0CxEREQ6t3DhQsyePRtLlizBgAEDVIdDRERERGbEpDmZxbRp0+Ds7IyZM2eqDgUA4OHhwfEkqVxKS0vD2bNnLTYJKM8VIirC+oDo3i1btgwTJ07EvHnzMHr0aM33x/OTiEg91sVky2zx+GfSnMzC09MTM2bMwEcffYQTJ06oDoeo3IqJiYHJZLJY0pyIiIjuz8qVKzF69GjMmjULkyZNUh0OEREREWmASXMym2eeeQZNmjTBSy+9pDoUonJr//79CA4ORtWqVVWHQkRERH+xfv16jBgxAhMmTMCUKVNUh0NEREREGmHSnMzGzs4O8+fPx44dO7Bly5a/XT85ORkTJ05EaGgonJycUKFCBXTt2hU7d+4sXmfWrFkwGAwwGAwlHgPZunVr8fJKlSoVL58/fz4MBgOysrIQHR1dvI6Dg8Md9+3s7IygoCB06tQJX3zxBXJycu4rxnXr1hXvx2Aw4PLly+jfvz88PT3h6+uLIUOGICUlBZcuXUKPHj3g6emJgIAAjB49GhkZGaU+l6SkJEyYMAE1atSAk5MT/Pz80KdPHxw+fPjeCoLKtaJJQP+M5wrPFaIirA9YH5A6O3bswIABAzBmzBgsWLCg1Os8P3l+EpF6rItZF9syHv9mPv4FkZn16dNHhIWFifz8/Duuk5CQIGrWrCngECaLAAAgAElEQVT8/f3Fhg0bRFpamjhz5ozo06ePMBgM4tNPPy2xvru7u2jbtm2p7TRv3lz4+vqWWn6n9f+87ypVqogNGzaI9PR0kZiYKGbOnCkAiAULFvyjGHv16iUAiD59+ojff/9dZGZmihUrVggAomvXrqJXr17i0KFDIiMjQ3z88ccCgHj55ZdLbCM+Pl5Ur15d+Pv7i02bNomMjAxx/PhxERERIVxcXMSePXvu+JmSdQgMDBRz5swp/p3nCs8Vor59+4q+ffuyPmB9QArt2bNHeHh4iCFDhgij0VjqdZ6fPD+JSB0AIioqinUx62KbxONfu+OfSXMyu4sXLwoXFxexaNGiO64zfPhwAUCsWrWqxPLc3FxRtWpV4erqKhITE4uXm/NkLtp3VFRUqde6dOlSfDLfb4xFJ/OmTZtKrN+gQQMBQOzatavE8po1a4q6deuWWDZs2DABQHz11VcllickJAhnZ2fRvHnzMt8TWYf4+HgBQPz000/Fy3iu8FwhKkqasz5gfUBqHDp0SFSoUEH07t1bFBQUlLkOz0+en0SkTlEdyLqYdbEt4vF/m7mPfybNSROvv/66qFChgkhKSirzdW9vbwFApKenl3ptyJAhAoD48ssvi5eZ82S+274fJMaik/n69esl1o2MjBQARFZWVonl4eHhwtPTs9Q+7ezsRFpaWql9PvTQQwKAuHr16l3jpvJr7dq1pcqf5wrPFaKipDnrA9YHZHmnT58W/v7+IjIyUuTm5t5xPZ6fPD+JSJ2iZB3rYtbFtojH/23mPv45pjlpYsqUKXBxccH06dNLvZaXl4e0tDS4uLjA09Oz1Ov+/v4AgMTERLPH9Xf7NkeMXl5eJX63s7ODvb093NzcSiy3t7eHyWQqtU+TyQRvb+8S4zcZDAYcPHgQAHDu3Ll7f8NUrsTExCAsLKz4GOK5IvFcIQJMJhPrA7A+IMu6cOECHnvsMYSGhuK7776Ds7Nzmevxei3x/CQilQoKClgXg3WxreLxL5n7+GfSnDTh6emJWbNmYcmSJTh27FiJ15ydneHt7Y3c3NwyB+i/fv06AKBKlSrFy+zs7JCfn19q3dTU1DL3bzAYylz+d/t+kBgflLOzM3x8fODg4ICCggII+SRIqZ8OHTqYbZ+kL/v37y8xCSjPlTvvk+cK2Ro7OzvWB3fYJ+sD0kJcXBwiIyNRuXJlbNq0Ce7u7ndcl9frO++T5ycRWYqjoyPr4jvsk3Wx9ePxf+d9Psjxz6Q5aWb48OFo1qwZXn755VKvPfHEEwCATZs2lViel5eHH3/8Ea6urujcuXPx8oCAAMTFxZVYNzExEVeuXClz325ubiVO/rp162Lp0qUl9r158+ZSf/fneO83RnPo06cPCgsLER0dXeq1uXPnolq1aigsLDTrPkkfhBA4cOAAWrRoUWI5z5Wy8VwhW8T6oGysD8jckpKSEBkZCXd3d+zYsQM+Pj5/+zc8P8vG85OILIl1cdlYF9sGHv9le6Djv8xBW4jMJDo6WhgMBrFhw4YSy/86Y256enqJGXOXLl1aYv3x48cLAOLDDz8UGRkZ4vz586Jfv34iMDCwzLGWunTpIry9vcWVK1fEnj17hIODgzh58mSJfQcEBIiNGzeK9PR0cfXqVfHcc88Jf39/cfny5X8UY9FYSzk5OSWWd+7cWdjb25eKMSIiQri7u5dYdv36dREaGipCQkLE5s2bRWpqqkhOThYff/yxcHNzK3NSBbIOJ0+eFABETExMieU8V3iuEBWNac76gPUBaS81NVU89NBDolatWiI+Pv6e/47nJ89PIlIHf4zpzLqYdbEt4vF/m7mPfybNSXN9+/YVoaGhpSZPunnzpnjppZdEzZo1haOjo/D29hadO3cWP/74Y6ltpKamilGjRomAgADh6uoqwsPDRUxMjGjevLkAIACI1157rXj906dPi3bt2gl3d3cRHBwsPvroo7vuOyAgQAwYMECcPXv2vmPcu3dvcQxFP1OnThUxMTGllr/77rvi119/LbX8rbfeKt5ecnKymDhxoggJCRGOjo7Cz89PPP7442L79u0PUgykc1988YVwdnYuc5Ixnis8V8i2FSXNhWB9wPqAtJSVlSXCw8NFUFCQiI2Nve+/5/nJ85OI1ChKGgrBuph1se3h8a/d8W/44wMm0szVq1cRFhaGWbNmlTlUCxEB48ePx4EDB7B3717VoRCRzvTr1w8A8O233yqOhMh65efno2fPnjh48CB27dqFevXqqQ6JiIjukcFgQFRUVHGbiciW8PjXDsc0J80FBwfj5ZdfxowZM5CUlKQ6HCJd+uskoERERGQZBQUFePLJJ7Fv3z788MMPTJgTEREREZPmZBmvv/463Nzc8NZbb6kOhUh38vPzcfTo0VKTgBIREZG2TCYThg4dip07d2Ljxo1o1qyZ6pCIiIiISAeYNCeL8PDwwDvvvIOlS5fi6NGjqsMh0pXDhw8jLy+PPc2JiIgsSAiB5557DuvXr8fGjRsRHh6uOiQiIiIi0gkmzclihg4diubNm3Ncc6K/2L9/P7y9vVGrVi3VoRAREdmMV199FcuXL8e3336L9u3bqw6HiIiIiHSESXOyGIPBgIULF2Lnzp1Yv3696nCIdCMmJgYtW7aEnR2rZCIiIkuYNm0aFixYgBUrVqB79+6qwyEiIiIinWGGhiyqTZs26N+/PyZNmoS8vDzV4RDpAicBJSIispxFixZh9uzZWLJkCQYMGKA6HCIiIiLSISbNyeLmzZuHhIQEfPjhh6pDIVIuLS0NZ8+e5SSgREREFrBs2TK8/PLLmDdvHkaPHq06HCIiIiLSKSbNyeKCgoIwadIkzJgxA4mJiarDIVIqJiYGJpOJSXMiIiKNrVy5EqNHj8asWbMwadIk1eEQERERkY4xaU5KvPHGG6hQoQLeeust1aEQKbV//34EBwejatWqqkMhIiKyWuvXr8eIESMwYcIETJkyRXU4RERERKRzTJqTEq6urpg9ezY+++wzHDhwQHU4RMoUTQJKRERE2tixYwcGDBiAMWPGYMGCBarDISIiIqJygElzUubpp59GmzZtMHnyZNWhECkTExPDoVmIiIg0snfvXjzxxBN46qmnOJ8OEREREd0zJs1JGYPBgPnz52PXrl1Yu3at6nCILC4hIQFxcXHsaU5ERKSBI0eOoFu3bujUqROWL18OOzt+9SEiIiKie8OWIynVunVrDBo0CK+88gpyc3NVh0NkUfv27YOdnR2aN2+uOhQiIiKrcubMGXTu3BnNmzfHN998AwcHB9UhEREREVE5wtYjKTd37lzUrVsXixYtwmuvvaY6HCJNREVFYevWrWjZsiVatmyJxo0bIyYmBmFhYfDy8lIdHhHpxL59+3D06NESyy5evAgAWLp0aYnljRs3RuvWrS0WG1F5ceHCBTz22GMIDQ3FunXr4OzsrDokIiIyk6+//hqZmZmllu/YsQOpqakllvXu3RuVK1e2VGhEZGUMQgihOgii6dOn4z//+Q/OnDmDgICA4uWnT5/GL7/8gjFjxiiMjujBrVmzBk899RTs7e1hNBrh6OiIatWqoWbNmhg2bBhatmyJ2rVrw2AwqA6ViBTasGEDevbsCXt7++KhJIqaakX1g8lkgtFoxPfff48ePXooi5VIj+Li4tCuXTt4e3tj586d8PHxUR0SERGZ0bBhw7BixQo4OjoWL/trW8loNMLd3R1JSUm8cUpWz2AwICoqCv369VMditXh8CykC6+++ioqVqyIadOmAQBSUlLw0ksvoWHDhli4cKHi6IgeXM2aNQHIBhwAFBQU4MKFC/jll18wbNgw1K1bF15eXujUqROOHDmiMlQiUqhLly7w8vKC0WhEQUEBCgoKUFhYiMLCwuLfjUYjPD090blzZ9XhEulKUlISIiMj4e7ujh07djBhTkRkhQYOHAgAxe2istpK9vb26Nu3LxPmRPRAODwL6YKrqyveffddDB48GFWrVsUHH3yA7OxsGI1GnD17Fnl5ebzgUblWlDT/q/z8/OL/Z2Vl4erVq6hfv76lwiIinXF0dMSAAQPwxRdflKgf/rrOwIED4eTkZOHoiPQrLS0NXbp0QX5+Pn799Vf4+vqqDomIiDTQqVMnVKxYEbdu3brjOgUFBRg0aJAFoyIia8Se5qQbfn5+CAoKwuzZs5GWloaCggIAsmfuyZMnFUdH9GAqVKgADw+Pu64jhMDHH39c4lFDIrI9AwcOvGPCHOAXQbJdy5cvx+rVq0stz87ORvfu3XHjxg1s3769xFB/RERkXRwcHDBw4MC7fmfy9fVF+/btLRcUEVklJs1JuXPnzuHJJ59EZGQk4uLiYDKZSrxub2+Pw4cPK4qOyHyqVat2x9eKeo526NDBghERkR49+uij8Pf3v+Prfn5+aNeunQUjIlLPZDJh9uzZ6N+/P7788svi5fn5+ejTpw/OnDmDbdu23fHJLiIish4DBw4s7mT3V05OThgyZAjs7e0tHBURWRsmzUmZwsJCTJ48GfXr18eGDRsA3B7v+c/s7e05xjNZhTp16txxok9HR0fMnz/fwhERkR7Z2dlh8ODBZQ6/4uTkhGHDhhVPEkpkKzZv3owLFy7AZDJhxIgR+Oijj1BQUIAnn3wS+/btw9atW1GvXj3VYRIRkQU88sgjqFq1apmv5efnF497TkT0IPiNi5RxcHBAw4YNIYQo1bv8z/Lz8/H7779bMDIibYSGhpb5GKGdnR3mzJlzx4YfEdmeOw3Rwi+CZKvmzJlT3GtQCIHx48cjMjISu3btwg8//ICHHnpIcYRERGQpBoMBQ4YMKfO7VXBwMFq0aKEgKiKyNkyak1LDhw/Htm3b4OrqCgeHO89Le+TIEQghLBgZkfnVrFmz1HHs4OCAOnXq4LnnnlMUFRHpUfPmzRESElJqefXq1ZkcJJtz4MABREdHl3oi8ZdffkHv3r3RqlUrRZEREZEqZQ3RUvRE3p2e7iUiuh9MmpNyjz32GPbt2wd/f/87TuaRmZmJK1euWDgyIvOqWbNmqYad0WjEsmXL7nrTiIhs0197UDk5OWHEiBEKIyJSY968eWW2EYUQWLlyJZ599tm7PrVIRETWp0mTJqhTp06JZfn5+RgwYICiiIjI2jBpTrrQoEED/P7772jYsOEdk4cc15zKu7/2GnV0dMTw4cPRpk0bRRERkZ4NHjy4xI02fhEkWxQXF4fVq1ffccI3IQQ+++wzDB48GIWFhRaOjoiIVPprB4N69eqhQYMGCiMiImvCpDnpRpUqVfDrr7+ia9eupSY4c3JywuHDhxVFRmQeNWrUKPGooIuLC+bOnaswIiLSs1q1aqFx48YwGAwwGAxo3Lgx6tatqzosIotatGjR3058azQasWrVKowfP95CURERkR4MGjSo+Iapo6Mjhg0bpjgiIrImTJqTrri7u+O7774r9aWnsLAQhw4dUhQVkXm4uLjA19cXgJz8c968efDz81McFRHp2dChQ2Fvbw97e3sMHTpUdThEFpWRkYH//ve/d+xlDsi5QTw8PDBjxgzMmzfPgtEREZFqISEhaNasGQwGAwoLC/lEHhGZFZPmpDv29vZYtGgRFi5cCDs7O9jZ2cFkMuHAgQOqQyN6YDVr1gQANG7cGKNHj1YcDRHp3cCBA2EymWA0GtG/f3/V4RBZ1GeffYbc3NwyX3N0dISzszMmTZqEK1euYNq0afD09LRwhEREpNrQoUMhhEDLli1RvXp11eEQkRXhzHOkWy+++CKqV6+OAQMGID8/H9euXUN6ejq8vLzkCsIIZF4Asq4AOfHyJ+8WUJAGQAD5qXI9Jx8ABsDRG3D2BVyryh/3YMAjFDDYq3qLZA1yEoDMi7ePwdzrQH4aIAqBwkzAVAA4uAF2zoC9K8L88/C7wYBP3xkKu7QjgGcdwMFd9bsgIpXyU4CM80BuoqxTchKAgnSgMBNVhQltGlQEAATFTQfi7QAHD8DRC3ANkD8uVQDPWoBTBcVvhKxeYSaQcQ7Ijrt93ctPBYw5gCkPKMwG7BzlMWpwkG0wl8q3216eofJ4vQdGoxELFiwoNcGnk5MTTCYTRowYgenTp6NKlXvbHv0DFixvIqK7ukt91L9WKibZGTCkrRHYP5b1ERGZDZPmpGu9e/cuHuc8OTkZRze9hfDqN4G0E0DaSdlgBwB7F5k4cPaTiQQY/kiWA8iMlf8WpAN5STIZYcy9/Xde9QDvBkCl1kDlCMCngfx7or/KTQSu7wKSdgOpx+RP/i35msEOcPGXP04V5M0YBw/5ZTI3CTDlA8Yc1PBIwLORjng4ZSKwBQAMgEdNwKchUOEheQxWagXYu6p8p0SklazLsg65ue/2tSz3+u3XnXwAlwBZjzi4AQY7DOlcHQYDgOwrgDABhVnyi2Juwu0bxID8Muhd//Y1zS8ccK9m8bdIVsKYI4/TG7uAWwfl8ZoZC0DI1518ZCLCqaJsT9k5yZvAhdlA7g3ZuSE/RR7fudflsQvIDgzeDQGfxkDlcKDyo2UmMlavXo1r165BCLk/R0dHmEwmDBs2DG+99RYCAwMt9EHYCMXlTURU7D7royruTuj0sD+eetRPdmZifUREZmIQRS1RIr0pSAfitwBX1+LSse341+wUjOvsivGDI4AKjWVSwLsh4F5dXgDvR14ykHVJXoBTjwOpR4Gbe+U+nSsBVToCwX2AgK6AIx/1tVnCBCRFA9e+A+I3A+lnZM+Fig8BFZrJRLd3A9lb3NVfvvY3Nm3ahEceeQQVPJ2BnGsyYZZ2Qibgk/fLBqGds0x4BfUCgp8A3Gto/16JSBsF6UDCD0DcRuD6j7KHlJ2TrEd8GgNeYTLR7VlbfgG0dym1ieTkZAAonhOhBGOOvBmccU7WJ+mngJSjQMpB+aSLW5C8pgX2AKo8zmsa3V3mReDqd0Dc9zJhYcqXN3Z9WwE+jf64KVMfcAu+v5u7ohDIuQ5knLnd9ko5BNw6JF/zCgOq/ku2vSq1AQx2aN68OQ4dOgQHBwcYjcbiZDkfvTcjHZU3Edm4B6yPzp07h9q1a5feLusjsgEGgwFRUVHo16+f6lCsDpPmpC/CBCRsBc4vBeK3yrvE/hFA1W5IdX4Im/dcxaCnB2u0byOQchi48QsQv0n2KLZzAKp2BWqNkckGXkRtQ/pp4PwnwKVVsneCV5hMYPt3APzayh7kWsm+Clz/GUjcAcRtkL0kKjYHQkYANQfLYYaISN+MufJm28Uvges75fXF7xEgoIvs/e3bQvunSYw5QHIMkPSrTNon7ZE39qp0BEKGyTrNzlnbGKh8KEgDYv8HXFgmEwlOFeRNloBI+fSTW7CG+84AbkbL69619fL661IFu1Mj0O6ZKBgMBvTv3x8zZswoOxlC90+H5Y0ag2Rb26uudvsmIv1hfURkFkyaa4dJc9KHwkzg3BLg7H/lo+v+7YGaQ+VF8357kZtLXrJMWsaukBdTjxpA7XFA7We1TZqSIkL2BD294HZ5h4wAqj0lh/BRwVQA3PgZuPwNcDlKLqsxCKj3iuyVSkT6knkBOL0QuPSV/DJWtStQvZ98aknVtaxIXjKQsEXWJfFb5VBmNQcDdV8EPELUxkZqZJwDTr4HXF4lf68+AKjeH6jcXg4tpkL6KeDKajw5Zi4MxixMH9MSDbpMAwK7gUPnPSAdlzcuLgcyL8n2f9hEljeRtWN9RGRWTJprh0lzUqswEzjzIXD6fTk+eehofd7ZLep5fP4z2Tuw3iSgznhO4Ggtrq0Hjs+Qj+kFdgfqjNPfkwUFafIGzpnF8vHFGoOAhv9m8pxID1IOASfnyi9b7jXkdazmEDnXhh7lJMj65PxSOZl2tb5A/deACk1UR0aWkH4GOD5LJis8a8v2jI6eZCosLMSJ48fQpHICcPYjOVRfxeZAozdlZwq6PzovbwC3nzRleRNZN9ZHRJpg0lw7TJqTOnEbgN/HA3m3gNCRQIMpchJFPctLBs5+KHsSOrgDTd+VPeKpfMo4J4/BhO2yF0Gjt4CKD6uO6u6ECbi6Bjj6puzVWvs5oPEsjlNMpEJOPHBsOnDhMznHRr1J8obWPcxvoAvCJIcjOz4TSP5dPlnTbD4nD7VWhdnAqfeAE+/Kse7rvwaEPiMnrtaz1GPyGL2yWg7Z9/BHclxbujuWNxHpBesjIk0xaa4dJs3J8rKvAb89IxOVoSOApnPl5JvlSV4ScOhVOV5twONAq89kA4DKB1EIHJshe4Z6NwBaLpGTzJQnwgic+xg4+m85zELLpUBAZ9VREdkGYQROzZdfpFwqA03fkwnnckvIL4SHXgXybsoeVWET9f9llu5dwlbgtzFAYQbQZDZQa2z5K9+be4GYcXLC2/qvA42mlZ8bVJbG8iYivWB9RKQ5Js21w6Q5Wda19TJh7uwnE81+bVVH9GCSdgO/jZZJ9NbL+dhWeZB1CYgeBKQeAZq8C9R5vvw13P4s9zpw4CU5TnG9ybIxqmosQCJbkHEO2DtMDsnScJpMLtu7qI7KPIy5wOn/AMdmyseRH1kBeISqjooehCkfODIFOPW+HDO2+UJ5o6e8Ekbg7GLg8BtAhWZA268B9+qqo9IPljcR6QXrIyKLYdJcO0yak4UI4MhU4MQcORRL80XWMx54YRbw+wvAxS+AhlOBxjPAyUJ06vpPwK9PypnY235jXY/XXfxCDjXj0wSI+F79pINE1ujK/wH7Rsh5N9qskE+qWKPU48DeIUDGeaDNl0BwH9UR0T+RdxPY1VM+Xv7wYiBkmOqIzCftBBA9AMiOA9qtlRO22TqWNxHpBesjIoti0lw7OprljqyWqQDYO1w+yt56mexhbi0Jc0C+l6L3dXIusG+kHP6D9OXyN8DOfwEBXYDO+60rYQ4AIcOBLjFyjOXt4bJHPRGZiZATV+3uD4SMBB7fZ70JcwDwaQh0/k3O2bG7rxyDlMqXzFhgW1v5NFKXGOtKWADy/Ou8H6gSCezsIm9o2TKWNxHpBesjIrIiTJqTtoQRiB4IXPsOiNgoE3vWKnQk8Oh6OS5s9CA5wRrpw6WVwJ6n5VAsj3xlPUMp/JVXPeDxPYC9K7C9HZB1RXVERFZAyKeJjk0HWnwEPPyBbQyBZOck32/zRXLi4QMvqo6I7lXWJWBHO8DRA3g8GvAKUx2RNuxdgbargNrPyl5/l1epjkgNljcR6QXrIyKyMpy9gLQVMw6I3ww8tg3wC1cdjfaqdgXabwJ2dpZDZbT4r+qIKH6z7P1f7xWg6RzV0WjPNQDo+BOwI0Ieh5G/lr+Jdon05OBk4NwnQHiUbQ5TUmc84FJF3gC3cwaavac6IrqbvCTgp85y7piOPwGO3qoj0pbBTo6Ta+con2p0qmhbk2KzvG2rvIn0jPUR6yMiK8Se5qSd0wuAC8tkosEWEuZFKj8q7zyfXwqc/VB1NLYt/Qywux9QcwjQ1IaGF3DyATpsBUx5cmgFYVQdEVH5dHoBcGYR8Mj/bDNhXqTaU3Js89PvA2c+UB0N3Ykwynk7hBHosMX6ExZ/1uw9oMZAec3LOKc6GstgedtWeRPpGesj1kdEVopJc9JG6nE5W3bjGUBgD9XRWF5Qb6DRW8DBV4CUw6qjsU2mAmDvUDlkSYslsLnJWV0DgEe/B27+Bpy0gR72ROZ2cx9w+HWgyTtA9QGqo1GvxiB5TT80GUjarToaKsvxWcDN/UC7NfLpAJtiAFp+CnjVl09FmPJVB6Q9lrdtlTeRnrE+Yn1EZKWYNCfzE4XAnoFApTZA/ddUR6NOgylApdbA3mHs6avC8ZlA+ikg/Bs5Nq8t8mkoh6Q5+jaQelR1NETlR2GmfEoloDNQ/xXV0ehHgzfkZ7JnMFCYpToa+rOUwzJp8dB8oEIT1dGoYeconwpJPwOceEd1NNpiedtWeRPpGesj1kdEVoxJczK/858B6WeBlp/Isb40Mn/+fBgMBhgMBgQFBZltXbMx2AOtlwHpp4GLX1hmnyRlxwGn/wM0ehvwCFUdjVp1XwB8WwCHXlUdCVH5ceIdoCANaLUUln5KRQiB6OhoPP/886hTpw6cnZ1RuXJlhIeHY+XKlRBClPqbwsJCfP7552jZsiV8fX1RoUIFNG/eHIsXL0Z+vjl7PBmAVp/Lz+bkXDNulx7YoVeBis3lhNc6YvH2l2dtoNGbwMn3gOxr2u9PFZ2W991ERUWhadOmcHV1LT4mjh8//mAbtZXyJtIzHddHFr0GsT4iskpMmpN5GXOBY9OB2s/JC4eZZGZmonbt2ujevXvxssmTJ0MIgSZN/v6O9v2sa1YeIUCt0cDRN+X40mQZx94GXPx12XizPIMczz3hB+D6T6qDIdK/rMvAqfflUCQKHjE+c+YMwsPDcfbsWaxevRppaWnYt28fqlWrhiFDhuCVV0r3fB8xYgRGjRqFTp064dSpUzh//jz69++PF154AU8++aR5A3SpDDR8Ezg1D8i+at5t0z+TuF3+PDQf5rzJU1BQgMaNGyM8/J/PS6Ok/VXnBXmcnphtuX1akkblraXo6GgMHDgQjz/+OJKSknD+/HnzJbCsvbyJ9Ezn9ZHFr0Gsj4isDpPmZF7XvgPybgINXjfrZoUQMJlMMJlMZt2uRdR/A8i9AVxbrzoS21CQBlz+Gqj3KmDnrDoafagcAVRuB5xbojoSIv079zHgUgmoPU5ZCA4ODvj222/RuHFjuLi4ICQkBF988QV8fX2xePFi5OXdvgl78eJFrFy5Es2aNcM777yDypUrw9fXF6+++ioiIyOxceNGxMTEmDfAOuMBp4pywmtS79wSwL+DJpOul8u2l70LUG8yELsSKMhQHY35aVjeWvm///s/CCHw4osvwsPDA6Ghobh69SoaNmz44Bu39vIm0rNyWB9pivURkdVh0pzM68IyILCb2XvneXp64sKFC9i8ebNZt2sRboFA1S7ysyHtXY4ChJCzmNNtoaOAaxE2cNsAACAASURBVN/Lm1pEVDZTPnBxmTxf7ByVhBAWFoaCggJUqFChxHInJycEBwcjLy8Pubm5xcuvXpW9vevVq1fmtgDgypUr5g3SzlF+Ruc/k5Mukzq5N4C4jUDoSLNv2tHREcePH8eePXvMvm3N1XhazrFzJUp1JOalYXlrqaie8vX11WYH1lreRHpWTusjzbE+IrIqTJqT+RRmAtd/BqozWVlKjUFA4o+cOM0S4jbIGzeO3qoj0ZfgJwEY5DAtRFS2pGj5JTBkuOpISklNTcW5c+fQrFkzeHvfrt/CwsLg6OiI06dPl/qb06dPw2AwoFGjRuYPKGQ4kJsI3CyHCVVrkvADALs/6ngq5lQBqPov2SawJuW0vI1Go7Y7sNbyJtKzclofaY71EZFVYdKczOfmPnlX1cyPZ61bt654Ag+DwVCih11ZVq5cWWJ9g8GAxMTEB173gVSOkJ9N8n7zb5v+RMjj0K+dRfaWlJSECRMmoEaNGnBycoKfnx/69OmDw4cPF68THh5e4vgaPHgwAKBTp04llqempmobrIM7UPEhIIkJLqI7urFLzkXhXsMsm/vrBFQxMTHo2LEjPD094ebmhg4dOiA6Ovqu20hPT0d0dDR69uyJKlWqYMWKFSVe9/f3x/z583HkyBFMmTIFSUlJuHXrFt577z3s2LEDb775JurUqWOW91OCR03AvTpw4xfzb5vuXVK0nOzZ3tWsm924cWOZba+/tskuXbqE/v37w8fHB76+vujevTsuXLjwt9u3SPvLL/yPa17pyXPLLY3KG7i3Nk2R06dPo3fv3vD29oabmxtatmyJjRs3lmjbjBo1qvh4Wb9eDlFYNAlo69atzR6/VZY3kZ4pro/+ej06c+YM+vXrB19f3+JlN2+W/YSt5tcg1kdE1kMQmcuJOUJ8F6zZ5nv16iUAiJycnBLLmzRpIgIDA4t/LywsFBMnThSRkZHi1q1b/3hds/suUIiT72m7D1uXcUGIryDEzX2a7yo+Pl5Ur15d+Pv7i02bNomMjAxx/PhxERERIVxcXMSePXuK1z18+LBwd3cXTZo0EZmZmUIIIXJzc0WrVq3EqlWrNI+12IGXhNjawnL7IypvfuoiRPRgs2+2SZMmwt3dXbRp00bs2bNHZGZmipiYGNG4cWPh5OQkfv755zL/bubMmQLyG5do3769OHr06B338e2334qgoKDi9StVqiQ+//xzs7+XEqKfFmJnN233QXe3pbkQByZqtvk7tb2Klvfq1av4mN6+fbtwdXUVLVqUvs4oaX8l7ZFtgsxYbbavgkblfT9tmnPnzgkfHx8RGBgotm3bVrxup06dhJ+fn3B2di61/TsdR2ZljeVNpGc6qI+EuF2/REREiJ07d4qsrCyxb98+YW9vL5KSkoQQCq5BrI/IwgCIqKgo1WFYJfY0J/PJTQTcgpSGkJqaim7dusFoNGLLli2lxoT9p+uahWsQkHtd233Yutw/egi4an8cvvHGG7h8+TLef/99/Otf/4KHhwcaNGiAb775BkIIvPDCC8XrNmnSBMuXL8eRI0cwdOhQCCEwduxYdOzYEQMGDNA81mKugTwGie4mNwFwr6bJprOysvDf//4Xbdq0gbu7Ox5++GGsXLkS+fn5ePHFF8v8m3//+9/Iy8vDqVOnEBYWhmbNmmHmzJkl1hFCYMyYMXj66acxceJEJCYmIikpCbNnz8b48eMxYMAAFBYWavKe4BYsPzNSR3Hba9SoUcXHdKdOndCtWzfExMTcsXcfYMH2l2ug/DdHgycIVdGovO+nTTNlyhSkpqZi0aJFiIyMLF7366+/RlaWwmEIrbG8ifRMB/XRn7322mto37493Nzc0KpVKxQWFqJSpUql1rPINYj1EZHVYNKczCcvGXDWaIKfe3DmzBm0atUKdnZ2WLhwIezt7c2yrtk4V+IkjFrLS5b/OlfUfFfr1q2DnZ0dunfvXmJ5lSpV0KBBAxw4cADXrl0rXt63b19MnToVa9euRXh4OJKTk0slvzTnXAnITbLsPonKk7yb8jzRgLu7O5o2bVpiWaNGjVC1alUcOXIECQllJ5+dnJwQFhaGJUuWoGfPnnjzzTexY8eO4tf/97//4dNPP8Wzzz6Ll19+Gf7+/qhUqRLGjBmD119/HVFRUVi8eLEm7wkufnIMeFIn75bStleLFi1K/B4cHAwAiI+PL3N9i7a/XPzkv9bU9tKovO+nTbN161YAQOfOnUus6+fnVzz5sBLWWN5EeqaD+ujPWrZs+bfbttg1iPURkdVg0pzMyAAINeN2paSkoHfv3ggKCsKWLVuwcuVKs6xrXgKAwUL7slWW+Xzz8vKQlpYGk8kEb2/vUmPiHTx4EABw7ty5En83c+ZMtGrVCnv27EHfvn1hZ2fpKlgABlb7RHdmgFbjT/r4+JS5vHLlygCAGzf+Pvnco0cPAHK86SJFCaxOnTqVWr9jx44AgC1bttxfsPdK8LqmC4raXgBKTEoLyJs8AGAymUqta/H2l/gjBoOVHaNmLu/7adPk5eUhIyMDLi4u8PDwKLUtzZ/avBtrLW8iPVNYH/2Vu7v7Xbdt0WsQ6yMiq+GgOgCyIs6+QMZZJbt2cHDAjh074O3tjUceeQSjR49G3bp1S/WAut91zSrvJuBdX9t92Lqi3g55yZo+ru7s7AwfHx9kZmYiJycHDg73VpX+/PPPSEtLQ6NGjTBu3Dg0adIETZo00SzOUjTsRUtkFTR8Iig5ORlCCBj+8gWqKFlelDy/a3jOzgCAW7duFS+7l+EQMjMz7yfUe5eXdLs3Fanh7AvkJ6uO4p5YvP1VdC5b03VPg/K+3zaNp6cnMjIykJmZWSpxfi83/zRjjeVNpGc6qI/uh0WvQayPiKwGuxyS+bhUAbLjlOza09MTgYGB8PDwwPfffw8PDw/07t27zMfd72dds8qJA1z8td2HrSv6fLNLP7Jnbn369EFhYSGio6NLvTZ37lxUq1atxDjCsbGxeOaZZ7BmzRp8//33cHV1Ra9evZCUZMHhUrJ5DBLdlWsAkHVVk03n5uYiJiamxLJjx44hPj4eTZo0QUBAAABg8uTJGDx4cJnbKOox/ucveK1atQIA/Pjjj6XW/+mnnwAArVu3fvA3UJbsq4BLgDbbpnvjUsUi1zxzsHj7K+ePNqk1Xfc0Ku/7adN07doVwO2nXIokJibi7Fk1nWcAWGd5E+mZDuqj+2HRaxDrIyKrwaQ5mY/vw/ILtOIvbzVq1MDq1auRlJSEPn36IC8vzyzrPpCsKzJh6atxb3Zb51ETcPYDbu7TfFfvvvsuQkNDMXLkSGzZsgVpaWm4desWPvnkE8yYMQPz588v7h2RmZmJ3r17Y+HChahfv37xcRcfH4+nnnoKBQUFmscLQH4uPAaJ7sy3FXCz9Jc0c/D29saUKVOwd+9eZGVl4ffff8fgwYPh5OSERYsWlVj366+/xowZM3Dp0iXk5eXh0qVLeO2117By5Uo0b94co0aNKl533LhxqF27NpYsWYIPPvgAN27cQHJyMj7//HPMmTMHgYGBmDx5sibvCUm7gUoaJeTp3vg+DNz8TXUU980i7a+kvbKXn3t1829bFY3K+37aNO+88w4qVqyIl156Cdu3b0dmZiaOHz+OESNGoEqVKmaP7Z5ZY3kT6ZkO6qN/SvNrEOsjIushiMylIEOIrx2EuPSNWTf73XffCchBZot/nn76abFq1apSyxcsWCD27t1barm9vf09r/v000+bNX4hhBCxXwmxylGIgkzzb5tK+rmHEL88aZFdJScni4kTJ4qQkBDh6Ogo/Pz8xOOPPy62b99evM7zzz9f4vg6duyYSEpKKnXczZw5U9tgCzKFWOUkROxKbfdDVJ4l7hTiKwiRGWvWzTZp0kQEBgaKkydPis6dOwtPT0/h6uoqIiIixO7du0usm5aWJj777DPRuXNnUaNGDeHk5CQ8PDxE8+bNxbvvviuys7NLbf/WrVvilVdeEWFhYcLZ2Vk4OTmJ0NBQMX78eJGYmGjW91Is44L8rK7v0mb7dG9i/yfEKmchCrI02XyvXr0EAJGTkyOEEGW2m6ZOnSqEEKWWd+vW7b7aamZvf/3yhBC7epl3m6ppWN730qYpcubMGdG7d2/h5eUl3NzcxCOPPCJ27dol2rdvL9zc3IrXK6sND0Ds3bvX7PFbZXkT6Zni+qis68hf01vKrkGsj8jCAIioqCjVYVglgxAKZw8i6/PT44CDK/DoetWR6MvP3eSEIB00moyNbju/FDjwEvBEHOCkcEIqvbn4BbB/LPDENdkbn4hKM+UD66oBtZ8FGr1tts02bdoUN2/exLVr5WMYjXty9E3gwmdAr8uAnaPqaGxXXjLwXSDQ+jOgRtnD+jyIHj16YPPmzcjLyzPr2LKay78lP5eHFwOhz6iOxnw0Lu8HFRYWhpycHFy+fNmyO7bW8ibSM53XR8qwPiIFDAYDoqKi0K9fP9WhWB0Oz0LmFToSiNsM5Gg8Pnh5kn0NSPhBfjakveoDAIMdcHmV6kj05cLnQFAvJsyJ7sbOSX7BOf8pYLLQsEnlkSlfJsxDRzFhrpqzLxDYTdbxZtCwYUNcunSp+Pe4uDhUq1atfCXMASB2JWBwAKr3Vx2JeZm5vP+JxMREVKxYsdTQcpcuXcKFCxfw2GOPWT4oay1vIj3TQX2kS6yPiKwKk+ZkXkG9ARc/4MS7qiPRjxPvAK5VZMKStOfoBdR4Gjg5DzDmqo5GH67vlGMP1x6nOhIi/as1VvYSOvuR6kj06+xiID9VflakXu1xwPWfgRu/mGVz8+bNQ2ZmJr7//nscPnwYzz77rFm2azHGHODUfKDmUMDBQ3U05mfm8v4nUlJSMHbsWFy9ehXZ2dnYv38/+vfvDy8vL0ybNs2ywVh7eRPpmQ7qI11hfURkdZg0J/OydwEaTQfOfwxknFMdjXoZZ2VvvEYzZA9GsoxGbwF5STKxY/MEcOhVoGpXwL+96mCI9M+9GhA2CTg+Hci98UCbmj9/PgwGA44cOYK4uDgYDAb8+9//NlOgiuReB47NAOq9ArgFqo6GAKBKRyDgceDQK5BDs/5zn3/+OU6cOIGAgABMmjQJ77zzjnYTyWrlzCJ546thOT/X7sSM5f2Pdl+lCnbs2IHU1FQ8+uijqFChAnr27InatWtj//79CAkJsWxA1l7eRHqmuD7SHdZHRFaHY5qT+QkjsKUp4OQLdPwRMNirjkgNYQR+7ADkpwFdD9ru56DK0TeBMwuBLgcBz1qqo1Hn9ELZkO16APBprDoaovKhMAvYVF+eMxHfAzCojkgfhAnY1RNIOw50Owk4uKmOiIqkHAa2tgAe+g9Qd4LqaNTJOAtsaQ7UmyxvoFsrlrdkK+VNpGesjyTWR6QQxzTXDnuak/kZ7IFHVgHJvwEn56iORp3js4Cb+4E2XzJhrkLDaYBXPSB6gBx/1xalHgOOvAE0fpsJc6L74eAOhH8LJGwDTtjwdeyvTswGErcBj3zFhLneVGgKNJomnyxKOaI6GjVMBcCeIYBXXaDBG6qj0RbL27bKm0jPWB+xPiKyYkyakzZ8GgJN5wBH3wKurVcdjeVdXQscnynvuFdoqjoa22TnCDzyPyD9DLB/LGzukcGceNkjtFIboD4bb0T3zbcV0Ow94Og04NLXqqNRL/Z/wLG3gYfeB/zaqo6GytJgKlCpFfBrHxuckF0A+0YC6aeAtt/YxpB4LG/bKm8iPWN9xPqIyEoxaU7aqfsiUGs0ED3QtiYHuf4zsOdpoPazQJ3nVUdj2zzrAO3+D7j0FXDoNdXRWE5+CrCzC2DvCoT/H2BgVU/0j9R9EQibCOwdBlxdozoada58C+wbAdR7FagzXnU0dCcGe6DdGvmF/eeuQEGa6ogs5+AkeZy2W2M7Q7KxvG2rvIn0jPUR6yMiK8VMCmnr4cVAYDfg525AwlbV0WgvfhOwqzsQ2BNo/oHqaAgAAroArb8ATv8HOPiyHJPXmuXE/zGWfirw2A+As6/qiIjKt2bvAbWfA3YPsM3Jhc8sAqIHAXVfAJq+qzoa+jvOlYAOW4G8ZGBHB+vv8SdMwO8vyOO0zZdAlUjVEVkWy1t1RERUhPWR6oiISANMmpO2DPbAI18D1Z6SQ0Vc+Fx1RNo5/ymwqzdQvT/Q9iv27tWTGoOAtquAs0vkGOfGHNURaSPtBLDtEcCYD0T+CrgFq46IyDo8/AHQeDrw+wQg5nnbmCfBlAfsfxY4OBFoMht4aIHqiOheuVeX1wBjtrwmpJ1UHZE2CrOB3f2AC58BbaOA6gNUR6QGy5uI9IL1ERFZGWb1SHt2jkDrZUD914DfRstHvAuzVEdlPoWZwL7hctzshlOBVp8BBgfVUdFfVesne14n7pAzvKedUB2ReV1YBvzQSibKH98tG61EZD4NpsjhnmJXAD+0lBPtWqvUo8DWlsDlr+XjxvVtaHgra+FeA4iMBtwC5fF6cbnqiMwr9TjwQwvg+k6gww+yc4YtY3kTkV6wPiIiK8KkOVmIAWg8E4hYD8RtBLY+DCTtVh3Ug7vxq3wvcZuA9huARm8DMKiOiu6kcgTQ9RDg6C0T52cWAcKoOqoHk5soe8//NkqONdzxJ8CpouqoiKxT8JOyDrF3l3XI8VnW9eSKMQc4PkMmzB09ga6HgaDeqqOif8rZF+i4E6g9Dtj3jJxjJve66qgejCgETi+UiRinCvJ8rPyo6qj0geVNRHrB+oiIrIRBCCFUB0E2JjtOJvgSfgBChsnxYp39VEd1f3KvA4dfAy6uAAI6y97lboGqo6J7JQqBYzOBk3MA7/pAi/8Cldqojur+iELg3BLgyDTAyQdouRQIeFx1VES2QRiBU/Nl0tzZF2g6F6jeD+X3pqkALkfJ61reLaDRm3ICVIO96sDIXBJ+APaPAQrSgcaz5GTl5a18k6KB358H0k4DDV4HGv6bT/bdCcubiPSC9RGR5gwGA6KiotCvXz/VoVgdJs1JnbgNcvKMvGQgdKR89N3FX3VUd5d3U04Ed3oh4OgBNHkHqDlUdVT0T2Wcl8dgwlagSidZnr4tVEd1d8IEXF0DHJ0GZF6UExQ2mQ04eKiOjMj25MQDx6bL+Tq86wP1Jss5FMrLFylhkhNYH5sO3DooHzFuNh9wr6Y6MtJCYTZw6j3gxBzArSpQ/3XZ/tL78Zp6VN6gurIa8G8vJ5n3rq86Kv1jeRORXrA+ItIUk+baYdKc1CrMAs79Fzg5DzDlAiEjgdpjAa96qiMrKe0kcO5jOSabgxtQ71WZrHRwUx0ZmUNR0ij5d6Dqv4A6zwEBXfTVCyI/RY6lfHYxkHkJqDlE9nLwCFEdGRGlHAFOzgWu/B/gHgyEjpY3VPX6BFJ2HBD7pZzAOvuanMC6/muATyPVkZElZJyHOD4L1w58heDqIUDd8UCNIfKpJb0QRiB+C3D2I3lj27elHAKvalfVkZU/GeeBE7OA2K9km4HlTUSqsD4i0gST5tph0pz0oTBLJqXPLQEyL8jxwWoOkWOpOldSE1PeTeDaOpmovPEr4BEK1BkH1BoLOLiriYm0Fb8ZOP0+kPiTTHyFjACCnwJ8GqqJx5QPXP8JuPwNcPlbwM4BqD4IqP+KPB6JSF8yL8q5EmJXAgVpcsikav2BwH+pH4YsL0nOv3HlWyBhmxyPs+ZgoO6LctIushmFhYUYO3YstmzeiPNRPeCWGCWTBNX7AdUHAP6PAXZOaoJLPQ5cXS07KWRdBap0BMJelje06cFkXpCdVC59xfImIrVYHxGZFZPm2mHSnPRFmIDE7bL3W/xmmTSsHAEEdpOJ9ArNtOv9KwqBlMPAjV/kZKU3fpEX7cDuQK3RgH9HwMC5c21Cxjng/CfApVVy+AXPOkBwb6Bye8AvXE6Qp5WsS/LYS9gOxG8E8tPkkDGhI2XCXMt9E5F5mPKAa98DF78EEnfI60ulNkDVLrIOqdhC+yeVCrOA5Bg56XbCVuDmPsDOEagSKecTCeyh7ospKZObm4vBgwdjy5YtiIqKQvfu3eU4s5e+Ai4sA279Lnv8BfaQx0rlRwH36toFVJAux4q98TNwdR2QcVY+oVF9EFBrDOBZS7t92yqWNxHpBesjIrNg0lw7TJqTfhVmykejrq4FEn+UveQcPQHf1kCFJnI8MZ9GgFs1wKXy/W079waQfQVIPQaknZCP1if/BhRkYN9lHyzb54tPPngXhsB/sVe5LRMmIHmfPAbjNgPpp+RNmwpNgYoPAd4NAO+GgFcdwKWKTEjdq8IseQymnZTHYOpxeQxmXQHsnAG/NvJJi6AnOL4wUXlWmCknwYrbIK9l2ddkXVGhKeDTGPAKk3WJZ23Ater9J9MLs4GcOHmzL+0kkH5aXtNSDstkvVuwnLMhsIfs+c5rms1KSUlBz549cfLkSXz//fdo27Zt6ZWyLgNXv5NP2t3cJ28AuVeXj6f7NPrjuldfHlf3cyyZCoDcRCD9zO1rXspBeawKoxyWL7AbENwHqNQa5XdS3XKG5U1EesH6iOgfY9JcO0yaUzkhZDLgxi8ysZh6XP5uzJEv2zkDrlXkUC5OPgAMt8dGy0+Vf5+fKhPvOYmyBzsA2Lv+kXxvKJPxlR9FzNlMtG0bjjlz5mDixIkq3izpVe51OVRP0m55wyX1mDymAAAGOZGtqz/g6C17cDq4y38LM2WDrTBT9hzPuQYUZPzxZ3ZyTD+fRvJJisoRsnFo76LsbRKRhrKvyjrk5m/yy1vaSflESxFHT8A1EHD0kj+AHEoFkHMbALJ3VEG6TJYX1SWA7CHlVe/2Nc2vLeAWZJn3RboWHx+PLl26ID09HVu3bkVYWNjf/5ExV7a5buwCbh0C0o7LIYiESb7u6Am4BgFO3nIyajtH+a8pX94YNuXLtlfuDXn9xB9fOZz9/rjmNZZPXvi1u//OD2R+LG8i0gvWR0T3hUlz7TBpTuWXMAKZsTIBkRMH5CQAecl/SpL/kVxwqoDiJLqzL+AaIBMSbsEyWVnGkCvvvPMO3n77bfz6669o1aqVRd8WlTO5N4DM8/JmTPY17N1/CKs2HcKil1vBYPyj0VaUPHf0BBw8ZRLLtYps7HnW5oSyRLauIE1OjpWTIL/c5cTLZHhBGopv+gK3bwo7ev/xhbHqHzfrAuRjxI7eKt8F6dSJEyfQtWtXeHl5YevWrQgKeoAbKYXZ8qmGnGvyeM2OkzdwCjNvJyuKbxo7yxs/rv6y3eVaBfCoxQRFefI35T323V8wpnddNG8QzPImIm2xPiK6IybNtcOkOVEZTCYTOnfujEuXLuHgwYPw9OQ40nRv3n//ffznP/9BXFyc6lCIiMjG7d27Fz169ECjRo2wbt06eHvzxgqZD7+kE5FesD4iW8bjXzuc1ZCoDHZ2dli5ciUyMjIwYcIE1eFQORIbG4uaNWuqDoOIiGzcunXr0LFjR7Rr1w6bN29mwpyIiIiI6D4waU50B/7+/vj000/x5Zdf4uuvv1YdDpUTTJoTEZFqy5YtQ9++fTFy5EisWbMGrq6uqkMiIiIiIipXmDQnuosePXpgwoQJGDt2LE6fPq06HCoHmDQnIiKV5s6di1GjRmHq1KlYvHgx7OzY3CciIiIiul9sRRP9jXnz5qFx48bo27cvsrOzVYdDOnf58mUmzYmIyOKMRiPGjh2LqVOn4pNPPsHbb7+tOiQiIiIionKLSXOiv+Ho6IhvvvkGCQkJGD16tOpwSMeuX7+OrKwsJs2JiMiicnNz0b9/f6xcuRLr1q1je4WIiIiI6AExaU50D4KDg/Hll19i1apVWL58uepwSKdiY2MBgElzIiKymJSUFERGRmLnzp3Ytm0bunfvrjokIiIiIqJyj0lzonvUrVs3vPLKKxg3bhwOHTqkOhzSodjYWDg4OCAwMFB1KEREZAPi4+MRERGBq1evIjo6Gm3btlUdEhERERGRVWDSnOg+zJ49Gy1atMDAgQORlpamOhzSmdjYWFSrVg0ODg6qQyEiIit34sQJtG7dGiaTCbt370ZYWJjqkIiIiIiIrAaT5kT3wcHBAd988w3S0tIwdOhQmEwm1SGRjly6dIlDsxARkeb27t2LiIgIhIaGIjo6GkFBQapDIiIiIiKyKkyaE92nqlWrYu3atdi6dStmzpypOhzSkdjYWCbNiYhIU+vWrUPHjh3Rrl07bN68Gd7e3qpDIiIiIiKyOkyaE/0Dbdq0wYIFCzB9+nSsXbtWdTikE0yaExGRlpYtW4a+ffti5MiRWLNmDVxdXVWHRERERERklZg0J/qHxo0bh2eeeQbDhw/HqVOnVIdDihmNRly9epVJcyIi0sTcuXMxatQoTJ06FYsXL4adHZvxRERERERaYWub6AEsXrwY9erVwxNPPIH09HTV4ZBCcXFxyM/PZ9KciIjMymg0YuzYsZg6dSo++eQTvP3226pDIiIiIiKyekyaEz0AZ2dnrF69GikpKRg+fDgnBrVhsbGxAIAaNWqoDYSIiKxGbm4u+vfvj5UrV2LdunUYPXq06pCIiIiIiGwCk+ZEDyg4OBhr1qzB5s2bMWXKFNXhkCKxsbFwdXWFv7+/6lCIiMgKpKSkIDIyEjt37sS2bdvQvXt31SEREREREdkMB9UBEFmD8PBwLF26FMOGDUNoaCh7gtmg2NhY1KhRAwaDQXUoRERUzsXHx6NLly5IT09HdHQ0wsLCVIdERERERGRTmDQnMpOhQ4fi9OnTeP7551GrVi106NBBdUhkQbGxsRzPnIiIHtiJEyfQtWtXeHl5Yffu3QgKClIdEhERERGRzeHwLERmNHv2bPTp0wd9+/bFuXPnVIdDFsSkORERPai9e/ciIiICoaGhiI6OZsKciIiIiEgRJs2JzMhgMGD58uUIDQ1Fz549kZKSojokshAmzYmI6EGsW7cOHTt2RLt27bB582Z4e3urDomIiIiIyGYxaU5kZq6urli7B3WqzgAAIABJREFUdi0yMjLQt29f5Ofnqw6JNJaXl4eEhAQmzYmI6B9ZtmwZ+vbti5EjR2LNmjVwdXVVHRIRERERkU1j0pxIA4GBgdi4cSNiYmIwfPhwmEwm1SGRhi5fvgyTycSkORER3be5c+di1KhRmDp1KhYvXgw7OzbPiYiIiIhUY6ucSCNNmzbF+vXrsXbtWrzwwguqwyENxcbGAgCT5kREdM+MRiPGjh2LqVOn4pNPPsHbb7+tOiQiIiIiIvqDg+oAiKxZ+/bt8eWXX2LQoEEICQnBpEmTVIdEGoiNjYW3tzd8fHxUh0JEROVAbm4uBg8ejC1btmDdunXo3r276pCIiIiIiOhP2NOcSGP9+/fHhx9+iFdeeQUrVqxQHU65Nn/+fBgMBhgMBgQFBf3tckuJjY1FSEiIxferB3otEyIivUpJSUFkZCR27tyJbdu22WzCnNcPKq947BKRXrA+ItKWQQghVAdBZAsmT56MDz74ABs2bEDnzp1Vh1OuNW3aFDdv3sS1a9fuabnW+vfvj8LCQqxZs8ai+9UTvZUJEZEexcfHo0uXLkhPT8fWrVsRFhamOiTleP0ovwwGA6KiotCvXz/VoSjBY5dIP1gfsT6yZbZ+/GuJPc2JLGTevHno27cv+vbti99++011OGbl4eGB8PBw1WEoExsbq7vxzG29TIiI9ObEiRNo3bo1TCYTdu/erduEOa8fVF7x2CUivWB9RGQdmDQnshCDwYDly5cjIiICXbt2xaFDh1SHRGaix6Q5ERHpx969exEREYHQ/2fvzsOjKPO1j9+d7mwESCCEEAhIwFFUNGoEUcCICAFBWcaEVUUEPY6ogIz4ih49Rzyj4jKOiIgzjKPjKA5qEInKIo4SQBZRBNllD0FAQkLMnuf9o0mk6YQspLu6k+/nunJBqqur766q5+mqX6rr6dhR6enpfFUaAAAA8HEUzQEvCgoK0gcffKBu3bqpb9++2rRpk9WRcI5ycnJ09OhRiuYAgAqlpqaqd+/e6tmzp9LS0hQeHm51JAAAAABVoGgOeFlQUJDmz5+vzp07q3fv3tqyZcs5Le/YsWOaPHmyOnbsqODgYMXGxurGG2/Um2++qby8vArnCwoKUrNmzdS/f38tX768fJ7U1NTyAUNsNpv27NmjYcOGKSIiQpGRkRo4cKB27dpVPn/ZACO5ublKT08vf57D4ahwedu2bVNKSooiIyPLpx09erTa+WrryJEjeuCBB9S+fXsFBQUpKipKQ4cO1XfffVfpez9b1tPt2bNHklyK5mwTa7cJAPiKuXPnKjk5WWPHjtUHH3yg0NDQs87P50fV+PzwTey7VWPfBbyD/qhq9EdANRkAljh58qTp2bOniY2NNbt27arVMg4dOmTi4uJMq1atzMKFC012drbJzMw0Tz31lJFkXnrpJZf5oqOjzcKFC82JEyfMtm3bzNChQ43NZjNvvPGGy3IHDRpkJJlBgwaZlStXmpMnT5olS5aY0NBQ06VLF7ccYWFhpnv37pXmLFteYmKiWb58ucnNzTWrV682drvdHDlypMb54uPjTZs2bdxep6LpGRkZ5rzzzjPR0dFm0aJFJicnx2zatMkkJiaakJAQs3LlyhplPdOCBQuMzWYzubm5bBMf2SYA4AueeeYZY7PZzBNPPFGt+fn8MFVO5/PDt0gy8+bNY989A/su4H30R/RHDVnZ/o+6R9EcsNDx48fNlVdeaeLi4sy+fftq/PwxY8ZU2kH269ev/KCgbL53333XZZ78/HzTunVrExoaajIzM8unl30wLly40GX+W2+91Uhy+3Cs7kFBWlraWd9HdfPV5KDgjjvuMJLMO++84zL90KFDJjg42CQkJNQo65n+/Oc/m+joaLf3wjapfLqntwkAWKm4uNjcfffdxm63mzlz5lT7eXx+uOLzw/eV7a/su67YdwHvoz+iP2rIKJp7DrdnASwUERGhxYsXq3HjxkpMTNTu3btr9PyPPvpIktS/f3+3xz799FNNnDjRZb4BAwa4zBMcHKzevXsrLy9Pn3/+udsyunTp4vJ727ZtJUkZGRk1ylmma9euFU6vbb7qSE1NVUBAgAYOHOgyvVWrVrrkkku0fv16HThwoNpZz3TmIKBsk6p5epsAgFXy8/M1bNgw/fOf/9SCBQs0fvz4aj+Xz4+q8fnhm9h3q8a+C3gH/VHV6I+A6nNYHQBo6CIjI/Wf//xH/fv317XXXqslS5aoc+fOVT6voKBAJ06cUEhIiJo0aVLr+aKjoyVJmZmZbo+dOVhZUFCQJKm0tLTKfBUJCwur03xVKVu25P5eTrdjxw7FxsZWmbUipxfN2SZV88Y2AQArHD9+XLfccot+/PFHLV68WN27d6/2c/n8qBqfH76pqKiIfbcK7LuAd9AfVY3+CKgZrjQHfECzZs30+eefq2PHjkpMTNSaNWuqfE5wcLDCw8OVn5+vnJycWs93+PBhSc6/LNeWzWar9XM9mS84OFgRERFyOBwqKiqScd6Syu2nV69etc5/etGcbVK9ZXt6mwCAt2VkZCgxMVH79+9Xenp6jQrmEp8f1V02nx++JzAwkH23Gstm3wU8j/6oesumPwKqj6I54CPCw8O1ePFiXXXVVUpKStLKlSurfM6QIUMkSWlpaW6PXXHFFZo0aZLLfIsWLXKZp6CgQMuWLVNoaKiSkpJqnb1Ro0YqLCws//3CCy/UnDlzqv18T+YbOnSoiouLlZ6e7vbYs88+q3bt2qm4uLhWy5akPXv2uNyehW1SNU9vEwDwps2bN6tbt24qLS3VihUr1KlTp1oth8+PqvH54ZvYd6vGvgt4B/1R1eiPgBrwxo3TAVRfQUGBGTp0qAkLCzOLFy8+67xlo2rHxMSYTz75xGRnZ5v9+/ebe++910RHR5u9e/e6zFc2+nZ2drbL6NtnDlRWNthHXl6ey/SpU6caSWbDhg0u0/v162fCw8PNvn37zMqVK43D4TA//vhjlcs7831UN19NBjo5fPiw6dixo+nQoYNJS0szWVlZ5tixY2b27NmmUaNGbgNmVJX1dEeOHDGSzNKlS93eC9uk8ume3CYA4E0rV640kZGR5vrrrzdZWVnntCw+P0yV0/n88C06NfAY+66pcjr7LuBZ9Ef0Rw2ZGAjUYyiaAz6osLDQDB8+3ISEhJgPP/zwrPMePXrUTJw40cTFxZnAwEATExNjhg8fbrZv337W+cLDw01SUpJZtmxZ+TyrVq0yklx+pk2bZowxbtMHDBhQ/rytW7eanj17mrCwMNO2bVvz6quvVrq8yv5WV518M2bMqDBfZdPLHDt2zEyePNl06NDBBAYGmqioKNO3b1+zZMmSs773qv6uuGbNGiPJ7Nq1i23iI9sEALzlo48+MqGhoWbw4MHm119/rZNl8vnB54c/Of0knX2XfRewEv0R/VFDdvr+j7plM8YYAfA5JSUluv/++/X666/rueee00MPPWR1JJzh/fff18iRI5WXl6fAwECr4wAAvGTu3Lm65557dM899+gvf/mLAgK44yEaHpvNpnnz5iklJcXqKAAaOPojNGTs/57DET7go+x2u2bNmqUXX3xRDz/8sMaPH6+ioiKrY+E0u3fvVmxsLAVzAGhAnn32WY0bN07Tpk3TzJkzKZgDAAAA9ZDD6gAAzu7BBx/UBRdcoGHDhmnv3r3697//rfDwcKtjQc6i+emDgAIA6q+SkhL94Q9/0N/+9je9/vrrGj9+vNWRAAAAAHgIl8YAfqB///76+uuvtWXLFvXo0UN79+61OhIk7dmzh6I5ADQA+fn5GjZsmP75z39qwYIFFMwBAACAeo6iOeAn4uPjlZ6eLpvNpmuuuUarVq2yOlKDx5XmAFD/HT9+XH369NHy5cu1ePFiDRgwwOpIAAAAADyMojngR9q1a6cVK1YoISFBiYmJevnll62O1GAZY7Rv3z6K5gBQj2VkZCgxMVH79+9Xenq6unfvbnUkAAAAAF5A0RzwM02bNtXHH3+sGTNmaMqUKRo8eLCysrKsjtXgZGRkKD8/n6I5ANRTmzdvVrdu3VRaWqoVK1aoU6dOVkcCAAAA4CUUzQE/ZLPZ9OCDD2rp0qVas2aNrr76am3cuNHqWA3K7t27JYmiOQDUQ6tWrVJiYqI6duyo9PR0xcbGWh0JAAAAgBdRNAf8WGJior777jvFxsbq6quv1l//+lerIzUYu3fvVkhIiFq1amV1FABAHUpNTVXv3r3Vs2dPpaWlKTw83OpIAAAAALyMojng51q2bKnPP/9c9913n+6++26NGzdOJ0+etDpWvbd7926dd955CgigGwWA+mLu3LlKTk7W2LFj9cEHHyg0NNTqSAAAAAAsQLUHqAccDoeef/55ffjhh1qwYIEuv/xyrVq1yupY9dru3bvVvn17q2MAAOrIs88+q3HjxmnatGmaOXMmfxQFAAAAGjDOBoB6ZPDgwdq0aZMuuugi9ezZU4888ogKCwutjlUv7d69m/uZA0A9UFJSonvuuUfTpk3T66+/rieffNLqSAAAAAAsRtEcqGeio6P18ccfa9asWZo5c6Z69Oihbdu2WR2r3qFoDgD+Lz8/X8OGDdM///lPLViwQOPHj7c6EgAAAAAfQNEcqIdsNpvuvvturVu3TqWlpbryyis1e/ZsGWOsjlYvFBUV6eDBgxTNAcCPHT9+XH369NHy5cu1ePFiDRgwwOpIAAAAAHwERXOgHuvUqZNWr16tP/7xj5owYYKuv/56bd++3epYfiU/P1+rVq1SZmZm+bR9+/appKSEojkA+KmMjAwlJiZq//79Sk9PV/fu3a2OBAAAAMCH2AyXngINwoYNGzRu3Dht2bJFTzzxhKZMmSK73W51LJ9XXFyspk2bKi8vT0FBQWrbtq1atWqlrVu36sEHH1Tnzp0VFxen9u3bKyIiwuq4AIAqbN68Wf3791fTpk312WefKTY21upIgM+755573G739+233youLk7NmjUrn2a32/WPf/yDdgXAY+iPAFc2m03z5s1TSkqK1VHqHYfVAQB4xxVXXKHVq1frxRdf1BNPPKH33ntPf/3rX5WQkGB1NJ/mcDgUHx+v1atXq7CwULt27dKuXbsUFBSk6dOnuwy0mpSUpM8++8zCtACATz75RLt379b999/v9tiqVat0880369JLL1VqaqrCw8MtSAj4n5YtW2rOnDlu0zdu3Ojye1xcHAUqAB5FfwTAW7g9C9CABAYGaurUqdq0aZOaNWumbt266ZFHHlF+fn6Vzy0tLfVCQt/UvXt3BQUFuUwrLCx0KZhL0gMPPODNWACAM5SUlOihhx7SxIkTlZqa6vJYamqqevfurZ49eyotLY2COVADo0aNqnKeoKAg3XHHHV5IA6Ahoz8C4C0UzYEG6Pzzz9fSpUv10ksvadasWbr88su1dOnSsz7n7rvv1ueff+6lhL6lS5cuKioqqvRxu92u+Ph49e/f34upAABn+vvf/66dO3fKGKNhw4ZpxYoVkqS5c+cqOTlZY8eO1QcffKDQ0FCLkwL+pVOnTrr44otls9kqnaewsFAjRozwYioADRH9EQBvoWgONFABAQGaMGGCNm3apE6dOqlPnz5KTk7W/v373eb9/vvvNXfuXA0dOlQbNmywIK21rr76ap1t+IeSkhL96U9/OuuBGwDAs/Ly8vTYY4/JGCNjjEpKStSvXz9NnDhR48aN07Rp0zRz5kwFBHD4C9TG7bffXul4ODabTZdddpkuuOACL6cC0BDRHwHwBs4agAauXbt2Sk1N1dKlS7V582Z16tRJTz75pAoKCsrnmTJlihwOhwoLC9WnTx/99NNPFib2vvbt26t58+YVPma323X55ZerX79+Xk4FADjdjBkzdPTo0fI/cpaUlCg/P1+zZs3Sc889pyeffNLagICfGzFihEpKSip8zOFwcCsEAF5DfwTAGyiaA5Ak9e7dW99//73+7//+Ty+88II6d+6stLQ0LV++XEuXLlVRUZGKi4uVnZ2t66+/XpmZmVZH9qqrr766wqsTucocAKx35MgRPfvss24n0GW/z5kzR7/88osV0YB6o127duratWuFx0PFxcUaNmyYBakANET0RwC8gaI5gHKBgYF68MEHtXnzZsXHx2vAgAEaOXKkHA5H+TxFRUXKzMxU7969deLECQvTele3bt1c1oP021XmSUlJFqUCAEjSf//3f1c69kRRUZH27Nmjvn37Kjc318vJgPrl9ttvd7tQICAgQN27d1ebNm0sSgWgIaI/AuBpFM0BuGnXrp3mz5+vhx9+WIcPH1ZxcbHL40VFRdq+fbtuvvlml9u41Gddu3ZVYWGhy7SSkhI988wzXGUOABbavn273njjjbMO2FxUVKQNGzZo2LBhlX6dG0DVkpOT3abZbDbdfvvtFqQB0JDRHwHwNIrmACpUWFiod999t9KCcHFxsVatWqXbb79dpaWlXk7nfV27dnVZF3a7XQkJCVxlDgAWe/jhh6sc3DMwMFClpaU6fvy4duzY4aVkQP0TFRWlG264wW0AvqFDh1qUCEBDRX8EwNMomgOo0Msvv6yMjIyzFsSLi4s1f/58TZgwwYvJrNG8eXO1bdu2/PeSkhI9/fTTFiYCAKxevVoff/xxhVeZ22w22e12BQYGatiwYfruu++Unp6uTp06WZAUqD9Gjx5dPuCu3W5XUlKSIiMjLU4FoCGiPwLgSRTNAbg5fvy4pk+fXq2vsJeWlmr27NmaMWOGF5JZq0ePHnI4HLLb7brqqqu4yhwALDZx4kS3K8zKxp9o166dnn76aWV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60Lp1a+3fv7/899rsz7Q51zZXdqW5L72fytZ5dXgyH30ZGjqK5gBQTUOGDJEkLVq0yGV6QUGBli1bptDQUCUlJZVPj4mJ0cGDB13mzczM1L59+ypcfqNGjVwOaC+88ELNmTPH5bXT0tLcnnfFFVdo0qRJtcpYF4YOHari4mKlp6e7Pfbss8+qXbt2LlfIAGgY6DMrRp+J+oa2XjHaOupCp06dtGPHDpd9hTZXseq2udNveeMr7+ds67w6PJmPvgwNmjdunA4A/kynBtY4c1Ty7Oxsl1HJ58yZ4/K8CRMmGEnmlVdeMTk5OWbnzp0mJSXFtGnTpsJBd/r162fCw8PNvn37zMqVK43D4TA//vijMea3EdtjYmLMJ598YrKzs83+/fvNvffea6Kjo83evXtd5qtuxrKBWvLy8lymJyUlGbvd7pYxMTHRhIWFuUw7fPiw6dixo+nQoYNJS0szWVlZ5tixY2b27NmmUaNGDEoCNDBlA4HSZ9Jnon7j+Og3tHV4yvr1640ks3Xr1vJptLlza3Pt27c3zz77rCXvZ+rUqUaS2bBhQ7XX+dmWV6am+WoyEGhN+7KqsqLuiYFAPYaiOQBU4fQPoaNHj5qJEyeauLg4ExgYaMLDw01SUpJZtmyZ2/OysrLMuHHjTExMjAkNDTU9evQwa9euNQkJCUaSkWSmTp1aPv/WrVtNz549TVhYmGnbtq159dVXXZZ35mvHxMSY4cOHm+3bt591vooyrlq1qjxD2c+0adPM2rVr3ab/6U9/Ml9//bXb9CeeeKJ8eceOHTOTJ082HTp0MIGBgSYqKsr07dvXLFmypC42AQA/UlY0N4Y+kz4T9RnHR7R1eF5+fr5p0qSJmTVrlst02lzt21xUVJTLe/LG+zHGuE0fMGBAleu8ouVVdu1rdfLNmDGjwnyVTa/Jeq1JVtQtiuaeYzPGmLNeig4ADZzNZtO8efOUkpJidRQA8HllfeX7779vcRIAnsTxEeAdycnJOnnypD799FOro9QLYWFhmjVrlu644w6rowB1gs9jz+Ge5gAAAAAAAD7olltu0fLly886WCWqp6SkRHl5eWrcuLHVUQD4AYrmAAAAAAAAPmjgwIGy2+168803rY7i944cOSJjjKKioqyOAsAPUDQHAAAAAADwQc2aNdNdd92lF198UcXFxVbH8Ws///yzJKlly5YWJwHgDyiaAwAAAAAA+KjJkyfrwIED+ve//211FL92+PBhSRTNAVQPRXMAAAAAAAAf1b59e6WkpOjJJ59UQUGB1XH8VmZmpoKDg9WsWTOrowDwAxTNAQAAAAAAfNgzzzyjgwcP6sUXX7Q6it/atWuX2rdvL5vNZnUUAH6AojkAAAAAAIAPa9u2rR599FFNnz5de/bssTqOX9q1a5c6duxodQwAfoKiOQAAAAAAgI+bMmWK2rZtqz/+8Y9WR/FLFM0B1ARFcwAAAAAAAB8XFBSkl19+WfPnz9fChQutjuN3fvrpJ3Xo0MHqGAD8BEVzAAAAAAAAP5CUlKQ777xTY8eOVUZGhtVx/MbJkyf1888/c6U5gGqjaA4AAAAAAOAnXnnlFbVo0UIjR45USUmJ1XH8ws6dO2WMoWgOoNoomgMAAAAAAPiJsLAwvfPOO1q1apWef/55q+P4hR9++EFBQUH63e9+Z3UUAH6CojkAAAAAAIAfufLKK/WnP/1Jjz/+uL766iur4/i8zZs3q1OnTgoMDLQ6CgA/4bA6AAD4kqysLBlj3Kbn5ubq+PHjLtMaN27MQReABu3XX39VQUGBy7TCwkJJcuszg4OD1ahRI69lA1B3OD4CfNOkSZO0cuVKDR06VKtXr9b5559vdSSftWnTJnXu3NnqGAD8iM1UdPQDAA1Ur1699OWXX1Y5n91u14EDB9SqVSvPhwIAH/Xqq69qwoQJ1Zp35syZuu+++zycCIAncHwE+K68vDz16tVLWVlZWrVqlZo1a2Z1JJ/Uvn173X333Xr00UetjgLUKZvNpnnz5iklJcXqKPUOt2cBgNOMGDGiynlsNpt69uzJCSGABi8lJUV2u73K+ex2OwfygB/j+AjwXaGhoUpNTVVeXp4GDx5c/o0v/CYnJ0f79u3TpZdeanUUAH6EojkAnCY5OVkOx9nvXBUQEKDbb7/dS4kAwHdFRUWpV69eZy2cBwQE6IYbblBUVJQXkwGoSxwfAb6tVatW+vjjj7VhwwaNGTNGJSUlVkfyKT/88IOMMdyeBUCNUDQHgNM0a9ZMffv2rbIANGTIEC+mAgDfddttt1V4r+Mz5wHgvzg+AnxffHy8UlNTlZqaqrFjx6q0tNTqSD5j7dq1at68udq3b291FAB+hKI5AJxh9OjRlR5kOhwO3XTTTYqIiPByKgDwTUOGDDnrFagOh0ODBg3yYiIAnsDxEeD7brjhBi1YsEDvv/++7rrrLgrnp6xfv15XXXWVbDab1VEA+BGK5gBwhkGDBik4OLjCx0pLSzV69GgvJwIA39WkSRPdfPPNCgwMdHvM4XDolltuUdOmTS1IBqAucXwE+Ic+ffrogw8+0Lvvvqs//OEPFM4lrVu3TldddZXVMQD4GYrmAHCGRo0aadCgQRUWgIKDgzVgwAALUgGA7xo1apSKi4vdppeUlGjUqFEWJAJQ1zg+AvzHTTfdpPfff19vvvmmRo8e3aAHBz158qS2b9+uhIQEq6MA8DMUzQGgAqNGjVJRUZHLtMDAQN16660KDQ21KBUA+KabbrpJYWFhbtNDQ0PVr18/CxIB8ASOjwD/ccstt+izzz5TWlqa+vXrp+zsbKsjWeLbb79VSUkJV5oDqDGK5gBQgX79+rndTqCoqEgjR460KBEA+K7g4GAlJycrKCiofFpgYKCGDx+ukJAQC5MBqEscHwH+5frrr9eKFSu0fft29ejRQwcPHrQ6ktetW7dOUVFRateundVRAPgZiuYAUIGyYs/pBaCIiAjdeOONFqYCAN81cuRIl69/U0gD6h+OjwD/07lzZ3399dcqKChQjx499P3331sdyatWrlypa665xuoYAPwQRXMAqMSIESPKC0CBgYEaNWqUHA6HxakAwDfdcMMNatGiRfnvkZGRuv76660LBMAjOD4C/E9cXJzS09MVFxen7t27a968eVZH8prVq1dTNAdQKxTNAaAS1113nVq2bCnJecXk8OHDLU4EAL4rICBAI0eOVFBQUHkhzW63Wx0LQB3j+AjwTy1atNCSJUs0YcIEDR8+XPfcc0+Fg3jXJ3v27NHBgwd17bXXWh0FgB+iaA4AlQgICNBtt90mSYqJiVH37t0tTgQAvq3sClRuzQLUXxwfAf7LbrfrmWee0T/+8Q+99dZbuummm3T48GGrY3nMqlWrFBgYyCCgAGqF79EBwOkKf5HyDkmFWVJJnkbc2FYvvCDdPribbIeXSTa7FBQhhUQ7f2xcRQmggTLFUv4RKf9nqShbKi3Q1e2K1LZ1pCSpa9tfpMylkj1ECmwqBUdJIVGSjcNPwK+UFjjbef4RqeiEZEo0onebU8dHVzuPjyQpMNzZ1kNbS4FNrM0M4Kxuv/12XXzxxRo+fLji4+P15ptvql+/fpXOv2HDBl100UW+Mbj3GedrKi2Qin91Hl8ENnE5X1u1aqWuuOIKNWrUyOrUAPwQZy0AGiAjnfhR+uVb6cQmKWuTlL1NyjsoleS7zJkg6aI20sh2H0lffOS6GJvdWThv3EGK6CyFd5YiLpMiuziLRADg70qLpKyN0onNUvZ2KefUT94hZxHtDDZJt3d1/mv78qYKFmhzFs5DY6QmFzh/ml4ohV8iNbuMgjpglbK2nvWD85goZ/upY6MMqfC42+y/HR+lSl+kui/PHups5407ONt404uc/0Z2cRbXAVjuqquu0oYNG3Tffffppptu0v3336/nnntOwcHBLvMVFxdrxIgRuvjiizV//nwFBHjjhgXVP187m5TmAep7Y4S0pCfnawBqzGaMMVaHAACPy90rHVwoHf5C+vlrqeCoFBAshV/kLNaEXyQ1aus8wQttLQU1dx5IBQTr/Q8/UcqtQ6Tik5IpdV7dkH/YeSL5a4aUs815UJe1yflYQLDUoqvU8nqp9U1Si6vlLCEBgI8rPillfiH9/B/p2DfOk9WSPGe/1vR3UpMLpaYXSKFtnP1lSEvnFeRBEVJAkGRzaPP2fZKkSy5o57wavbTQeTVYwamr0vMOSb8e+K0ol7PTeZWYPVRqnuDsM1smStE3SI4wi1cIUE+V5Es/f+U8Ljq6SvplnfNKTXvIb3/Manqh1ChWColx/rErpKUUGCHZAiR7qN7/4GOlJP/e+U0TSSrKcRbY8zJOXZl+yNm+T2yRsrc6j5FsAc4CeotrpJbXSTFJzuUCsNTbb7+t++67T+eff77efPNNXXbZZeWPzZ49W/fdd58k6f7779ef//xnz4Q4h/M1ORo5//jH+RoaIJvNpnnz5iklJcXqKPUORXMA9devB6Xd/5D2fyj9st55ZVN0ovPgqOV1UrP4ur+qMXevs9j081fS4eXSyZ+kRm2k2MFS+1HOk0QA8CW5+6R986SMz6QjK5yF7vDOzv6qxdVS5NXO4pmnbkdlSpwFtaPfOAv1R1c7r3YNCJJa9pBi+knnDXOeKAOovcLj0r5/Swc/cRalinOdhagW15z66SY17eQsbHtC3qFTbXyVs50f/UYyRc4/lrUe4GznTTt55rUBVGnnzp2688479c0332jatGl69NFHlZ+fr7i4OP3yyy8yxshms+mFF17QpEmT6uZFOV8DzhlFc8+haA6gnjHSoSXSjtecJ4VBEVLboVLbIc6rFgOCvBsn6wfpwEfSvg+cX3tuFi+df48Ud5vkaOzdLABQpihb2ve+tPttZ6E8qJnzis+Yfr5x5Wf+YenQ585C/qHPpaIsKaqnFDdaajeM+yUD1WVKpIw0afdb0oGFUoBdatVXat3feXVlo1jrshXnSpnLnPkyFjm/gRLZVYq7XWo/0tkvAfAqY4zeeOMNPfTQQ2rfvr0SEhL0zjvvqLi4uHwem82mt99+W6NGjartq3C+BtQhiuaeQ9EcQP2RuVT6/lHp2Hh2iC4AACAASURBVFrnVUvn3+082LGHWp3M6Zf10s450p53nF8lvGCC1GkS9/YE4D0nd0s7X3f2RSV5UqsbnQWq2EHeP0mtLlPivBJs91vOK9FsAdJ5I6ROk51XwANwV5zrPN7Y+qLzNkhlx0XnjfDNPzqZUunoSucf8va+KxnjLJzTzgFL7N69W7fddptWr16tkpISl8dsNpscDoe++OIL9ejRo2YL5nwNqHMUzT2HojkA/3fsG2ntBOdBTuwg6dInpGaXW52qcgVHnSex22c676cXP13qON5zX4cGgJyd0sbHnVeXN2rrPAk8f7z/nQQWHpd2viHteNX5le7zhkmX/a/UuKPVyQDfUJIvbXtZ+vE5qTRfihsjdZooNfmd1cmqryhH2vU35/v4db+z0B8/XQo7z+pkQIOSkpKi1NRUFRUVuT1mt9sVFhamb775Rp06VeO2SpyvAR5D0dxzKJoD8F+FWdJ3j0i73nAOGnfli7598HWmgmPSj3+Stv1FanaF1OU1qfmVVqcCUJ/k/yz98D/OfrLx+dJlTzq/Al3X9wf1NlMs7ZvvfG8ndzmvVLv0CeegpECDZKQ9/3JewVlwzHmF9oUPSsGRVgerPVPsvAf7xv923rrlgvulztP87499gB9avXq1rr32Wp2tXORwONSqVSutXbtWrVq1qngmztcAj6No7jkUzQH4pyPp0sqRUkmhdOXzzkFb/FXWJmndH5yDYsU/LV00RYzeDuCc7X5L+nay8+vFlz4pdRjj/8XyM5liadffpU3/47zC9sqXnF/zBhqS3H3SmvHO+4N3uFO67H+k0NZWp6o7pUXSztnSD//rvIXD1XOc4y8A8AhjjLp166Zvv/3W5V7mFQkMDNRFF12k9PR0NW58xv2/OV8DvIKiuefw3RIA/ufHZ6Sl10sRl0kDfvDvAzBJiugs3fgf6bLp0vfTpOU3Oa/KAIDayM+UlveTVt8pnTdSGrhV6jiu/hXMJed7On+8NGCL8xYOq8dIX97kvMIeaAh+elNK6+y8ErvPCunqN+pXwVySAgKdV5kP3CJFdZeW95e+ucs5LgOAOjdv3jytWbPmrFeZlykqKtKPP/6o5ORk1wI752sA6gGuNAfgP0yJtPYPzvtcXvG81OlB1bu/8B/7Rvr6Vuco8td/KjWKtToRAH9ydJW0Itl5NeY1b0ktrrE6kXcdSZdW3SGVFkg950uRV1udCPCM0iLp20nS9lnOKx4v+1/nt0oagv0fSd+Mkxq3l3p+JIW1szoRUK+sX79eX331lTZt2qT169dr69atKigokM1mU3BwsIqKitwGB7Xb7brzzjv1xpzZnK8BXsaV5p5D0RyAfzDF0ooU6dDn0rXvSrG3WJ3Ic37d77yKqihbunE5A9wBqJ7db0nfjJdi+krXvO08mWuICo9LK0c7b1XR7a9S+9FWJwLqVlGO9NUg6dha6Zo3pba/tzqR953cJX012PmtkuvTpOYJVicC6q2SkhLt2rVLGzdu1A8//KCNGzdq/fr1OnDggIwxcjgcKi0tVWlpqaaPu1jT+uzhfA3wIormnkPRHIAfMM7bDOybL/X63PnV3Pqu8Lj0RV/nv33TpZBoqxMB8GU7Zkvr7pMueth5r01bA78Dnyl1Djy29QWpy2znLVyA+qAoR/qyv5SzS7rhc+etDxqq4pPOqz2PrZFuWCw1v8rqRECDkpubq82bN+v777/Xpk2b9O1/3tPWn47oxWce021/+F+r43ke52vwERTNPYeiOQDf9/1j0pYZUuLHUkyS1Wm8p+CItLiHFNhY6pPecL52DaBmdr4urblXip8uXfKo1Wl8y6b/lTY+6Rw4sOM4q9MA56a0QFrWWzr5k9T7C6lpJ6sTWa8kX/p6qPPWVDd+JUVcanUioGE67XztaGCCWrRoYXUi7+B8DT6AornnNPDLkAD4vMxl0o9/krq82rAK5pIUHCX1+tR5crxhitVpAPiiw8uldfdLl/0PBfOKdP5vqfPjzvur/vyV1WmAc7N2gpS1Seq9jIJ5GXuIdN1HzivuvxoiFf5idSKg4TnjfK3BFMwlzteAeo6iOQDfVXhcWnW71PbWhnuFYOMOUtfXnQN9ZSyyOg0AX/LrfudYD7FDpM6PWZ3Gd132pBQ7yHkbh18P/H/27j0uqjr/H/hruA1XB0TuFxXDS17IBTWLUhO8rNfYwDQ1K4WttdSyhdpqa7NScyu/re3KVuuWeUF/q4mXDDTLG4n3S0LeURAFBOTOwHx+fxyZHAGZwZk5w/B6Ph4+fHA48zlvzpzPm8/nzZnzkTsaotY59wVw/kvgoa+BDr3kjsay2CiByHWAplZazwD8IDWR2XC+xvkakRVj0ZyILNep96QFQAcuN+lhlixZAoVCAYVCgcDAu69+bsi+RhMcB3R+Ejg0D9CozXNMIrJ8B2cDSk/gwf8AUMgdjQVTAA+uABw8gEMvyR0MkeGqr0l3MPaaDwSMkzsavaxduxYPPPAAnJyctOOmkydPmu6Ajt5AZIq0YPzFVaY7DhHpMtN8rSUbN27U5hqFQoHq6mrzBsD5GpFVYtGciCxT+QUg+x9A378CDu7Ga7a8HKGhoRg7dqx22/z58yGEQFhYWIuvN2Rfo3rgA+mu0rPyDkiJyEJc3gBcSZUWubRzNtth1Wo1+vXrh8jISLMd0yjsXIABn0nnLTdV7miIDHPkVcBeBfT5q9yR6GXv3r2YPHkyRowYgYKCApw9e9Y8Nxp0ehC4Lx44PB9Ql5r+eETtnYnma60xceJECCEwYcIE+YLgfI3I6rBoTkSW6ddPAWd/oNssozYrhIBGo4FGozFquybn0lmaCGZ9BIg2FjsRGd+JvwJdJgM+Q81+6DaZQwHAd7h0J9jxt+SOhEh/ZWeBi98A/T806x/I7sW6desghMCcOXPg6uqKbt264fLly+jTp4/pDx72HlBfBZxNNv2xiNo7E83X2izO14isDovmRGR5NGrgwkog5FnAxt6oTbu5ueHcuXPYunWrUds1i9DnpTs6ru+SOxIiklP+DqDkBNDzZbMf2t7eHidPnsS+ffvMfmyjuD8RKD4KXP9R7kiI9HNmGeAcBATFyB2J3i5fvgwA8PT0NP/BHToCITOAX5cBot78xydqL0w4X2vTOF8jsiosmhOR5bm2A6gpBEKeljsSy9KhJ+A5iM/qJGrvzn8JeEUCHcPljqTt6fg7oNNDwNnP5Y6EqGVCA1z4Ggj9I6CwlTsavdXXy1ys7v4CUHEJuLZL3jiIrBnna03jfI3IqrBoTkSW5/puoEMP6c4qIzJ0gZiVK1fq7K9QKJCfn6+zT1ZWFsaMGQOVSgVnZ2cMGzYMe/fuNWrcOnyjgII9pmufiCycAPJ3AoHGf2ZnUVERXn75ZXTr1g1KpRKBgYGIiorCihUrUFVVhc2bNzeZQxcsWKDddvuzzr/77jvt9k6dOmm335mLL168iEmTJsHd3R2enp4YO3Yszp07Z/SfTytwPJCfBkCY7hhExlB8FKgpAvzHtryvgQoKCvDSSy+hS5cucHBwgJeXF2JiYnD06NFG+2ZlZWHixInasc7AgQOxefNmREVFafvxzJkztX3722+/BQDtIqAPPvhgo36fnZ2NuLg4eHp6arcVFhYa54dz6y79u7bTOO0RUWMmmq81WLJkiTY3BAYGIjMzE8OHD4ebm5tec678/Hzzji1ux/kakdVg0ZyILE9hBtBpsNGbNXSBmMmTJ+Pll19GdHQ0bty4ASEEfH19td8vLy/HCy+8gNdffx25ubn46aefcOPGDTz22GP48UcTffTf6yHg5q/SJJqI2p/SX4DqfMDnMaM2m5+fjwEDBmD16tVYunQpCgsLcejQIQwdOhTPPPMMli9fjrFjxzaZQ9944w0IIeDi4qKzfdSoURBCIDxc9474O3Px3LlzMXfuXOTm5mLt2rXYuXMnJk+ebNSfT4fvcKD6GnAzy3THIDKG67sApRfg3tuozV69ehUDBgxASkoKPvvsM9y4cQO7du3CjRs3MHjwYOzfv1+779mzZzF48GAcPHgQ69evx/Xr1/Gf//wHS5cuxfHjx6FUKiGEwOeff96ob1dVVUEIgYyMjEbfS0hIwAsvvIDLly8jIyMDtrZGvpPe9zHeaU5kSiaarzWYP38+hBAICwtDSUkJ5syZgwULFiA/P1+vOdftY4t169Zh9+7dph1b3I7zNSKrwaI5EVmeiovSnQsyKikpwZgxY1BfX49t27bBw8Oj0T6lpaV4//338fDDD8PV1RURERFYuXIlamtrMWfOHNME5tYdgAAqc0zTPhFZtrKz0v9GLqK99tpruHDhApYuXYqxY8fCzc0NPj4+eOONNzBq1CijHutOM2fOxODBg+Hi4oKoqCiMGTMGmZmZxrvr9E6qW4sRlpnpjjOi1io/D6juB6AwarOvvfYaLl26hI8++gi///3v4erqit69e2PNmjUQQuDFF1/U7vv666+jpKQES5cuRXR0tHbfVatWoaKiotUxJCYmYujQoXB2dsagQYNQV1en84mUe6a6Xzp/RGQaZpyvVVRU4LPPPtOOFfSZc90+tnjssccwduxY044tbsf5GpHVYNGciCxPTRGglGHxqFuys7MxaNAg2NjY4JNPPmn27idHR0cMGjRIZ1vfvn3h7++PY8eO4erVq8YPruG81JhhwEdElqf6OmCvAmyURm12w4YNAIDRo0c3+t62bdswd+5cox7vdgMGDND5OihI+qh3Xl6eaQ5o6wjYu0l3mxNZsuoCwNHL6M1u3LgRNjY2GDtW97Evvr6+6N27Nw4dOoQrV64AkB6zBAAjR47U2dfLyws9e/ZsdQwDBw5s9Wv1ovQGagqk58ITkfGZcb7m4uKCBx54QGdbS3OuO8cWAQEBAEw4trgd52tEVoNFcyKyPPWVgK2TLIcuLi7GxIkTERgYiG3btmHlypXN7tvwHM47eXt7AwCuX79u/ADtbj3+oK71d3cRURtWX/lbHjCSmpoalJaWwtHREW5ubkZtWx8qlUrnawcHBwCARmPCYpedG1BXbrr2iYyhvhKwdTZqkw39XaPRQKVSNVq75fDhwwCAM2fOoKamBmVlZXB0dISrq2ujtpr6FJ6+7nyck9HZuQCiHqi/+/o1RNRKZpyvubu7N7n9bnOuO8cWNjZS6cukY4sGnK8RWQ07uQMgImrEwQOoLZbl0HZ2dkhPT4dKpcJDDz2EWbNmoUePHo3uVgCkx7M0pWHg1jCQM6raG9L/Dh2N3zYRWT6lp9GfkalUKqFSqVBaWoqysrJWF85tbGxQW1vbaHtJScm9hmhkQrr7S2n8O3iJjMqh42+/941EqVTC3d0d5eXlqKqqgp3d3aeDbm5uKCsrQ3l5eaPCuUluDjCWmkLAzln6R0TGZ8b5WlFREYQQjW5WMumc615wvkZkNXinORFZHmUn6SPJMnBzc0NAQABcXV2xadMmuLq6YuLEiU1+7K+8vBzHjh3T2XbixAnk5eUhLCwMfn5+xg+w4bwojfjcTyJqO5TegKbG6BPVxx9/HACwdevWRt/r378/5s2b12Ibfn5+yM3N1dmWn5+PnBwLe6ZnzQ1AUws4Wtgkm+hOjt4meYxQTEwM6urqsHfv3kbfW7RoEYKDg1FXVwfgt0c2NTympUF+fj5+/fVXo8dmNNXXpXxJRKZhxvladXU1MjMzdbaZfM51LzhfI7IaLJoTkeVR9QaKj8gdBbp06YL169ejoKAAMTExqKmp0fm+i4sLZs+ejZ9//hkVFRU4ePAgpk6dCgcHByxdutQ0Qd04LD3L2K2badonIsvm8QAABVCYYdRmP/jgA3Tt2hXz5s3Dli1bUFZWhitXruCFF17A1atX9SqajxgxAnl5efjHP/6B8vJynDt3DnPmzLG8O8AK9wNQAB5hckdCdHfu/YDiY0BdpVGb/eCDD9CtWzc8++yz2LZtG0pLS3Hjxg0sX74cf/vb37BkyRLtHejvv/8+OnbsiLlz5yItLQ3l5eU4efIknnnmGfj6+ho1LqMqyriVL4nIJMw4X1OpVHj99dexf/9+88257gXna0RWg0VzIrI8nR66VdQQRm1248aNUCgU+PbbbwEATk5OmDp1KtasWQOFQoFjx44hNzcXCoUCn3zyCTIyMjB06FCo1WpkZGTA0dFR+8zPY8eOwd3dHR999BFee+01+Pr64tFHH4WHhwd27tyJIUOGGDV2rcL9gGeE0RcBJKI2wtEbcO8DXNth1GZ9fX2RmZmJSZMm4cUXX4SnpycGDhyI4uJi7N69G8HBwS22sWDBAsycORPvv/8+vL29MWPGDLz66qvw9fVFUVERFAoFkpKSkJGR0SgXv/HGGwAAhUKBRYsWAZDucL9zoUKjuLYT8OjHx7OQ5fMZJn0qonC/UZv19vbGgQMHMHHiRMyePVu7qOf//vc/fPvtt4iLi9Pu261bN+zfvx8DBgzAE088AR8fHyQkJOC1115D165ddRZLb2qcpVAokJGR0WS/b2pdGKMQGuDaj4DPUNO0T0Qmm681xdXVFZ9++ineeecd+Pn5NTnnkn1scTvO14ishkIIYfosR0RkiJITwNZ+QPRuwCtS7mgsh6gDNnYGus0E+r0jdzREJJejrwEXVwITLgAK8y9PM27cOGzduhU1NTUtPg/Z4mjUwKauQNengbD35I6GqGVb+wGeA4FBn8sdSSM9e/ZEVVUVLl26JHcouvK2AbvGAGNPAx16yB0NkXUy03ztgQceQGFhIa5cuWKyYxgV52skA4VCgbVr1+r80ZuMg3eaE5Hlce8LePQHzn0pdySWJW8bUHUVCJkudyREJKfQ54GqfCDn/5nlcH369MHFixe1X+fm5iI4OLjtFcwBIGctUHUNCP2j3JEQ6Sf0BeDiKqMvAKyv/Px8dOzYEWq1Wmf7xYsXce7cOTz22GOyxHVX2f8H+A5nwZzIlDhfaxrna0RWhUVzIrJM9828VdzIkzsSy5H1CeD7GODK5+MRtWsuwUDQ48Cp96Q7p83gww8/RHl5OTZt2oSjR4/ij39sg0VnTS1w6gMgOBZwDpI7GiL9dJ0K2DoCWX+XLYTi4mIkJCTg8uXLqKysxIEDBzBp0iR06NABb775pmxxNakoE8j/HujxktyREFk/ztca43yNyKqwaE5ElinkWel5s8f/KnckliFvm/Qc3r5vyx0JEVmC/ouB8vNA1scmP9QXX3yBU6dOwc/PD6+88gref/99zJ8/3+THNbrTS4DyC0DYArkjIdKfnav0u//034GbWWY/vK+vL9LT01FSUqJ9jvD48eMRGhqKAwcOICQkxOwxNUtogIMvAl4PAwEmfmYxEZl0vrZkyZJGa041PKPcYnG+RmR1+ExzIrJcF1cC+2cAI/ZJz/Nsr+qrgO8iALdQ4NGNckdDRJbi1PvS3eYjMqSPSVPzSo4D3w8G+rwJ3J8kdzREhhH10jjAzhUYvhOwsZc7Ist0+u/AsdeA0UcAVW+5oyFqHzhfk3C+RjLiM81Nh3eaE5Hl6vIU4DcK2DsFUN+UOxr5HH5F+thj+CdyR0JElqTXq0DHAcBPE4CaQrmjsVw1BcCPEwDPQUDPV+SOhshwCltg8FdA8RHgSBv8lIc55O8AjiYBYe+zYE5kTpyvSThfI7JKLJoTkQVTAA9+DtSVAT/PlD52295cXAWc+RcwMBlw6SJ3NERkSWzsgUfWAUIAPz0OqMvkjsjyqG8CP04EFDZA5DreoUttl3tf4MEvgexPgTOfyR2NZSk5CeydBAQ/AfTiHxWIzIvzNc7XiKwXi+ZEZNkcfYGH1wJXNgGH5sodjXld/R7IeAbo9Yq0cB0R0Z2UXsDQzUDZGeCHkUBtidwRWY7aYmDnCKDiAjB0C6D0lDsionsTHAeEvQdkzgbO/FPuaCxDyQlgx2OAqg8w6Au5oyFqnzhf43yNyEqxaE5Els9nKPDwN9KdVUcTAbSDpRjy04HdfwA6T5IW/CMiao6qNxD1I1CZA+wYBlRclDsi+ZWfB9KHSh+VjvoR6NBT7oiIjKP3a7cK53+S1jRoD2Oi5lzfjfq0xwD33tIfxuyc5Y6IqP3ifE3uaIjIBFg0J6K2IegPwOAVQNbHwP6nAY1a7ohM5+I3wK4xQOD4W3dNKeSOiIgsXYceQNRuAEJaiOrqdrkjkk/eNuC7AdJzoKN3S4tyEVmT3q8BEZ8Cx98G9kwC6irkjsj8zvwT2DkcXxwIQs8XcrHo7//A9evX5Y6KqH3jfI2IrAyL5kTUdnSZCgzZDFzZKH0UtyJH7oiMS6MGjvwZ2DcN6PES8NBKPn+XiPTn2hWI3ictyLXr98Dhee2rmFZXDhyaA/w4FggYC4zYC7h0ljsqItPo/ifgsTTg2g/SH8oK98sdkXnUFEh/KMj8E9DnDTz09H8x7LHh+OCDDxAUFIS4uDhs374dGk07fK4ykSXgfI2IrAiL5kTUtviNkIpCtTeAbf2By/9P7oiMo+wskPaI9JHGB78E+n8I3rFARAazc5YmcIO+AM7/F9jaF7j6ndxRmd7V74AtfYELK4EHVwCD/wvYOskdFZFp+QwFRh+W/jiU9ghwZL70xyNrdWktsKUPUJQBDPsO6PMW+vTpi3/+85/Iz8/HypUrUVxcjNGjRyM4OBhJSUm4cOGC3FETtT+crxGRlWDRnIjaHvc+wMhMIPgPwO4ngJ8mtN1n+NZXAyfekQpbmmpg1EEgZIbcURFRWxcyAxj7C9AxAvhhNLAzGrhxUO6ojK8oE9gZJf2MngOln7nrNLmjIjIf5yBg2DZg4HLg3BfAplDgbDIg6uSOzHgK9wFpkcDeyUDgBOD3J6Si3G0cHR0RGxuLtLQ0ZGVlYerUqVixYgXuu+8+REdHY926daitrZXpByBqhzhfIyIrwKI5EbVNds7AwGRg+E7g5hlgS2/g2OtATaHckelH1AMXvpLumMr6O9BvgTSw5GJ1RGQsjr5AZAoQ9ZP0mJbvBgK7Y4CCPXJHdu+u/yhNwLcPkiazUT8BkWsBRx+5IyOSgQLo9hww7gzQOQ44+KL0yYtzXwKaGrmDa72CPVI///5hwMYBGHVAGvvZd7jry7p3746FCxciNzcX27dvh4eHB6ZMmQJfX18kJCTg+PHjZvoBiNo5zteIqI1TCCHawbLGRGTVNGrg10+BXxYBdZVA99nSsz6dA+WOrLH6KuDiauCXhUD5BemOyH7vAs4BckdGRNbuyrdSnizcL92B3uNFICgGsHOVOzL9qMuAy+uB7E+B4iNAp4eA3klAwDi5IyOyLGVngVMLpPGGQ0egx2yg64y2Mdaor5KehZy1FCj6WernfV4H/MfcU7N5eXn4+uuvkZycjPPnzyM8PBzx8fGYMmUKXF3bSA4kass4XyMyGYVCgbVr1yIuLk7uUKwOi+ZEZD3qKoAz/wRO/11aKCpgDHBfPOA7Qv4FWkpOAudvPWO4rgLoMgXo8wbg2k3euIio/Sn6Gcj6BLj8P8DGDgiYIOUk3yjA1lHu6HTVVwH56cDFb4Arm6S7voJigJ7zpMexEFHzqvKA7P8Dzv4bUJcCvsOl4k/A+Bbv1jYrUQ9c3w1cXAnkrJfGSYETgF6vAJ0GG/VQGo0GO3fuxFdffYX169fD3t4eTz75JKZNm4bIyEijHouImsD5GpHRsWhuOiyaE5H10dRKdymd+RdwbRfg4AEEjgMCYwDfx8xzV6Wol+6EvLxBKkzdzAJcQ4D7ZgEhz/ARAkQkv9obwKUUqSBdsBewcwK8hwL+o6UCeoceMP8CV0LKl/npQN42KYfXVwPekUCXp4DgWOnOWSLSn6YGyN0MXPha6lcQgFekdPe230hAdT+gMPNTO6uuAtd2ArlbgKvbpXzk0R/oOh3oMtks46Ti4mKsW7cOy5Ytw/Hjx3H//fdj+vTpeO6559CpUyeTH5+oXeN8jchoWDQ3HRbNici6lV+QBkGX/wcUZQCwATr+DvB+BPAcJC1S4xYKKOzu7TiVuUDpKeDGIekZnAV7APVNwKWLdFdkUIx0t5S5J6VERPqovCIV065+JxWs1TcBB3fpbm7PQYB7P6mI3qE7YKM0zjHrq4GyX4GbvwIlx4CiA0Dhz9IdsfYqqXDvPwrwG82PRBMZS+0NqUjdUKyuKZT6m+dAoNODgEeY9Lxet1DpOeL3TAAVl4GybOkuzqKfpUdEVeRI7Xs/Cvj/Xrrb1K27EY7XOocOHUJycjJWrVoFtVqN8ePHIz4+HsOHD4dCYe4/HhK1M5yvEd0TFs1Nh0VzImo/qq9Ji8dd3w1c3wWUnpbuMLBxkApBzsGAky/gFCh9bNneTRqc2btJd2nVVUr/15ZKbVVeAarzgZvZQG2xdAznAOnuLe9HAa9HpUEeEVFbolFLd14V/QwUHpCK2eVnAaGRJpIunaVnkDr6SIuNOnoBdm6AnQsAhVRsB4DaEgACqCuX/lUXSDmzIX9WXLrVpq300edOg34r0nfsf++TYyK6O1EPlByXitiFGdK/8nO3+qUd4NoVcPKXxjZKL8DRWxoT2SilsZOdi5Qv6sql16hLpfFQdT5QfV16PEzZWekxB4DURkNxvtNgqc9b2JoKZWVl2LBhA77++mukp6cjNDQUU6ZMwbPPPovg4GC5wyOyfpyvERmMRXPTYdGciNqv+mrg5mnpjoPSLKDqClCVD1TlSncdqMsAjRrpR8vRt7M9fDxdpef92rkBTj6AU4A0aHMLBVS9AVUfQOkp909FRGR8mhrg5hnpbtGbv0qPVmgogFdfl4pitwpnJ86XAgD6dnMHoJAmsrbOUsHN0Vcqtjv7S3eVdugBuN1nvLvXieje1FdLxaWybOn/qnyp+F19XXr+cF25tI+mBulHK38bHylspQKWg/utfu4tFdxdQ6Q71zv0bHNjpNOnT+O///0vvvjiCxQXF2PYsGGIj4/H448/Djs7/lGPyCw4XyNqEYvm3SW7LwAAIABJREFUpsOiORFRC/hLiIhIfw25MiUlReZIiMiU2sv4qKamBps2bUJycjJ27NgBX19fTJ8+HbNmzUK3blwgkMgStJd8RNQUXv+mw4c1ERERERERETVBqVQiNjYWaWlpuHTpEubMmYM1a9YgNDQUkZGRSE5ORmVlpdxhEhERkZGxaE5ERERERETUgqCgICQmJuL8+fP4/vvv4e/vj9mzZyMgIAAJCQk4evSo3CESERGRkbBoTkRERERERKQnGxsbREVFISUlBTk5OUhKSsLOnTvRv39/REREIDk5GWVlZXKHSURERPeARXMiIiIiIiKiVvD19UViYiLOnDmDgwcPIjw8HPPmzYO3tzfi4uKQnp4OLiNGRETU9rBoTkRERERERHSPwsPDsXz5cuTl5WHp0qU4e/YsoqOjcf/992PRokUoKCiQO0QiIiLSE4vmREREREREREaiUqkQHx+Pw4cP4+DBgxgxYgQWL16MwMBAxMXFITU1FfX19XKHSURERHfBojkRERERERGRCYSHh2Pp0qXIzc3FypUrUVxcjAkTJqBz585ISkrCxYsX5Q6RiIiImsCiOREREREREZEJOTo6IjY2FmlpaTh9+jSmTp2K//znP+jWrRuio6Oxbt06qNVqucMkIiKiW1g0JyIiIiIiIjKTHj16YOHChbh8+TI2btwIDw8PTJkyBUFBQZgzZw5OnDghd4hERETtHovmRERERERERGbm4OCAcePGISUlBRcvXsS8efOQmpqKfv36ISIiAsnJyaioqJA7TCIionaJRXMiIiIiIiIiGQUEBCAxMRFnz55FWloaQkJC8OKLL8Lf3x8JCQnYs2eP3CESERG1KyyaExEREREREVkAGxsbREVFISUlBfn5+fjwww+RkZGBRx55BL1798aiRYtQVFQkd5hERERWj0VzIiIiIiIiIgvj4eGB+Ph4HDt2DAcPHkRkZCQWLFiAwMBAxMXFIT09HUIIucMkIiKySiyaExEREREREVmw8PBwLF++HLm5uVi6dCny8vIQHR2NHj164O2338bly5flDpGIiMiqsGhORERERERE1AZ06NAB8fHx2LNnD06dOoWYmBgsW7YMXbt2RXR0NNatW4e6ujq5wyQiImrzWDQnIiIiIiIiamPuv/9+LFy4EFeuXMHq1asBAJMmTULnzp2RlJSE8+fPyxwhERFR28WiOREREREREVEbpVQqERsbi7S0NGRnZ2PWrFlYvXo1QkNDERkZieTkZFRVVckdJhERUZvCojkRERERERGRFQgNDcXbb7+N8+fPY/v27fD398ef/vQn+Pv7IyEhAceOHZM7RCIiojaBRXMiIiIiIiIiK2Jra4uoqCikpKQgJycHSUlJ2LFjBx544AFEREQgOTkZ5eXlcodJRERksVg0JyIiIiIiIrJSfn5+SExMxJkzZ7B7926Eh4dj3rx58Pb2RlxcHNLT0+UOkYiIyOKwaE5ERERERERk5RQKBSIjI7F8+XLk5ubik08+wZkzZxAdHY1evXph0aJFKCgokDtMIiIii8CiOREREREREVE74u7ujvj4eBw5cgQHDx7Eo48+ivfeew9BQUGIi4tDamoq6uvr5Q6TiIhINiyaExEREREREbVT4eHhWL58Oa5fv46vv/4axcXFmDBhArp06YKkpCRcunRJ7hCJiIjMjkVzIiIZLVmyBAqFAgqFAoGBgXKHQ0RErdRcPmeeJ7Iu1tzXHR0dERsbi7S0NPzyyy946qmn8J///AchISGIjo7GunXroFar5Q6TbmPN1yO1jO8/kWmxaE5EJKP58+dDCIGwsDC9X6NWq9GvXz9ERkaaMDIiIjJEc/m8NXmeiCxXe+nrPXv2xMKFC3H58mWsWbMGjo6OmDx5MoKDgzFnzhycPHlS7hAJ7ed6pKbx/ScyLRbNiYjaII1GA41GY5Zjubq6skBPRG0WcxhR+8C+bhoODg6IjY1FamoqLl26hLlz52LTpk3o27cvIiIikJycjIqKCrnDtDi8Hts3vv9E1oFFcyKiNsbe3h4nT57Evn375A6FiIiIiNqJgIAAJCYm4ty5c0hLS0NISAhmz56NgIAAJCQk4PDhw3KHSEREZDQsmhMRERERERGRXmxsbBAVFYWUlBRcu3YNixcvxv79+xEeHo7evXtj0aJFuHHjhtxhEhER3RMWzYmI9FRTU4O33noLPXv2hLOzMzp27Ihx48Zh06ZNqK+vBwAsWLBAu+jK7R/J++6777TbO3Xq1OwxsrKyMGbMGKhUKjg7O2PYsGHYu3ev9vubN2/WtqNQKFBdXa3z+oKCArz00kvo0qULHBwc4OXlhZiYGBw9erTRsYqKivDyyy+jW7duUCqVCAwMRFRUFFasWIGqqirtAjIVFRXYu3ev9ph2dnb3eiqJqJ1oKc80tZ+DgwM8PDwwevRo/PDDD9p9Nm7cqJP/Ll68iEmTJsHd3R2enp4YO3Yszp07p92/pRx2Z3vZ2dmIi4uDp6endlthYaHe8bWWPnnbkFiJ5MC+3jJr7eseHh6Ij4/H8ePHcfDgQURGRuLdd99FQEAA4uLikJ6eDiGEWWPi9dgya70eAb7/+rDm95/IqAQREd0VALF27Voxc+ZMoVKpxPfffy8qKytFfn6+mD9/vgAgfvjhB53XuLi4iIcffrhRW+Hh4cLT07PR9rCwMKFSqcSwYcPEnj17RFlZmcjMzBT9+vUTDg4OYteuXTr7T5gwQQAQVVVV2m15eXmic+fOwsfHR2zZskWUlZWJkydPiiFDhghHR0exb98+7b5Xr14VXbt2Fb6+viI1NVXcvHlT5Ofni3fffVcAEB9//HGLPwsRUVNiY2NFbGys3nmmYT8fHx+RmpoqSktLRXZ2toiJiREKhUL8+9//1mm/If9NmDBB7Nu3T5SXl4u0tDTh5OQkBgwY0CielnJYQ3tDhgwRP/zwg6ioqBAZGRnC1tZWFBQUGBxfWFiYCAgIaHScprYbkrf1iZXInBrGR+zrosXt7a2vl5aWiuXLl4uHH35YABDdu3cXCxcuFPn5+SY/Nq9H0eJ2a7wemY/a9/vf3jVc/2R8LJoTEbWg4ZdQ165dxUMPPdTo+927dzdK0RyA2L9/v87248ePCwAiLCxMZ3tTRfOnn35aABDffPONzr5Xr14VSqVShIeHa7fNmDGj2V+uo0aNYtGciFqtoWiub55p2G/16tU6+1RXVwt/f3/h5OSkU2hpyH+pqak6+z/xxBMCQKMJnL4T161btzb5fUPjM2Tiakje1idWInNq6N/s67rY13WdPHlSJCYmCk9PT2FrayuioqJESkqKUKvVJjker0dd7eV6ZD5q3+9/e8eiuenw8SxERHoaNWoU9u3bh/j4eGRkZGgfyZKdnY2hQ4fec/uOjo4YNGiQzra+ffvC398fx44dw9WrV+/6+o0bN8LGxgZjx47V2e7r64vevXvj0KFDuHLlCgBgw4YNAIDRo0c3amfbtm2YO3fuvfwoRER655mG/caMGaOzj1KpxPDhw1FVVYXt27c3amPAgAE6XwcFBQEA8vLyWhXvwIEDm9ze2vj0YUje1idWIjmwr7esPff13r17Y+HChcjNzcXq1asBAJMmTULnzp2RlJSE8+fPG/V4vB5bZs3XI9//llnz+09kbCyaExHpadmyZfjqq69w/vx5DB8+HB06dMCoUaO0g5p71fB8uDt5e3sDAK5fv97sa2tqalBaWgqNRgOVSqXz/DmFQoHDhw8DAM6cOaPd19HREW5ubkaJnYjodhqNRq8801I+8vHxAQDk5+c3+p5KpdL52sHBQXvs1nBxcTFqfC0xJG/rEyuRHNRqNft6C9jXJUqlErGxsUhLS0N2djZmzZqFVatWITQ0FNHR0fjqq690njfdGvqOcXk9Wuf1yHzUMmt+/4lMgUVzIiI9KRQKTJs2Denp6SgpKcHGjRshhEBMTAw++ugjnX1tbGxQW1vbqI2SkpJm2y8tLW1ye0OxvKF43hSlUgl3d3fY2dlBrVZDSI/favRv2LBhUCqVUKlUqK6uRllZmV4/NxGRIWxsbPTKMy3lo2vXrgGQ7n5qrXvJYaaMz5C8TWSp7O3t2df1aJt9XVdoaCjefvttXLhwAdu3b4eHhweee+45BAQEICEhAcePH29Vu/qOcXk9Wuf1yHykX9vW+v4TmQKL5kREenJ3d0dWVhYAaVAWHR2tXVV8y5YtOvv6+fkhNzdXZ1t+fj5ycnKabb+8vBzHjh3T2XbixAnk5eUhLCwMfn5+d40vJiYGdXV12Lt3b6PvLVq0CMHBwairqwMAPP744wCArVu3Ntq3f//+mDdvnvZrZ2dnnT8A9OjRA8nJyXeNhYhI3zzTsN+debSmpgY7duyAk5MTRo4c2eo47jWHmTI+Q/I2kaViX28Z+3rTbG1tERUVhZSUFFy6dAmJiYlIT09HWFgYIiIikJycjPLycoPa5PXYMmu+Hvn+t8ya338iozPDc9OJiNo03FpYQ6VSiSFDhohjx46J6upqce3aNfH2228LAGLBggU6r5k9e7YAID799FNRVlYmzp49K+Li4kRAQECzC4G6uLiIyMhIkZGRIcrLy0VmZqbo16+fcHBwELt27dLZv6mFQK9duya6desmQkJCxNatW0VJSYkoKioS//rXv4Szs7PO4iANK7L7+fmJzZs3i5s3b4rLly+L559/Xvj4+IhLly5p9x01apRQqVQiJydH7Nu3T9jZ2YlffvnFWKeXiKxMw0Kg+uaZhv18fHxEamqquHnzpsjOzhYxMTFCoVCI5ORknfabyn9CCJGYmCgAiCNHjuhsbymHNddeA0PjM2QxLkPytj6xEplTw/iIfV20uJ19XX/19fVi9+7dIj4+Xjg5OQk3Nzcxbdo0kZaWptfreT2KFrdb4/XIfNS+3//2DlwI1GRYNCciakHDL6GjR4+KhIQE0atXL+Hs7Cw6duwoHnzwQfHvf/9baDQandeUlJSImTNnCj8/P+Hk5CQiIyNFZmamCA8PFwAEAJGYmCg+/PBD7dcBAQHiwIEDYtiwYcLV1VU4OTmJIUOGiD179jSKqbnBS1FRkXj55ZdFSEiIsLe3F15eXmLEiBFNTjQKCwvF3LlzRdeuXYW9vb3w8/MTTz75pPj111919svKyhKPPPKIcHFxEUFBQWLZsmVGOKtEZK0aiuZC6J9n7txPpVKJkSNHih07dmj32b9/vzZfNvz7y1/+IoQQjbaPGTNG+7rmclhT7TV3P4k+8d2ez2+Pr7ntDfTJ24bESmQut0/S2dfZ102huLhYLF++XISFhQkAolevXmLhwoWioKDgrq/j9dj+rkfmo/b9/rd3LJqbjkIIIUBERM1SKBRYu3Yt4uLi5A5Fa9y4cdi6dStqampgZ2cndzhERFoNuTIlJUXmSIjIlCxxfETW69ChQ0hOTsbq1atRW1uL8ePHIz4+HsOHD+f6O8R8RO0ar3/T4TPNiYjagD59+uDixYvar3NzcxEcHMyCORERERFZvfDwcCxfvhzXrl3D119/jeLiYkRHR6Nz585ISkrCpUuX5A6RiIisDIvmRERtxIcffojy8nJs2rQJR48exR//+Ee5QyIiIiIiMhsnJyfExsYiLS0Np0+fxpQpU/Dll18iJCQE0dHRWLduHdRqtdxhEhGRFWDRnIioDfjiiy9w6tQp+Pn54ZVXXsH777+P+fPnyx0WEREREZEsevbsiYULF+Ly5ctYs2YNHB0dMXnyZAQHByMpKQlnz56VO0QiImrDWDQnImoDBg0ahF27dqGsrAxnzpxBUlISbG1t5Q6LiIiIiEhWSqUSsbGxSE1NxcWLFzF37lysWbMGoaGhiIiIQHJyMiorK+UOk4iI2hgWzYmIiIiIiIiozQsMDERiYiLOnz+PtLQ0hISEYPbs2fD390dCQgKOHDkid4hERNRGsGhORERERERERFbDxsYGUVFRSElJQU5ODt555x3s27cPv/vd7xAREYGlS5fixo0bcodJREQWjEVzIiIiIiIiIrJKvr6+mDNnDk6cOIGDBw8iPDwcf/nLXxAQEIC4uDikp6dDCCF3mEREZGFYNCciIiIiIiIiqxceHo7ly5cjNzcXS5cuxblz5xAdHY1evXph0aJFuH79utwhEhGRhWDRnIiIiIiIiIjaDZVKhfj4eBw6dAgnT57ExIkTsXjxYgQFBWHcuHFYt24d6urq5A6TiIhkxKI5EREREREREbVLvXv3xsKFC5Gbm4uVK1eiuroakyZNQpcuXZCUlIQLFy7IHSIREcmARXMiIiIiIiIiatccHR0RGxuLtLQ0ZGVlYerUqVixYgXuu+8+REdHY926daitrZU7TCIiMhMWzYmIiIiIiIiIbunevbv27vPt27fDw8MDU6ZMga+vLxISEnD8+HG5QyQiIhNj0ZyIiIiIiIiI6A62traIiopCSkoKLl26hMTERKSnpyMsLAwRERFITk5GeXm53GESEZEJsGhORERERERERHQX/v7+SExMxJkzZ5CWlob7778fc+fORUBAABISErBnzx65QyQiIiOykzsAIiJLsmrVqibvFklPT0dJSYnOtokTJ8Lb29tcoRERWZyMjIxGH1E/f/48ACA5OVlne79+/fDggw+aLTYiMh6Oj4h+Y2Njg6ioKERFRWHp0qVYt24dPvvsMyQnJ+P+++/H9OnT8dxzz6FTp05yh2qVmI+IyFwUQgghdxBERJbi6aefxldffQV7e3vttoY0qVAoAAD19fVwcXFBQUEBlEqlLHESEVmC1NRUjB8/Hra2trCxkT7AeGfO1Gg0qK+vx6ZNmzBu3DjZYiWi1uP4iKhlhw4dQnJyMlatWgW1Wo3x48cjPj4ew4cP1/YTunfMR0S6FAoF1q5di7i4OLlDsTp8PAsR0W0mT54MAFCr1dp/dXV1qKur035ta2uL2NhYDsCIqN0bNWoUOnTogPr6+mZzZn19Pdzc3DBy5Ei5wyWiVuL4iKhl4eHhWL58OfLy8pCcnIzi4mJER0ejR48eePvtt5GTkyN3iFaB+YiIzIVFcyKi20RFRaFjx4533UetVmPKlClmioiIyHLZ29vjySefhIODw133mTx58l33ISLLxvERkf7c3Nwwffp0pKWl4ZdffkFMTAyWLVuGkJAQREdHY926dairq5M7zDaL+YiIzIVFcyKi29jZ2WHy5Mk6H/e7k6enJ4YOHWq+oIiILNjkyZNRW1vb7Pc5cSVq+zg+ImqdXr16YeHChbhy5QpWr14NAJg0aRKCg4ORlJSEc+fOGdzmiRMnjB1mm8J8RETmwqI5EdEdJk+eDLVa3eT3HBwcMG3aNNja2po5KiIiy/Too4/Cx8en2e97eXnhkUceMWNERGQKHB8RtZ5SqURsbCzS0tJw6dIlzJkzB2vWrEFoaCgiIyORnJyMysrKFts5cuQIIiIisGrVKjNEbbmYj4jIHFg0JyK6w0MPPQR/f/8mv1dbW6t9jh4REQE2NjaYOnVqk49fcXBwwNNPP61dJJSI2i6Oj4iMIygoCImJiTh//jy+//57+Pv7Y/bs2QgICEBCQgKOHj3a7Gs///xz1NXV4amnnsLf/vY37QKY7Q3zERGZA2cwRER3UCgUmDZtWpMf+QsKCsKAAQNkiIqIyHI194gWTlyJrAfHR0TGZWNjg6ioKKSkpCAnJwdJSUnYuXMn+vfvj4iICCQnJ6OsrEy7f1VVFb7++mtoNBoAwDvvvINJkyahurparh9BNsxHRGQOLJoTETWhqY/8NdwxqVAoZIqKiMgyhYeHIyQkpNH2zp0743e/+50MERGRKXB8RGQavr6+SExMxJkzZ3Dw4EGEh4dj3rx58Pb2RlxcHNLT05GSkoKKigrtazQaDTZs2IAhQ4agoKBAxujlwXxERKbGojkRURPCwsLQvXt3nW21tbV48sknZYqIiMiy3XnHl4ODA5555hkZIyIiY+P4iMj0wsPDsXz5cly5cgWLFy9GdnY2oqOj8dZbbzUqBtfV1eHw4cOIiIhAdna2TBHLg/mIiEyNRXMiombcWQDq1asXevfuLWNERESWa+rUqTp3fHHiSmSdOD4iMg8PDw+8+OKLOHbsGNavX4+cnBzU19c32q+urg55eXkYOHAgfvzxRxkilQ/zERGZEovmRETNmDJlCurq6gAA9vb2ePrpp2WOiIjIct13333o168fFAoFFAoF+vXrhx49esgdFhEZGcdHROb3888/N/n87gZ1dXUoLy9HdHQ0Vq5cacbI5MV8RESmxKI5EVEzQkJC0L9/fygUCtTV1fGOSSKiFkyfPh22trawtbXF9OnT5Q6HiEyA4yMi86qrq8OXX37Z6Pndd9JoNFCr1Zg2bRrefvttCCHMFKF8mI+IyJRYNCciuovp06dDCIGBAweic+fOcodDRGTRJk+eDI1Gg/r6ekyaNEnucIjIRDg+IjKfTZs2oaioyKDXvPvuu5g+fTpqa2tNFJXlYD4iIlOxkzsAIquwJ1buCMhEJnWtxis2Ckx7qJbvszXr+TLQabDcURDAftbG+QMY3NsDABB4cR5wUdZw6F5FrjNNu4X7gayPTNM2mQXHR1ak02BpHGQqvD7u2RdL9ui9r62NAjYKoE6jwcqVK5Fzcjs2vDcYHTs4mDBCeTEfkVlx3tiusGhOZAw564FODwLOgXJHQkbm29ERURHeeGJogNyhkKnkrAeCYwFw8GMRmE/bvGkjO0OhkDsKuieVV4DCDBO2f/lW7n3CdMcgk+L4yEqYsp834O/1e7ZlcSQAoLisFhoNUFqhRl29BmWVdahVa1BRXY+qmnpU19ajolraVlZZh7p6gdIKNTbuzsMzv+9itb+bmY/IbDhvbHdYNCcylp7zgOA4uaMgE/h05Rn4hIbKHQaZyiornUG0ZcynbdoTvW59hNzTU95AqPVyUoA9Zni8jqnuZCez4PjICpjrrlz+XjcKj1v/87drY8xHZBacN7Y7LJoTEbU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+ "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tm.draw_jupyter()" + ] + }, + { + "cell_type": "markdown", + "id": "fe1a8c56-19ea-4636-8d7d-0ca4420af49e", + "metadata": {}, + "source": [ + "## We then convert an SBML Qual document from the Covid-19 disease map\n", + "\n", + "The specific file is here: https://git-r3lab.uni.lu/covid/models/-/blob/master/Executable%20Modules/SBML_qual_build/sbml/Orf3a_stable.sbml?ref_type=heads\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1013581c-2a26-4f0c-b6e1-181fecd2b0c2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_text = requests.get(MODEL_URL).text\n", + "tm = template_model_from_sbml_qual_string(model_text)\n", + "tm.draw_jupyter()" + ] + }, + { + "cell_type": "markdown", + "id": "e8fb68bf-2fb0-4168-a8c5-345062e638e9", + "metadata": {}, + "source": [ + "## We identify all concepts and their identifiers from the model that is apart of the Covid-19 disease map\n", + "\n", + "Qualitative species' annotations have been provided for most of the species' in the model" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "272b8133-3f48-4bba-ab67-7375bcca0483", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "csa2 | {'hgnc': '20266'}\n", + "csa4 | {'hgnc': '1974'}\n", + "csa8 | {'hgnc': '7562'}\n", + "csa7 | {'hgnc': '7794'}\n", + "csa3 | {'hgnc': '5991'}\n", + "csa10 | {'hgnc': '6859'}\n", + "csa13 | {'hgnc': '11312'}\n", + "csa17 | {'hgnc': '15631'}\n", + "csa11 | {'hgnc': '10059'}\n", + "csa12 | {'hgnc': '1974'}\n", + "csa15 | {'hgnc': '660'}\n", + "csa21 | {}\n", + "sa1 | {}\n", + "sa3 | {'hgnc': '30834'}\n", + "sa10 | {'hgnc': '16400'}\n", + "sa14 | {'pubmed': '32172672'}\n", + "sa11 | {'hgnc': '12033'}\n", + "sa25 | {'hgnc': '1499'}\n", + "sa38 | {'hgnc': '12036'}\n", + "sa41 | {}\n", + "sa42 | {}\n", + "sa48 | {'hgnc': '18348'}\n", + "sa49 | {'hgnc': '7562'}\n", + "sa50 | {'hgnc': '10059'}\n", + "sa56 | {'hgnc': '16379'}\n", + "sa65 | {'hgnc': '7797'}\n", + "sa67 | {'hgnc': '17274'}\n", + "sa70 | {'hgnc': '660'}\n", + "sa74 | {'hgnc': '16288'}\n", + "sa75 | {'hgnc': '1144'}\n", + "sa76 | {'hgnc': '10065'}\n", + "sa77 | {'hgnc': '29938'}\n", + "sa81 | {'hgnc': '7794'}\n", + "sa34 | {'uniprot': 'P0DTC2'}\n", + "sa83 | {'ncbiprotein': '1796318600'}\n", + "sa87 | {'hgnc': '9075'}\n", + "sa88 | {'hgnc': '5434'}\n", + "sa92 | {'hgnc': '5992'}\n", + "sa93 | {'hgnc': '11849'}\n", + "sa132 | {'ncbiprotein': 'BCD58760'}\n", + "sa141 | {}\n", + "sa142 | {}\n" + ] + } + ], + "source": [ + "for initial_name, initial in tm.initials.items():\n", + " print(f\"{initial_name} | {initial.concept.identifiers}\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From d4e7d4a0b5a86a095e055d6a1cca36e00c08d313 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Mon, 22 Apr 2024 10:26:41 -0400 Subject: [PATCH 32/44] Update sorting method based on prefix and identifier --- mira/sources/sbml/qual_processor.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/mira/sources/sbml/qual_processor.py b/mira/sources/sbml/qual_processor.py index 0d4f13742..ed2124bf9 100644 --- a/mira/sources/sbml/qual_processor.py +++ b/mira/sources/sbml/qual_processor.py @@ -366,7 +366,14 @@ def _extract_concept(species, units=None, model_id=None): # involved. Deterministically choose the CURIE to use as the identifier for the concept by # sorting the keys of the identifiers dictionary (prefix) alphabetically - all_identifiers = dict(sorted(dict(identifiers_curie_list).items())) + # Sort the curie by prefix and then by the identifier + all_identifiers = dict( + sorted( + identifiers_curie_list, + reverse=True, + key=lambda curie_tuple: (curie_tuple[0], curie_tuple[1]), + ) + ) if all_identifiers: chosen_key = next(iter(all_identifiers)) From 8455864269f4d37fcd2b8c03250cd0a7d686b7a9 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Mon, 22 Apr 2024 10:29:10 -0400 Subject: [PATCH 33/44] Rerun notebook with updated concept names --- notebooks/SBML Qual Demo.ipynb | 92 +++++++++++++++++----------------- 1 file changed, 46 insertions(+), 46 deletions(-) diff --git a/notebooks/SBML Qual Demo.ipynb b/notebooks/SBML Qual Demo.ipynb index 23814076d..e216a632d 100644 --- a/notebooks/SBML Qual Demo.ipynb +++ b/notebooks/SBML Qual Demo.ipynb @@ -2,7 +2,7 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2mk5aedJ2SJv/T5ofIX35e+n0Yemml6VBCVKfLdJvptjjdVW5SF+yF2CI6GF/3gMOSr/7QWoySjq6RFrVRVrS0h6DzE01nbT80R9doe644w45HA5Nnjy5xP0FBQWaPn26fvOb38jf319BQUHq1q2bVq9eXclJDaI/GgAAAAAAAKhQVbwHHwAAoJrKPm4PjK7pLtW+Wuq3Q2r1F8npYzoZCt18882mI1SuqL5Sv+1Syz9L2/4qLW8jJf7PdCq3cLZQPzMz03ASAMBlWfnSTy9LcS2l5K3SbXFSl/n2JDVckUcffVQPP/ywBgwYoJ07d+rUqVN699139f3336tNmzZauHCh6YjuLaCxdMtC6dbF0qlN9oTk3a9IVoHpZAAAAAAAoDKk77KLtBc2lLY/J0X0lHpvku74WWr9rFTnOtMJK5ZPmNRsrNRjnTQg3h4PTVhjL1bweU/76euWy3TK8me5pCOf2X9j3PX2k9av+3/SgENS97VSs/vt96Y6q9NaumGyfa332ihFdJe2//38Yg3pu0wn/PXoj65wc+bM0eLFiy+6v6CgQL///e/12GOP6b777tPhw4f1/9m787gq6/z//48jILssKmLuueaSCy7ZqBGhYrlluWRj36lwGZe0/Fk6ZZPZ8knb1KHRMjKdLLUZNTRRMccld8wly31FBQQRBAFZzu+PSzEHRBYPF8vzfrudG3HO+7yv5+GCeve+rtf7vW/fPurXr0+PHj347rvvSjBtKaD5aBEREREREREREZtQob6IiIhIaRO1En5sBZe2QJdl0G2lccFUSlS/fv2wWq25HkePHsXR0ZHhw4ebHbHk2TlBq7eMgn2XOrC+G0SOh+zrZiczlZubGwApKSkmJxERkXylnIWIR2Hfa3D/88aOTfc9bnaqcuGFF15g/Pjx+Pr64uLiQteuXVm8eDFZWVm8+uqreb5n9+7deY61Pv300xJOX0rU6m0sztXsZdg3Gdb9CZJPmp1KRERERERERGwl+RTsGmkUaUdH3CjSPg3t50DVTmanM4dLbXjg/4M+hyFgHVT2gs1Pwo8PwtllgNXshPdGdASs7QCb+xvfd1lyY17oFXCpZW42U1ig2kPQ/h/Q/zy0+xhiN8GqFrB1ECQdMTtg0Wg+2uYuXLjAhAkTGDZs2B3b/Otf/2LVqlWMGjWKsWPHUrVqVRo0aMCXX35J06ZNGT16NFeuXCnB1KWE5qNFRERERERERETuKRXqi4iIiJQW2RmwZ5xxU0bt/tD7MNR92uxUFVKjRo3o2rVrnq/NmTOH/v374+vrW8KpShG3hsaOD53mw4lQWN8FUs6Ynco0rq6uACQnJ5ucRERE7ujcf4wbejMSodcv4DcL7F3NTlUuzJ8/n3nz5uV6vnXr1jg7O3PixAms1nJyE7Wt2TkbiyL13AWZyRDuZyziJSIiIiIiIiLlR+oF2PE8hDWBSz8bRdq9j0Dz14zCdAEs4BsIXZbC4wegSjPYOhjWPmQUcJdVMf+FtR3hpx7gdr+xMHbAeqg7ECx2ZqcrHRzcodEIePygcf4TD8HqlrDzRUi9aHa6gtN8dIkYPnw4AwcOpEePHndss3z5cgD69Olz2/MWi4V+/fqRkJDA999/b9OcpZbmo0VERERERERERO4ZFeqLiIiIlAbpcfBTdzi5wLghp9N8Xaw3UWBgIBMnTsz1/NWrV/n6668ZPXq0CalKoYYvQK9IyEo3biyK3WJ2IlNUrlwZBwcHUlJSzI4iIiK5WOHXt2HL01D/GeOGM48WZoeqEFJSUkhNTaVly5ZYLBaz45Qtnq0gaLdxk/aWAfDrO5SbHeNEREREREREKiprNhz7DFY1h9jN0Pkrowi9zlNg0e1bd+TRHLp+D0F7oLK3sUP5zhfh+mWzkxVceryxOMOGAHCsblxb67LM+GySN0slY0H7xw/AQ6EQ/ROsbg7H5hp/S6WW5qNLSmhoKIcOHeLDDz/Mt11MTAwAPj4+uV6rWbMmAFu3br33AcsSzUeLiIiIiIiIiIgUm670iIiIiJgt+RSs62zsSN5jG9QdZHaiUiM+Pp5XXnmFhg0b4ujoSO3atQkMDGTBggWkpqYCkJ6ezptvvkmzZs1wcXHB29ubPn368MMPP5CVlZXTV2ZmJkuWLKF79+74+vri7OxMq1atmDVrFtnZBbuh46uvvqJu3bp069bNJp+3THJvAj1+hup/gp8C4ewysxOZwtXVleTkZLNjiIjIH1kzYfv/M24q6/AZdPgn2DmZncpUJTluWrbMGBO8/vrreb6+aNEi2rRpg6urKx4eHnTt2pXFixcX/0OWF3bO0PFzaD/HuLl3x/PG77SIiIiIiIiIlD3JJ2B9F4icAI3/auykXv/PKtAvDO928OgaY5f1C+Gw6gE4t9zsVHd37t9G1uj10PXf4L8avNqanarssNhBg2HwxCFoOBz2jIOIbsb19dJG89G52Go+OioqiokTJxIaGoq7u3u+GapVqwbcKtj/o0uXLgFw+vTpYnzKckLz0SIiIiIiIiIiIsWiKz4iIiIiZkr6HSK6gr079NxprFYuAERHR9OhQwe+/fZbZs2aRVxcHJGRkfj7+/MytzZ1AAAgAElEQVT8888zb948AMaOHcvs2bOZM2cO8fHx/P777zRr1ox+/fqxZcutHd7Dw8MZMmQIAQEB/P7775w7d44RI0bwyiuv8Nprr901j9VqJSQkhNGjR9vsM5dZ9m7GzUWNR8HPz8CJULMTlTg3NzdSUlLMjiEiIjdlp8OWp+Dcf+CRVcZ/o6TExk0xMTFMnjyZ4OBgBg3KexGqhIQEQkNDiY2NZdeuXTRo0IBnn32Wl1566Z593nKh8Wh45AdjMaStgyD7utmJRERERERERKQwon6A8PaQlWbsCt/mfaMgUoqm7tPQ+zeo1deY//tlUuksJs3OgL2vwJaBUOdJeOI346sUjb0LtJ1h/A1lJkO4H1xYbXaqWzQfnSdbzUcHBwczdOhQAgIC7pqhZ8+eAKxatSrXa+Hh4QC6xvtHmo8WEREREREREREpEhXqi4iIiJgl5Sz81ANc6kHgRnDyMTtRqTJlyhROnTrFrFmz6N27N+7u7tSoUYM33niDoKCgnHYbNmygRYsWdO/eHWdnZ2rUqMHMmTNp0qRJrj79/f2ZMmUKXl5eVKtWjXHjxjF06FBmzZpFUlJSvnnWrFnDxYsXGTZs2D3/rOWDBfxmQYspsGs4nF1qdqAS5erqSnJystkxREQEwJoN256DmE0QsA5q9jA7UalREuOm+Ph4goKC8Pf3Z+7cuXm22bp1KwsXLqRdu3a4urrStGlTFi5cSMeOHZkzZw47d+68Z5+5XKgZBI+uhegI2P4X43dcREREREREREq/A3+Hzf2hzlPQYxt4Pmh2ovLBwQM6fQGdv4Zjn8GGQLieYHaqW65fhg0BcPxzeHgRdJwHDlXMTlU+eLWGHtuhdj/4bx9j52+zaT76jmwxH/3FF19w7NgxZsyYUaAMwcHB+Pn5MXfuXEJCQoiPj+fs2bOMHTuW8+fPA+DsrMVTbqP5aBERERERERERkUJTob6IiIiIGTKSYGMQVPYC/9XGDSVym+XLlwPQq1evXK+tWbOGCRMmABAUFMS2bdsYMWIEO3bsICsrC4AjR47g7++f857evXuzcePGXH21bt2ajIwMDh06lG+e2bNn89xzz+Hm5lbUj1QxPDgdmoyFbcMgdrPZaUqMq6urdlsQESktfpkI53+Abiug2sNmpylVbD1uSklJoWfPnjRv3pxvvvkGOzu7QuV7+umnAQgLCyvU+yqE6l2g63JjV659r5qdRkRERERERETyZYW9E+HQu0aRdqf5YOdkdqjyp8Ewo2g7+ST8FAjp8WYngvQ42PAYXDsHPXZA/WfNTlT+2DnDQ19Bh8/g4NvwyyRz82g++o7u9Xz02bNnmTRpEqGhobi6uhYog5OTExs3bmT8+PF8+OGH1KxZk06dOmG1Wlm2bBkAvr6+xfyk5ZDmo0VERERERERERApFhfoiIiIiJc4KO14wdnbwXwOVPc0OVOqkp6eTmJiIk5MT7u7u+bYNCQlh4cKFnDx5kscee4wqVaoQFBSUU+h/U2JiIm+++SatWrXCy8sLi8WCxWJh0iTj5o1r167d8RhHjx5l3bp1jB49uvgfriJo9wnc9zj8PATSos1OUyLc3NxUqC8iUhqcWQKHZ8FDoVDD3+w0pY4tx02ZmZkMHDiQWrVq8fXXXxe6SB+gZs2aAMTGxhbh01UAvo/BQ/Ph94/h3L/NTiMiIiIiIiIidxL5MhyZDQ9/A42Gm52mfPN8EAI3Qfpl+OkxYzd7s6THw4YAyEiEwP+CZ0vzslQEjUdB54Vw+FNjYQwzaD46X/d6PjosLIzExET8/f1z2lgsFoYNGwbA1KlTc547fvx4Tv/u7u7MnDmTU6dOcf36dS5evEhISEjOtd127dqVxI+j7NF8tIiIiIiIiIiISIGpUF9ERESkpB2fD1Er4U/fgksts9OUSo6Ojnh4eJCWlsbVq1fzbXvz4ntERARXrlxhxYoVWK1WBgwYwMcff5zTrk+fPkyfPp3hw4dz9OhRsrOzsVqtfPLJJwBYrdY7HmP27Nl069aN5s2b35sPWN5ZKkHnBWDnAjteNDtNiXB1dSU5OdnsGCIiFdu1KNg1HJqMhXrPmJ2mVLLluGnkyJGkp6ezdOlS7O3tc55v1KgRO3bsKFC+CxcuAODj41Ocj1m+1f+zcRPyjhch9YLZaURERERERETkfx3/Ao7OgT8thnqDzU5TID/++CNNmjS5bU6nIPr27YvFYuGdd97J9VpCQgJz584lICAAb29vnJ2dady4Mc8++yz79++/V9ENbg1uFetv+zNYs+9t/wVhzYZtz94o0t8ErvVLPkMR2OLc34v+C6z+UHj4X3D4EzjxpW2OcSeaj76rez0fPWbMGKxWa67HokWLAJg+fXrOc40aNbprvq1btwIwYMCAe/3Ryw/NR4uIiIiIiIiIiBSICvVFRERESlJaLOybDE1f0qr6d/Hkk08Cxg0c/6tt27a8/PLLAHh6enL48GEAHBwc6N69OytWrMBisbB69WoAsrKy+Pnnn/H19eWll16ievXqWCwWAFJTU/PNkZSUxMKFCxkzZsw9+2wVgoMHPPQVXFgDZ5eancbm3NzccnZdEBERk0S+BE6+0HaG2UlKLVuNm9566y0OHTrEypUrcXR0zDfD/Pnz8fPzy/W81Wpl6VJjzNCnT58if8YKod1H4FgVIsebnURERERERERE/ujyHmOOqsXrUHeg2Wnu6sSJE/Tt25cpU6YQExNTqPcuXLiQsLCwO74+adIkxo0bR79+/fjtt9+Ij48nNDSUffv24efnx4oVK4ob/3audaHrMoj+CX6dfm/7LoiD0yDmv9D13+BSp+SPX0i2PPfF7b/Q6g2GFlNgz1i4HGnbY/2R5qPvytbX8QsiLi6OSpUq5SwSe1NSUhLz589nyJAhNGnSpNjHKdc0Hy0iIiIiIiIiInJXKtQXERERKUmH3gN7Z3hwmtlJSr3333+fBg0a8PLLL7N69WquXr1KVFQUo0eP5uLFizmF+gCjRo3iwIEDpKenExsby4wZM7BarQQEBABgZ2eHv78/0dHRzJw5k7i4OFJTU9m4cSNz587NN0doaChubm45CwdIIfh0hfv/AvumgDXT7DQ25erqSnJystkxREQqrrhtcG45tJ8Ddk5mpynV7vW4acGCBUybNo2dO3fi7u6OxWK57XHixIlc79m7dy9jxozh+PHjpKWlceTIEYYNG0ZkZCTjxo2jU6dONv85lGl2ztD+H3D2e4jfaXYaEREREREREQFjR/WdwVC9K7R6y+w0BTJ16lQefvhhIiMjcXd3L/D7Lly4wIQJExg2bFi+7V544QXGjx+Pr68vLi4udO3alcWLF5OVlcWrr75a3Pi5Ve0E7T40CvUTf7v3/d9J4iE49C74fQre7UvuuMVg63Nf1P6L7MG3oVpn42/Qmm3742k+usBseR2/oKxWK88//zzHjx8nPT2dXbt2ERQURI0aNQgJCbknxyjXNB8tIiIiIiIiIiJyVxar1Wo1O4SIiIhIhZB+CVbWh9bvQVOtNl4Q8fHxvPPOO6xcuZKoqCiqVavGI488wttvv03jxo0B2L9/P//85z/ZvHkzZ86cwcnJiSZNmvDiiy/y4osv5qy4HxcXxxtvvMGPP/5IdHQ03t7e9OrVC19fX/7v//4PAD8/P/bs2ZNzfKvVSpMmTRg6dCjTpmlxhSJJPgVhTeChUGiQ/007ZdnYsWM5ePAgmzZtMjuKiEjF9N/ekHEFum81O0mpZotxU+/evXN2P7qT7du389BDDwGQnp5OWFgYixcv5sCBA0RFReHk5ETbtm0ZMWIEzzzzjG1/COXJus7g5APdVpqdREREREREREROfg07X4QnDkKVB8xOUyCpqak4OzsDULt2baKjo8nMvPvCy0888QS1a9ema9euDBs2jOnTp/PGG28U+LguLi6kp6eTmZmZMx91z1izYW0HcKldcnMm/+0NqVEQtBcsZWPPHFuf+6L2XyxJh2F1K+j8FdT/s22PpfnoArHldXwwFgGYN29eruP27NmT8PDwnO8jIiKYM2cOu3btIjExkYYNGzJ48GAmTpyY83sqBaD5aBGp4JYuXcrgwYNR2YWIiIiIiIjkIVOF+iIiIiIl5egc2P86PBkN9i5mpxEpOVsHGQtVPLbR7CQ2M3nyZNavX09kZKTZUUREKp7UC7CiDnRZBnUGmJ1GpOScXQY/PwNPRoGTr9lpRERERERERCowK/zQCHwDoWPuotGyoKDF1KGhobz99tscPHiQlStXFrpQPyUlBTc3Nx588EH2799/L6LndnEtbAyCoEjwbmebY9x0ORLC20PAeuP8l0G2PvclVqgPsDMYYjdBn6PAPV4E4ibNR0tFpfloEangVKgvIiIiIiIi+cgsG8v4ioiIiJQHZ5dBrX4q0peKp94zELsZ0qLNTmIzrq6upKSkmB1DRKRiOvcfsHeD+x43O4lIyarV2/h/i3P/MTuJiIiIiIiISMUWvxuST0Lj0TbpPj09nTfffJNmzZrh4uKCt7c3ffr04YcffiArKyunXWZmJkuWLKF79+74+vri7OxMq1atmDVrFtnZ2cXOERUVxcSJEwkNDcXd3b1IfSxbtgyA119/vdh57qhmT3BrCGeX2u4YN535Dtwb26xIvzyd+xLReDRcPQ6X99ruGJqPlopK89EiIiIiIiIiIiJ3pEJ9ERERkZKQfR3idkHNHmYnESl5voGABS5tNzuJzahQX0TERLFbwOcRsHMyO4lIybJzhupdIXar2UlEREREREREKrZzy43CcK/WNul+7NixzJ49mzlz5hAfH8/vv/9Os2bN6NevH1u2bMlpFx4ezpAhQwgICOD333/n3LlzjBgxgldeeYXXXnut2DmCg4MZOnQoAQEBRXp/TEwMkydPJjg4mEGDBhU7T77qDCiZYtJzy6HOUzbrvryc+xLj3Q7cGtj23Gs+WioqzUeLiIiIiIiIiIjckQr1RUREREpC4u+QnQ7efmYnESl5Du7g3gQSfjE7ic24ubmRnJxsdgwRkYopYZ9xA6ZIReTtV67HWCIiIiIiIiJlQsI+8Olms+43bNhAixYt6N69O87OztSoUYOZM2fSpEmTXG39/f2ZMmUKXl5eVKtWjXHjxjF06FBmzZpFUlJSkTN88cUXHDt2jBkzZhTp/fHx8QQFBeHv78/cuXOLnKPAajwCV49Bpg2v3WRcheQTOveljc8jtp0v03y0VGSajxYREREREREREcmTCvVFRERESkJajPHVpZa5OUTM4lLr1t9BOeTo6EhaWprZMUREKqa0GHDWGEsqqHI+xhIREREREREpE1KjwKWOzboPCgpi27ZtjBgxgh07dpCVlQXAkSNH8Pf3z2nXu3dvNm7cmOv9rVu3JiMjg0OHDhXp+GfPnmXSpEmEhobi6upa6PenpKTQs2dPmjdvzjfffIOdnV2RchSKc23j67XztjtG6o2+XWrb7BBl/dybwqW2bc+75qOlItN8tIiIiIiIiIiISJ5UqC8iIiJSEjJTjK/2ZeQGBpF7zd7N2FmknKpcuTLXr183O4aISMWUmaIxllRc9u623RlORERERERERO4u/TI4etus+5CQEBYuXMjJkyd57LHHqFKlCkFBQSxfvvy2domJibz55pu0atUKLy8vLBYLFouFSZMmAXDt2rUiHT8sLIzExET8/f1z+rRYLAwbNgyAqVOn5jx3/Pjx296bmZnJwIEDqVWrFl9//XXJFOkDOFYzvqbH2e4Y6fHG18o693mde9M4VrPtedd8tFRkmo8WERERERERERHJkwr1RUREREqCg7vxtYwUKp85c4a+ffuSlJTEihUrbrvxojzsGj537tzbPlNej169ehW5PUBWVhaffvopbdq0wcXFBQ8PDwICAoiIiChQxr59+2KxWHjnnXdyvTZ58mSWLFlSvB9CSctIgsqeZqewmcqVK5OdnU1mZqbZUUREKh4Hd8gsG2MsKP/jrD/68ccfadKkCfb29oV6X37jICj8OKsw7cvcOCsjERw8zE4hIiIiIiIiUrE5VoO0Szbr/mZhdEREBFeuXGHFihVYrVYGDBjAxx9/nNOuT58+TJ8+neHDh3P06FGys7OxWq188sknAFit1iIdf8yYMVit1lyPRYsWATB9+vSc5xo1anTbe0eOHEl6ejpLly69bY6oUaNG7Nixo0h5CiQ91vjqVMN2x3CqfuNYtisKL8vn3jRpMbY975qPLlWKch2/S5cud2w7YcKEPI+TkZHBJ598gp+fH+7u7vj4+NCrVy/CwsJu+/tKSEhg7ty5BAQE4O3tjbOzM40bN+bZZ59l//79ufrVfLSIiIiIiIiIiEj5oEJ9ERERkZLg5Gt8vRZlbo4C2LdvH+3bt6dHjx5UqVKF/v37Y7Va6devn9nRStTDDz9c5PZZWVn079+fV199leDgYM6dO8e+ffuoX78+PXr04Lvvvsu3r4ULFxIWFnbH14cPH86UKVOYOnVqoTKa6to5294UY7LKlSsDcP36dZOTiIhUQM41y8QYCyrOOOvEiRP07duXKVOmEBMTU6j33m0cVNhxVmHbl7lx1rWocj3GEhERERERESkTXGpDqu3mpzw9PTl8+DAADg4OdO/ePafgdvXq1YAxB/Lzzz/j6+vLSy+9RPXq1bFYLACkpqbaLFt+3nrrLQ4dOsTKlStxdHQs2YPfnC90vs92x3CudeNY52x2iLJ67k11LcrG513z0WVNYa/7/6+UlBQCAgJYsGABn3zyCbGxsezZswc3Nzf69u3LoUOHctpOmjSJcePG0a9fP3777Tfi4+MJDQ1l3759+Pn5sWLFitv61ny0iIiIiIiIiIhI+aBCfREREZGS4NEM7F0gfrfZSfKVlJREnz59eOqppxg7dqzZcWyqX79+ee4AcfToURwdHRk+fHiR2//rX/9i1apVjBo1irFjx1K1alUaNGjAl19+SdOmTRk9ejRXrlzJM9eFCxeYMGECw4YNu2P2hg0bsnz5ct59912WLl16b34gtnT9Clw9Dt7tzE5iMzdvMFOhvoiICbzaQvwes1PcVUUaZ02dOpWHH36YyMhI3N3dC/y+goyDCjvOKmz7MjfOurynXI+xRERERERERMoEbz+I2QgUbdfyghg1ahQHDhwgPT2d2NhYZsyYgdVqJSAgAAA7Ozv8/f2Jjo5m5syZxMXFkZqaysaNG5k7d67Nct3JggULmDZtGjt37sTd3T3XrtUnTpywbYDoDeDR3Lg+ayv2rlDlAYj5yXbHoOyde3NZjb/Fqu1tdwjNR5c6hb3uD7B79+483/Ppp5/majtp0iQOHDjAunXr6NatG87OztStW5cFCxbkuQjJCy+8wPjx4/H19cXFxYWuXbuyePFisrKyePXVV29rq/loERERERERERGR8kGF+iIiIiIlwWIP1TrDxXCzk+RrxowZREdH8+abb5odxaYaNWpE165d83xtzpw59O/fH19f3yK3X758OQB9+vS5ra3FYqFfv34kJCTw/fff59nf8OHDGThwID169Mj3M7Ru3Zqnn36aiRMnkpmZmW9b011cCxY742+gnKpcuTKgQn0REVP4dINLWyAzxewk+aoo4yyAL7/8ksmTJ2Nvb1+o9xVkHFTYcVZRxmVlZpyVmQyXthp/AyIiIiIiIiJinjpPQcpZmy3YvWnTJpo1a8aQIUPw9vbmgQceIDw8nC+++IK//e1vOe2WLFnCyJEjmTNnDvfddx8NGjRg4cKFDB06FIDu3bvTvv2tAuZVq1blFM6fP3+erKysnO/nz59/xzyjRo3CYrHkLLY4depULBYLQUFBOW3udB2sZFghajnUedr2h6ozAM5+j60WaSiL5744/Rdb3A5jx29bnnvNR5cqhb2OX1gxMTF8/vnnPPvss9SocftO8q6urqSlpdGyZcuc5+bPn8+8efNy9dO6dWucnZ05ceIEVqs112uajxYRERERERERESnbCne3rIiIiIgUXd1BsPdlyEgChypmp8nFarUyf/58OnXqxH333Wd2HJsKDAwkMDAw1/NXr17l66+/JiwsrFjtY2JiAPDx8cn1npo1awKwdetWgoODb3stNDSUQ4cO8d1337Fy5cq7fo4nn3ySZcuWsXr1avr163fX9qY5sxh8HwPHamYnsRkV6ouImKjOk7B7DESthPpDzU6Tp4o0zgJwdnYu9HsKOg4q7DirqOOyMjHOOrccsjOg9pNmJxERERERERGp2LxaGzurH5kDDy+65923bt26QDujV6tW7Y7t3n///VzP9e7dO1fBaEHMnTv3rnlWrVpV6H7vmXMrIOUc1Btk+2PVGwyH3oOoMKjd9553XxbPfXH6L7aj/wCPFuDZ8u5ti0rz0aVKYa/jF9YPP/xAVlYWXbp0KVY/KSkppKam8uCDD2KxWHK9rvloERERERERERGRsq2S2QFEREREKoy6g8BiD8c+MztJnvbv309MTAytW7fOt110dDSDBw/G09OTqlWr0rt3b06cOJGr3eHDh+nfvz8eHh64uLjQsWNHVq1aRWBgYM6OCcHBwaxYsSLne4vFwunTpwvUf3x8PK+88goNGzbE0dGR2rVrExgYyIIFC0hNTS3Sz+Crr76ibt26dOtWsFXg79S+WjWjIP1mYdgfXbp0CYDTp0/f9nxUVBQTJ04kNDQUd3f3Ah2/TZs2AKxdu7ZA7U2RdBjOr4JGw81OYlMq1BcRMZFjdajTHw5/hK12rioujbPyV5hxUGHHWUUZl0FZGGdZ4fDHxq5tjlXNDiMiIiIiIiIiD75tLFx8ea/ZSSo2aybsfx3qDTEKtm3NsxXUHQj7XjWOLeZJ2AdnvoMHp9v2OJqPLhPz0Xe77r9o0SLatGmDq6srHh4edO3alcWLF+dqt3ev8e90Ly8vJk6cSJ06dahcuTL16tXjpZde4vLlywXKs2zZMgBef/31PF/XfLSIiIiIiIiIiEjZpkJ9ERERkZJS2RMaj4bfP4brCWanyeXXX38FoHbt2vm2mzBhAhMmTOD8+fMsW7aMLVu28Mwzz9zW5vjx43Tu3Jk9e/bw/fffExsby1dffcWsWbM4cOAAjo6OOSv59+/fH6vVmrMy/B/7X7JkCT/99FOu/qOjo+nQoQPffvsts2bNIi4ujsjISPz9/Xn++eeZN29eTtuAgACqVq3Kjh078v1cVquVkJAQRo8eXaCfV37te/bsCeS9W0h4eDhgrJr/R8HBwQwdOpSAgIACHR+gVq1awK1zVyodfAvcm5b7lfVVqC8iYrLmU+DyL8ZuWaVQRR9n3U1hxkGFHWcVZVwGZWCcde4/kLDf+N0XEREREREREfPVfQqqdoQ944wdh8Ucv82E5BPQ+p2SO2ab9yD5lHENWMyRfR12jYKqnYwielvTfHSpno8uyHX/hIQEQkNDiY2NZdeuXTRo0IBnn32Wl1566bZ2Fy9eBOCFF14gJiaGTZs2ERsby/Tp0wkNDaVz584kJibmmycmJobJkycTHBzMoEGD8myj+WgREREREREREZGyTYX6IiIiIiWpxWSo5AD7St8FzJsXmT08PPJtFxwcTOfOnXF1dSUgIIDevXuze/du4uLictr87W9/48qVK8yaNYvu3bvj5uZGixYtWLx4cZ6FUHfqPzAwkCeeeCJX/1OmTOHUqVPMmjWL3r174+7uTo0aNXjjjTcICgq6rb/s7GysVitWa/47GqxZs4aLFy8ybNiwfNsVpH1wcDB+fn7MnTuXkJAQ4uPjOXv2LGPHjuX8+fMAODs757T/4osvOHbsGDNmzCjQsW+qUqUKFosl59yVOhfXwpkl0PYDsJTv//VQob6IiMm820H9ZyFyPGQmm50ml4o+zspPYcdBhR1nFbb9TaV6nJWRBJET4P6/gFf+u2KJiIiIiIiISEmxwEMLIPFX+GWS2WEqppiNcOBNaPMBuN1fcsd1awit34P9f4Po9SV3XLll70RIPASd5gMW2x9P89Glej76btf9t27dysKFC2nXrh2urq40bdqUhQsX0rFjR+bMmcPOnTtz2qalpQHGHPKCBQu4//778fT05LnnnmPKlCkcPXqUjz766I5Z4uPjCQoKwt/fn7lz596xneajRUREREREREREyrbyXS0jIiIiUto4eEC7j+D453A+zOw0t7l5kdnBwSHfdh06dLjt+5uru1+4cCHnuZu7k97cwfSm6tWr06xZs0L1X6dOnVz9L1++HIBevXrlev+aNWuYMGFCzvf//e9/uXz5Mp07d873uLNnz+a5557Dzc0t33YFae/k5MTGjRsZP348H374ITVr1qRTp05YrVaWLVsGgK+vLwBnz55l0qRJhIaG4urqWqBj/5G9vT2pqamFfp/NpcXCzheh3mCo1cfsNDanQn0RkVKg3UeQdQ12jzE7SS4VfZx1J0UZBxVmnFWU9n9UasdZu/9q7BLWdqbZSURERERERETkj6o0hY7z4MhsODHf7DQVS9Jh+HkI1BkAzSbcvf299sArUOdJ2DYMrh4t+eNXZMc/h6Mh8NCX4NG85I6r+ehSOx9d2Ov+Nz399NMAhIXduo/j5rx1YGAg9vb2t7Xv08e4Br527do8+0tJSaFnz540b96cb775Bjs7u3yPr/loERERERERERGRskuF+iIiIiIlrd4QY7Xx7f8Prh43O00OJycnADIyMvJt978r71eqZAwps7OzAUhPT+fq1as4OTnlefHby8urUP3fLID+Y/+JiYk4OTnh7u6eb18FdfToUdatW8fo0aPvWXt3d3dmzpzJqVOnuH79OhcvXiQkJCRnZ4F27doBxoX+xMRE/P39sVgsOY+bK/xPnTo157njx3P/vmRmZua5C6ypsjNg27NQqTJ0+KfZaUqECvVFREoBJx/ovBBO/wuO3XlnGjNU5HFWfoo6DiroOKuo7W8qleOsoyFw5jvovAgcq5qdRkRERERERHuthVkAACAASURBVET+V70h0OrvsGskHJ9ndpqKIfEQRDwKbo1u7KhuBgt0CgW3BhDhD0m/m5Sjgjn2GewaBQ9Og7qDSvbYmo8ulfPRhb3u/0c1a9YEIDY2Nue5+vXrA1C1au65WB8fHwAuXbqU67XMzEwGDhxIrVq1+Prrr+9apH/zPZqPFhERERERERERKZtUqC8iIiJihg4h4NYQNgZBWrTZaYBbF54TExOL1Y+joyPu7u6kpaWRnJyc6/U/Xtguav8eHh6kpaVx9erVYvV10+zZs+nWrRvNmxdsl4XCtv+jrVu3AjBgwAAAxowZg9VqzfVYtGgRANOnT895rlGjRrf1lZSUhNVqzTl3pYMVdr4Icduhy/dQOf8bNMoLFeqLiJQS9z0OLd+EPeMg6gez0+SoyOOs/BRnHJSX/x1nFad9qRxnnVsOkeOh1TSo2cPsNCIiIiIiIiJyJ63+bvz/+66/wm//B1jNTlR+XfrZKNKv0gQC1oKD7RefvCMHd3h0nXENOMLfuFYmNmKFQ+/C7rHQ5j1oOdWcGJqPLnb/Zl/3/6MLFy4AtwrwAbp06QLAxYsXc7W/+flr1KiR67WRI0eSnp7O0qVLsbe3z3m+UaNG7NixI1d7zUeLiIiIiIiIiIiUbSrUFxERETGDnTP4rwZLJfipJ6TFmJ2Ili1bAhAVFVXsvnr16gVAeHj4bc9HR0dz9OjRYvf/5JNPAvDjjz/meq1t27a8/PLLBe4rKSmJhQsXMmbMmHvWPi4ujkqVKuVczP/je+fPn8+QIUNo0qRJgTPeyfnz54Fb58501mzYPQbOLIGu/wbvvHenLY9UqC8iUoq0ehMavgA/D4GL4XdvXwIq6jjLFgo7zirquKzUjbMurIZtQ6HRCGj5htlpRERERERERORuWr4Bfp/C/qmw5SnISDI7UflzZBZseBSqPwz+a8A+947fJc7BHR5dA1U7GsX6R+eYnaj8yUiEzU/CwWnQfg40n2xuHs1HF0tJX/efP38+fn5+uZ63Wq0sXboUgD59+uQ8//jjj1OrVi3Cw8NJS0u77T1hYWEA9O/f/7bn33rrLQ4dOsTKlStxdHQsUHbNR4uIiIiIiIiIiJRtKtQXERERMYuTDwSsh6xUWN8VUs6YGqd169b4+Piwf//+Yvf13nvv4e3tzYQJE1i/fj3Jycn8+uuvPP/88/j6+ha7//fff58GDRrw8ssvs3r1aq5evUpUVBSjR4/m4sWLt12wDwgIoGrVqnmuTA8QGhqKm5tbzk0Ad1PQ9larleeff57jx4+Tnp7Orl27CAoKokaNGoSEhBT8w+Zj3759APToUQpWsLdmwo6/wIlQ+NO3ULOn2YlKlAr1RURKEwt0+AzqDYJN/eDsMrMDVdhxlq0UdpxVlHFZqRpnnVli3Hxcfyi0/4fZaURERERERESkoJq+BI9tgEvbIbw9xG4xO1H5kBZtLH6wd6Kx03O35WDvYnaqW+zd4JEfjF3eI1+GrQNLxaLt5ULsZuNvKX43PPYTNCnYQuy2pfno4jDjuv/evXsZM2YMx48fJy0tjSNHjjBs2DAiIyMZN24cnTp1ymnr6OjI/PnziY+PZ8iQIRw7dowrV66waNEi3n//fTp16sRLL72U037BggVMmzaNnTt34u7ujsViue1x4sSJPDNpPlpERERERERERKRsU6G+iIiIiJlc60H3zcbNI2s7waWfTYtisVgIDg5m586dt+04umPHDiwWCytXrgTA2dmZN954I+c9H3zwAWCsaN+7d28AGjZsyPbt2+nQoQNPP/00NWrUYOTIkUyZMoUGDRpgZ2dXrP59fX3ZvXs3gwcPZty4cVStWpWOHTuSkJDAli1bqFu3bk7/mZmZWK1WrFZrrs9stVoJCQlh+PDh2Nvb3/VnVND21apVY/369Tg5OdG1a1e8vLx48cUXefzxx9m+fTve3t53fO+oUaOwWCwMGzYMgKlTp2KxWAgKCsrVdvny5dSqVYsnnnjirtltKj0efuoB5/5j3HhUZ4C5eUygQn0RkVLGYgcPfQWNRxk7GR16D8g9FiixOBVsnLVq1aqcGw/Pnz9PVlZWzvfz58+/48+pIOOgwo6zijouKx3jLCv8Oh1+fsa46bjTfLBoOldERERERESkTPHpBr32gnsjiHgEdo2A6wlmpyqjrHD8c1j1AFzeCwHroMUUwGJ2sDxYjF2oHw03ispXPQAn5mPmHGWZdv0y7AyGCH+o0gx6RUL1LmanukXz0UXuv6Sv+w8bNoxly5Zx8eJFgoKC8PT0pFOnTpw/f57Fixcze/bsXO8JCgpi8+bNpKWl0aFDB2rUqMF7773HpEmT2LhxI87Ozjltv//++zseOz+ajxYRERERERERESnbLNa8Zi5FREREpGRlXIXtw+BCOPh9Ao3/akqMxMREWrRoQe/evZk7d65NjtGsWTNSU1M5c+aMTfqvKPbv30/btm1ZvHgxQ4YMMS/I5T2wdTBYs40dS7zamJfFZHZ2dnzzzTfmng8REcnt6D+MnavqPAmdvgAHD1NiaJxVdpSKcdb1K7DzRTgfBn6fQuPR5uQQERERERERkXvnzBKInABkQ4vXofFIqORodqqyIXoD7P+bUaDfbAK0mmYshF4WZKbAgTfhyGyo2h5avws1AsxOVTZkpcGxuUbheyV78JsFdQeanSp/mo+WQtJ8tIhI2bB06VIGDx6c54IxIiIiIiIiUuFlaslLERERkdLAwR26/gdaTIY942Dzk8Yu5SXMw8ODsLAwvv/+e0JCQorcT3R0NN7e3mRkZNz2/OnTpzlx4gQBAbr5pDhOnjzJgAEDmDJlinkX663Z8NsMWPcncGsIQbsqdJE+gKOjI9evXzc7hoiI/K8mY43dtWK3wI9tIG6bKTE0ziobSsU469JWWNMG4nZAwHrdFCkiIiIiIiJSXtQbDL1/gwbDYN9kCGti7LKerWsLdxS3DTY8Bj8FQmVvCNoDbWeWnSJ9AHtXaPcRBO02irY3PGY8TJqnLBOyr8PxL4y/kQOvw/1/gSd+K/1F+qD5aCkUzUeLiIiIiIiIiIiUDyrUFxERESktLJWg1VvQfStc2W/ceHBkllEQXYLatm3Lnj17WLNmDUlJSUXuJyEhgZEjR3Lu3DmuXbvGrl27GDx4MFWqVGHq1Kn3MHHFM2/ePN59913effddcwIk7IP1XWD/69BiCjwaDo7VzclSilSqVImsrCyzY4iISF5qPApPHADPlrC+K2x/zpRFkTTOKv1MHWddvwKR4yHCH6o0hV6R4PNIyecQEREREREREdup7AVtP4R+p6HeM7B7LKyoaxTuX4syO13pkH0dzi6Dn7obC0ZnpcJjP8Gja8Crtdnpis6rjXFNrcc2wGp8tvD2cPxzY+d4gbQY+O0D+KEh7BkD9/WCPseg7Qyo7Gl2uoLTfLQUkOajRUREREREREREygeL1Wq1mh1CRERERP5HRiIceBOOhoBXW+j4T/Bub3aqQtmwYQMhISH88ssvXLhwAS8vLwIDA5k2bRoNGzY0O54UxR9/L6s/DO1DwLOV2alKDXd3d2bNmsULL7xgdhQREcnP2WWwZxxkZ0Cb96HRcMBidqpC0TirvLHCqUXwyySgErT9wNhZr4z9XoqIiIiIiIhIEVyLgmOfGbuHZyRB3aeh/p+hZnew2JudrmRd+RVOfwMnF0B6HNQZAE3HQfUuZiezjUtb4chsOLccnKrD/c9D/aHg0cLsZCUrOwOi18Gpf8G5/4CDhzFn2/iv4FLb7HTFp/loKXU0Hy0iUhRLly5l8ODBqOxCRERERERE8pCpQn0RERGR0izhF9g9GuL3GDeitPq7cXOCSEmyZhs3Rv0yCbBCmxlw/3PoYv3tPDw8+OijjwgODjY7ioiI3M31K7D/dTg+D6r/Cdr/Q4vPiDkS9sOesRC33bj5uPU7Gu+LiIiIiIiIVERZaXDmWzg+35gncKwG9QZB3UHG4snltWj/6jE49284vRiuHATXutDgOWg0snwUaRfEtSg49k+jcPbaOfB80CjYr/MUuDcyO51tWDMhdiucXWoUsqfHG7/nDYOh3hCwczI74b2l+WgpLTQfLSJSZCrUFxERERERkXyoUF9ERESk9Luxovne/w+y06DxaGj+GlT2MjuYlHfWbLiwGg78HRL2QYM/Q7uPjZvDJBdPT09mzpzJ8OHDzY4iIiIFlbMo0i6473FoNQ2825mdSiqCK7/C7zOMm9C9WkOHf0LVjmanEhEREREREZHSIPkUnFkMp7+FxENQ2RN8u8N9vaBmEDjXNDth0WVeg9hNcOFHuLAGkk+AY1WoOxDqDQWfLlTYhaKt2XBpqzFfdHYZXL9sFOrf97hx7n0eATtns1MWXeoFuBAOF9fAxfWQkQieLY3zXv8ZcK1vdkLb03y0mEXz0SIixaZCfREREREREcmHCvVFREREyoyMq3DsM/htBlgzbhTsvwqVvc1OJuWNNdvYveTA3+HqEeNGkQffBq+2Zicr1by8vPjggw8YMWKE2VFERKRQrHB+FRycBpf3Qq0noNVb4O1ndjApj64chN9nwulvwKM5PDAJ6j8LFjuzk4mIiIiIiIhIaXT1qFHQfmGNUeCelQZuDY3dx6s9bOzO7dG89M4tXDsPcduMx6VtRqFydqZRKFozyChAr/4wWOzNTlq6WDPh0s+3CtsTDkAle/Bqd+vcV+sMLrXMTpo3axYk/mYsPBC33fgsySeNhQZ8HjHO+329wL2x2UlNoPloKUGajxYRuWdUqC8iIiIiIiL5UKG+iIiISJmTkQRHZsPhT4ybNBqPhiajwaWO2cmkrMu8Bme+NS7WXz0O9Z6Blq9DlWZmJysTvL29ef/99xk5cqTZUUREpAjOn49i3XcfsH7VN3w+7ApujfpBs1fAp6vZ0aQ8iN0Ehz+GqDDwbgst34TafamwO8SJiIiIiIiISOFlXrtR+Hyj6D1+h7HQt50TVHnA2J3co4XxcLsfXOuBvavtc2VnQOp5SD4NSYeNwtCk34yv6fFGEb7XgzcWFngYfPzBuabtc5UnqRcg5r+3it6vHDCK4R2rgmcr45x7tjKu6bnWA5faJbP4QWYKpJw2ivATfzN27U48BEm/G4tKOFSBag/dOvfVuxjF+gJY4dwK+PVtSNgPtTUfLfeQ5qNFRO45FeqLiIiIiIhIPlSoLyIiIlJmZVyFo/8wivbTLxmr7TcaBTV7gqWS2emkLEk6DMfmwqmvITMV6g+BFn8D9yZmJytTqlWrxvTp0/nrX/9qdhQRESmAtLQ0tmzZwtq1a1m3bh0HDx7E2dmZbt268c+/D6BB0pcQv8u4ybXxKGgwDBw8zI4tZcn1K3B6kTHOSvzNuCm5xevGuF03RIqIiIiIiIhIcVmzjMLoK/tvfD1oFElfO3erjWO1W4XbjtWMwu7KVY2vDlWMQv5KlY22Du63irszEsGabfzz9QTISoX0y3D9slF8f/0yXIuClDNGEbk160YfHjeKxlveWDigFVRtD/ZuJfdzqQgykyF+DyQevHHubxTIZyQar1vswKWWce6da0Fl7xvn3hscvY1i+cpeN9pWujXvac00rkEDZF83CvEzEo1znx534/zHGb9jKWeNf77Jte6NhSJunHuvNsb32rn7LqwQ9QMcek/z0VI8mo8WEbEpFeqLiIiIiIhIPlSoLyIiIlLmWbPgwo9GwX70BnC5D+r/GZqMNW66EclL9nWIWgnHP7/1e9MwGBqPBicfs9OVSdWrV2fatGmMHj3a7CgiInIHJ0+eJCIigoiICMLDw7l69Sr3338/gYGBBAYGEhQUhLu7+603XI40/lt5erFxk2qtPtB0PFT/k3kfQkq/nN+bb4yxet2B0HQCeLczO5mIiIiIiIiIVAQZSUYBfcoZY7fzlDNw7Txcj79RbB9vFNtnJN2xi/hkCN8PQzqDXSWMwm5Hb6PQ+2axt/N9NxYBqGt8da0HzjVL7GNKHlIv/uHcn4FrZ42FFG4usnD9svHPWak5bzl8ATYfhhEBd+jTwePGua9666tLbaMw37X+jUc9Y6EHKR7NR0tRaD5aRKREqFBfRERERERE8qFCfREREZFyJekwHJ8HJ782djjw7Q71BkGtvlDZ0+x0YjZrFsRugjNL4dx/jJtxaj0Bjf8Kvj2MHTOkyHx8fPj73//OmDFjzI4iIiI3JCcns3HjRlatWsXatWs5c+YMbm5u+Pv706dPH4KCgqhbt+7dO8pIhFM3d6I5BJ4PGmOsuoPAvbHtP4iUflePGmOss8vgygFj17BGN3e+qmJ2OhERERERERGRvGWlQlaa8c8ZSca1JGDfb2dp2+lRft23gxatO5kYUGwmIxGs2Xy35Hue/csoshKPgcXu1lyWnZOxQIOUPM1Hy91oPlpEpMSpUF9ERERERETykWlvdgIRERERuYeqNIN2n0Dr9+Dcv42LsztHACOgZo9bRfu6OFtxWLM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vMmfOHJQ2IiIiIiIiErpULOBYVBZA/neQ9y0c/Abyv7XHvqSmsGgbAE/wJsgn9vMnzMf1Cu0q9zWV/qIJvkIJdYsn+FaaDYuC5CGQPBxSToJ2J0HyCCuiINLcnCqbHOqbMFqUbhfufF+X7qs/wSQq1ZsY09Vf0CO2mzdpJq3OhTwlyByXmkpb3bX0AJR6i4+U7vV+vc9bgMRbqKHuqtbhMQ0mtfapM7m1t110FamjqqqK0aNH06lTJxYtWuR2OBIITlX9SQm+1RlK99WZ0LnfP5Gh4UrOnvDGhV0aJYY3fL4dRCRqJfrWrLrMO+HlCEUi6r3mva8ua/x+Uan+yT6xXW0lxxjvao4xnesnnygBQ+TQSvd7++jbG99K9lG76o4n3Pat2G62b8WleZPY07xJ7T28+177+qu6yqFV5Hn74Bne4gt1izHs8/bV99dvAyOTvQUBm7ipOGCr9fnnnzN27Fh2795N9+7d3Q5HAqHMW1ylZA8U74KS3d6vd9vXpfvr95k9EXWSabt4+zkdGyTkeB/7iiRK4FQWWp+0qUS1siz/qra+BLeG/8u4bnacjOtpRWDiukN8ncd1VqIVCSo1lVC4BfLXQ8EGyF8HBRshf6M/IT48xp+MUDt22Kv+uGFbSxCsOGjte92kltqx8Z12nguAx/5eSUMgeajdpwyDpMHW5xMROUHfffcdV199NZs2beJ//ud/uOWWW2wFXDeoP9y6qT8sIiKBUrIb8jfUOe9cbzffeZMnzK5JHCohPrZb27sGWF1q1xGKdzZRSCG9/jysqFQ736x3zjnEjr8iIiLS4lQsQEREREREJPSpWMChVByE7JV2y1tjRQGK0gHHVoZNHg4pIyzZPWmoFQSITbMLBdJYRa4lexRsrFNs4TubiAF2gcBXOKDD6dBhrCUbiBxJTaUVpMhfb5+vwq3eZKP0+qtIhcfWuXjX2590HtfN9t2Yzja5VIJDRZ5N+inNsIladYs8FKfbxUffSqj1qpX3gaRBNqk1eYhdnJU2509/+hO/+MUv+Oabbxg0aJDb4cixcKq9q0Tv9E/eLNntLS6SYRMAfRP+qNOFDYv2J2w3TNL2rR5Yu4p0O016l2NXXdqggEDu4QtVVBbW//mGq4rEdvMmN/eE+B7eiak92t6EImk7KvIsuSt/nU24qy0st91fJCos2vroDRPQ47r7C3i1tUSvYFGe4y0gsMfOsxoWdajMt+/zhFtb5vvfJQ20sZPkoTaBUoKWr1jArl276NGjh9vhyPEoO2AJtYVbrI0t2WUTdkv2Wp+63irTnf1JMXX7IrFp/oQorfrVupVn+8+bas+r9tjnwve47ID/+8OiGyRN9YTE/pA4wO5jOrv3u0jbUXYAcr6A3C8h7zsb6y3aamO/nnAb9/MlFyQPtc9nfG87z5JjU1lg46uF27zFF7x99IKN/tUx47r7EznanQrtT4PEgbr+JSLHrKKigvvuu4+HHnqIyZMn89e//pV+/fo1/4bUH5a61B8WEZGGqkvh4Nd23nlwrb8YXWWBvR7TCZK9xdOSh9mck4Q+Nt4dFuVu7K1NTYV3jk+695zTW4ghb50dn8HmXfrOOVNGQvvR0O4UXScVEREJMBULEBERERERCX0qFgCAYwPUWZ9D9meQ/blVDsaxCVCpp0DKSf4CAQm9AZdWPgg1FblWPMB3O7jWLtDUVFgV/w5joONZdp86WsncbVlVie2ntReTNjaYNBpmCSiJA+sUA+jtTyLXRI7QUlPpXSFrR/1q5b6iJL5K75HJdkHXtypW0hArIhDfW8lmISo7O5t+/fpxyy23cP/997sdjjR0LCs4ecL9ydQxnbwruHfxruDUxb+ie0wXiEpx9/cSaai61Cajlu7zTkzNtM+3b9Wr0gzvCt676q/YHd2xzsTUXo0fx6Zp1W4JbpUF3klf33pX4PEWCCjZa69HJlp/LLF/46IAKr7XepXnNC4g4OuXl+6z74lM8q4g5C0ekDLcCi/GpbkbuwDw8ccfM3HiRA4cOECnTp3cDkcOpV4C1FbvbYuNi/gKFYXHWhsb38u7amaaTWquu2pmWLS7v4cEh5pyKN4NpXubODdLt8+Xr58ameQ9dtdJmFLilJyIygIrCpDzhbdAwBf2OQT7XKWMtPE7X6JG0mBdF2gJTo03mcObxFGwwQo35H1j12sik+waTfvT7JZ6mh1fRESOwsqVK5k7dy7btm3jl7/8JfPmzSM6+hj7peoPS3NSf1hEJHQ5VXYuk/MF5PzHzjnz1tnz0e2tIFqytxBdknfV++j2bkfdNpTn+AvW5a+3W+5XNr/HE2HXDdqfBu1Pt/PPlOH2vIiIiDQLFQsQEREREREJfW23WEDhZti/CPZ/AFkrbJXQiDgbbO4wFjqcCR3PtIQdaVnVZZC72oo2ZK2w+7IDVq059VToPBm6TrP/jy4KhKaSPXZBKHc1HPzKLhYV77QJi2GRNgEjaUiDJPDBqjItfmWZ/qISBRusAEzBBvtsgU0wThpsBWBSR9kF4dRTbOVnadXuuOMO5s+fz7Zt20hMTHQ7nLansgCKtnlXjN7qvd/mnWzXcAWnLg1W66mzunp8T1sdUMd5aQvKvStcFe+uv7pV8U67L91rRXLAEqljunhX7u7jnaTazztBtb+9JtJSyrPqJHh9aQUCinfaaxHx/lVhkn23oVawSdqWioP+ohG+VYLzv7P+OkBUO/t8pI7yJ54lDkAFGlvWokWLmDZtGgcPHiQlRUWYXFe8y/YTX2FNX6HE2gSoGH9iSr1klf7Wn9b+I83Csb5oU8l4TSVOJQ21MZaUETaRO66Hu+FLcCndBweW2i1rhV2bcWosgTPVl3juTUKPaud2tNJQTYUVefYVeMj9wsZanWpLkOxwBnSaCJ0nWhugAmAicghVVVU89thj3HPPPXTu3JnHHnuMc889t/E3qj8sQUH9YRGRVqOqBLJXeM87P7EFaqpLbe5H6qn+YmftT7PCxRJ8irbVv96U+xVUFdkcsNRTodN46DwBOpxlcztFRETkuKhYgIiIiIiISOhrO8UCKgsg4yMrDpCxyFajjkyGLpOg0wQrDtDuZK3UGayKtkP2Z5C5vM7/Lwm6eAsHdDnXEqak9SneWb8wQO5XVhwCj02uSD0VUk6yxO7kYXbxTvupHK/KAisg4CskcPBr++yV59hE1sSBlqiUeqq3gMCp1tZIq7Bve5lzvAAAIABJREFU3z769+/Pgw8+yC233OJ2OKGrPNtbEGCr/9732Jf45wm3yXC+RGZfMQCt4CRy7JwaKMuos7qVt5BA0Xb/PuibnBoR79/vfEUEfPdxPZS0IcevstD66r7JWjn/sVXWwPrn7U+z82lfYYD43vq8yeGVZ1vxgIL1cPAbb8GJb6w4SlSKf/KmbyJnXJrbEYe0hQsXMmvWLEpKSoiNVRG+FlOZ702A8q7a7EuIqsiz1+O6Q/JwSzSpu3qlEqDEdY4Vuira6k+eyvvWPsMle+1botpZolTycGh3kv+zHJnsbujSMsoyIfNjf4GAgk1WCLjDGTbBP/U0aD8aYru5Hakcr6oiyP3aCgdkrYDMT2x8NbqDN4nDWzwgeajbkYpIENq1axe33HILb775JvP/eg9XTumm/rC0MuoPi4i4qroMsld6zzmX2PWKmgqbU9R5ArQ/w8aVkwbbNWtpfZxqK1KX+wVkr7IxhrpjC50n2TlnhzGacyAiInIMVCxAREREREQk9IV2sYCS3bDrNdjzOmR9DtTYCjVdz7UE8w5jtGJta1W4xQo/7P8ADnxsk9MSB0LaTOh1KbQ/HU0UCULVpXYhJ+tTyPrMm6SdXSdJ+9T6q7xrwoS0lEZFK1Z7k569RSvanwYdz4ZOZ3snuap9CUZz585l8eLFbNq0iehoXRQ+IU61FebJ964AnPetd9Wcbf7JmmFRlgya2M+7glP/OknKfex1EWkBjk1CbVi8w3dfWWDfFhZt+2Zi/zorvQ+D5CG2ModIXaX7bJLdgY9t0l3BRjs2xHb1r/rqS+KObu92tBIqasrh4Jo6RSm+gMJNVjQltpud53eeYAUftWpts/rXv/7FxRdfTFVVFeHhmkAbEBUHIWeVTV7O+cL618U77bXIJG/iyIg6SSQjtLq2tE4VufWLYOR9C/nr/H3S+N72+W5/mrXr7c+wIjHSujnVNta79y3Y/z7krbOEjPaj/UnjWv0vtDk1ts/7CkRkfmpFcWK6WMHn7rOg63QVZRVpy5roD7+9fCfnDIakJPWHJYSoPywiEhhF22DPm7D3HVtoprrMChn7zjk7T1RBulBXe93Ke95ZtMOub3YcC93Og+6z7TMhIiIih6RiASIiIiIiIqEv9IoFlO6zAgG7XrUJalHJkDYLun0PukxRIkMoqqmw1Wv2fwC7X4fCzXahveclVjggdbTbEbZdlfnelYWWQdYymwBUU2ErS3c827sC6am2CmlkotvRitRXsseKBuR+ZZPYsj+zVXWjO0DHs2yVrI7jrLCFCs+4bvPmzQwbNoy///3vXHPNNW6H04o4lqSUv84mr+Wv8942WIEXPJDQ2xKKkwZ5iwJ4iwPE99RqDCKtQVlm/UIChZuhYIPt5zUVlmyb0NcmYicP9a54NdRWXFHRj7ajLMMKAxxYaveFm/0rtHQc51/lPa6725FKW1NZ4C3q9YWN8WQt865a2x46nWOTQDtNhJRhqKDX8XvppZe4+uqrqaqqcjuU0FBT6S184U2Gyl5lhbdwbLyqwxmQMtKOuSnD7TmRUOcrRpf3nX//KN4JeCBpoHfVv9P9+0dYpNsRy5FUlUDGYm+yxttQnmXnEGnn2fG54zka723LnGrrwx1YagUkMpfZuWfnidD9Akg7H+LS3I5SRAJF/WGRxtQfFhE5Ro7N1dj9Bux909rPqFToNgO6TLWisvG93A5S3FScbuecGR/CvvesOFXKCCsa0H22LVSjawYiIiL1qFiAiIiIiIhI6AuNYgEVByH9JW+BgOUQkWADvz0vha7nKsmlrTm4xj4LO1+1xKiEvvZZ6Hs1JA1xO7rQVlkIBz7yrh60zFZMcKrt797Juyp7x3MswVSktXGqrH3JXGarY2Uth/JsO+Z0HGsFMLpOtWQ6rXLa4ubOncunn37K+vXrtRrqoVQW2KSKg19D/nrvijbroarIXo/r4U0UHg5JvoThIfYZF5HQ41RZ8YB6hULW2eTtmkorhJPY39qE5GGQcpI3WbyH25FLc6gqsmJrGR9ZcYCCDTYJOfU07yo8E6DDWK3+KsHHqbE+zIGlkOk976w4CNEdofN4+/x2O08TRY/RU089xR133EF+fr7bobROZZn2mcz+3JKhDn5tq5tFpXhXijzdv2JkTCe3oxUJHmUH/AmEOf+xW2U+hMdAu1MsUarDmdBpgvadYFFZCLv/DXtet0IB1WXWtnWfbQngSYPcjlCCVUWurQC6500rHlBVAu1H2+em12Va/VGktVN/WOT4qD8sIlKfUwOZn8Cuf8Let6Bkr43z+pK/O52jRRykaU4VHPjEW9DwTSjeZcWv02bZQkOdztEcHhEREVQsQEREREREpC1o3cUCclbBlsdh5wJb2bb7LG+BgGl2EVUkd7W/cEBxuq0EPuB66HEhhEW7HV1oKNgI+961W+YyuwjT7mRLnO50jq1EqgkMEpIcW5U5a5m3gMAnULLHEpW6TYdu37OCNVGpbgca8rKysujZsycPP/wwN9xwg9vhBIeqEpuUmfsl5Hxp94WbbZJFTGd/8m/yMP/jyGS3oxaRYFBTAQWbrJhI/nf+4iJF2/xtSOpoS+xIHW0FBGI6ux21HI2SPbB3Iex5yybxO1X2P+w8wbv661kqECOtj1MNB9dC5sfeAgKfWoGkdiNtxdq0WdZeaQWhw/r973/P448/zo4dO9wOpXWoyLPzvwNL7Ja3zsYl2420BKgO3hUhkwahz57IsXBsnDHbmyiVs8raeKfazls7T/Lexuv8tSU5NXac3f6cFQqoqYIuk73JGrMgpovbEUprU11mKz/uedMSgMqyrMhw3x9Bj4shMtHtCEXkSNQfFgkQ9YdFpI0q2gbbn4cdL0DxTptv5CsQ0O4Ut6OT1ij3K3/hgINrIb439Lka+v5QxepERKRNU7EAERERERGR0Nf6igVUFsLOl61IwMGvbcXyvj+E/tdBVDu3o5Ng5dTYhJWtf4c9b0BEvF0IGHQLJPRzO7rWpbrMVlTP+NASjQo2WDJ0l8nQZYolZMR2dTtKEXcUbbckvL1vW6KSU20Xs9Nm2r6ReiqaHNf87rvvPv7yl7+wa9cu4uPj3Q6n5TlVltibu9p/y/nCEn4jk20SWeoo/y15mNsRi0hrVFUEB9fUb2sKNlo/O7Zr/XamwxgrniPuy19n/ZK9CyHrM4iItUnFaecruUtCk1Ntq1nufRt2v27FknzFvNLOh24zVBSjCXfffTeLFy9m9erVbocSnKpKIPszGwvJWmGJUTWVNrG0yxTvbaqtnCoizauq2Nr1jA/tdvBrwOMtVHqWFSntOg0ik9yONPQU77LrMFv/buNdyUNtPL3fj9XXl+bju26z4wXY/S/7Ou186HOVFWL1hLsdoYiA+sMiblJ/WERCVWWBzd3aMR8yPoLYLrYCfN9rrI0TaS4FG2wRqu3P2lhH6iibY9rrBypWJyIibY6KBYiIiIiIiIS+1lMsoCwTNvwBtj5hq9f0uhT6Xw8dznQ7MmltSvbCtqdg25NQuh+6nQfD77FVUaVp1WWw711IfxH2vQfVpXaBrtsM+/t1GKOJeyINVebD/sW27+x7D8oyIK6HXeTufbldhJQTVl5eTu/evfnJT37CAw884HY4LaOyELKW2aTMzE+tMr6vMEDqKP9q36mjIaGP29GKSCirOAi5X0LOl3af+6VNtAFIHGCrQ3aaAJ3GQ3xPV0NtUwo2wPYXYOdL9v+I626Fi7rPhs4TISza7QhFWs7BNVYsY89bVuQkIs72hT5XW0KLzmMBuO6669ixYweLFy92O5TgUbLbJizvfsOSomoqrGBpl0nWlnaaANHt3Y5SpO0pz4YDH8OBpZZgXLARwqKs39n9+9bGx3V3O8pWzLFxrA3/a3/n2C7Q+0pb8T15qNvBSairyIX0l2HH81YEM6EPDLwF+l+rYk8iblB/WCQ4qT8sIq1d4WY750z/h7dY2CxbIKjrNI3VSmA5VbD/A9j+HOxZCGERVqhu8O12TVNERKQNULEAERERERGR0Bf8xQLKMmD9H2Dr4xCRCEPugH4/sZXMRU6EU2UXANY/CDn/sZVqRtwL7c9wO7Lg4FTbZIP0F2H3v6Gq0Cb/9LrM/lZxaW5HKNKKOJbQvectS9wr3ApJg6H3D6DX5ZDY3+0AW60XXniBuXPnsmPHDrp16+Z2OIFRWWDFAQ58YgUCcr+yNjp5iLXLHc+yAgGJAwCP29GKSFtXlmlFA7JXQebHdl9TbokenSZA5wne4gG9XA40xFTkws5XrEhAziorUNTnKuhxIaSeio4PIljhwL1vwo4XbVXMuDRLgOxzdZtPgLzkkkvweDy8+uqrbofirvx1/oSo3NW2slS3GbbCceeJEBui5xsirVnpPluBcO/bsP89qCyy8+Pu34ceF1hSoxxZTYWNAW/4X8hfb0kag36mZA1xT/462PIEbH/GEiAH3AADfwaxXd2OTCS0qT8s0vqoPywirUX2Zzb3b+9bkNAXBv0X9L4Cotq5HZm0RRW5sOMfsOkRKN4B3S+AIXdqwSoREQl5KhYgIiIiIiIS+oK3WEDpPlj/EGz9O0SlwJCfQ//rbBU4kea27z347n7I/hy6TreiAW31IkDuapscunOB7Yepo+wiXa85mggk0lxy/gPpL9l+VpZhRUp6X277WUxnt6NrVc4991zi4+N5/fXX3Q6l+VQWQOanVhigtjhAjSWx+ZJsO42HmE5uRyoicmTVpZC90tqzA0vtGFhdBvG9ofN46DTR2jYVDzh2TpWdx2x/3iYEh0VYcYA+P7RJ/J4wtyMUCV6Fm624Rvp8KN4F7U+zogG9L2+TxSmnTJlCv379eOKJJ9wOpYU5doza8wbsfh0Kt0BMF+g+C3p839rSsGi3gxSRo1VTbolSe96wYo1lByBxoO3P3S+ADmegAkoNVOTB1idg05+hPMeKWg6+A1JGuB2ZiKnIhS1/g02PQsVB6HOFfUbbeKEnkeaj/rBISFF/WESCjVMDe96EDX+0YgEdxsCQedYm6fqFBAOn2vrBG/5ohbg7jrOiAWnn6zMqIiIhScUCREREREREQl/wFQuoqYQtf4Vv7oHwWBh8Owy6xR6LBFrWcvjm/8GBJZA2E077q63KGepqKuwi3cb/s4t08b2g12XQ9xpIGuR2dCKhy6mxfW7HfFsNuLrULo4P+i9bLV4OKzMzk7S0NF566SUuueQSt8M5MUXbYe9CS/bM/NTa5YS+0GWKfRY6T4K47m5HKSJy4pwqOLgWMj60W9ZyKx7ga/PSZkLXczUZ/XCqimDb07DxYSjeacW9+l8HvX5gq/6JyNGr1x9/GaoroNelMOyXkDTY7ehazJAhQ5gzZw733Xef26G0jNL9sOMF2PYUFG61AjbdZ3lXTJ0Angi3IxSRE+XUwMGv7Tx75wIo2GhjvL0vhwE/VaGqmkrY/iys/TXUlNkY8JA728Y4uLRONRU2drr+95C/AXpeDKf8QfuyyPFSf1gk9Kk/LCJuO7AUvroD8tZCt+/Z/IcuU9yOSuTQspbDpkdg97+h3Ug45X+tbywiIhJCVCxAREREREQk9AVXGdQDH8N7J8OaX1g14dk7YehdKhTgglmzZuHxeHjggQfcDqVldRwHkz+C8Qshfx28M9wS6J0qtyMLjLJM+O5+eLM3fHYFxPeAc1fA7HQ4+UEVCmiFHMdhxYoV3HTTTQwcOJDo6Gg6derEuHHj+Mc//nFUA31tdv93gyfM2p3Tn4ALM+D0v9vkvMXjYNFYm8BTU+l2lEHr5ZdfJjY2lpkzZ7odyrFzqq0wzZc3Wxv8Vj/47gFbuenM5+CiTJi1zT4bfa5WoQBpMVVVVTz99NOcfvrptG/fnnbt2jFq1CgeffRRKioq6n1vcxxzpA3yRFhy+9C7YNJiuPggTPrQVrjKXAafzIJ/dYRlF0P6i1CZ73bEwaN0P6z9JbzRE9b+CrrPtmPF9C+tWIAKBYSEgwcP8vjjjzNp0iRSU1OJjY1lwIABXHHFFaxdu9bt8EJP3f749/fBqX+ErBXwzjBYfomtJhTiHMdh165d9O7d2+1QAqum0iZ6fjwT3uhhq0WlzYTvrYXZO2DUn23CshKj2pR3332XgQMHEhFxbP93jZu0Ap4w63OOuA9mboAZa6DHhZYU+VY/+OR8W3G1LY657P43vDMUVt8K/efCBXusDVShgIA5lrZmzZo1nHfeeaSkpJCYmMiUKVNYsWJFC0QZ5MKibHzse9/CWS9BzhfWX/v2Pqgqdjs6kdZB/WE5Ao31hhj1h0XELQWb4NPZ8NEkiO0K3/vG5l+pUECLOprz0McffxyPx3PY24wZM1owapd1HAfjXrVjZnQn+GgifPp9KNzsdmQiIiIiIiIiIiIiRy04igWUHYDPrrKLBfF94LzvYPg9EB7jdmRt0gsvvMDChQvdDsNdaTPhvHVW3XrN3fD+aFttMFQcXAMrr7FEo01/hr4/glnb4axXoMNYt6OTE7Bp0ybGjRvH5s2bee2118jPz2flypX07NmTq666innz5h3257X/uyg81vbFGV/BlE/s4vlnV8BbfWH9g1CR63aEQeeVV17hwgsvJDa2lRQVqqmE/e/Dqrnw7y7w0WSrUN/napi2Ei48AGPn28rQ0R3djlbaqGuuuYZrr72WKVOmsGHDBrZu3cqcOXP42c9+xkUXXVTve0/0mCMC2Dlfl8lwyh9h5nrrk578oCV8rPwx/KszfHwebHum7R4LCzbAqmvhzT72dxhyB1ywyybyJ/R1OzppZvPmzeNnP/sZs2fPZv369eTk5PDMM8+wZs0aRo0axRtvvOF2iKErIgEG3gznb4azXobinfDBGPjwHFuJj9BMjMjMzKSkpIRevUJ0VcGCDfD1nfBGdysA4VTZ//f7e+DUhyHlJLcjFBds27aNWbNm8Ytf/IIDBw4c089q3KSVajcSRv0ffH8vjH3RVilfdpElS349z5IZQl3ul3ZMW3YxtD8DZm6Ekb+FyCS3IwtZx9rWrFq1irFjx5KYmMiGDRvYsWMHffv2ZcKECSxatKgFIm4FPGHQ6zJLehx+jxV6XjjQzpOcGrejEwlO6g/LUdJYb4hTf1hEAq08B778Gbw7AorSYdIimPAOJA9zO7I25UTGvJoydmwbnD+WMhwmvgcT34eirbbI0Or/ss+4iIiIiIiIiIiISJDzOG6Xgd+/CD7/IYSFw8j/sYQ5cc2+ffsYPnw4M2fOZP78+dx///38+te/djssdxVutYta+z+AQT+DU/5gK9m0Rvnr4Nv/hl2vQeIAGHgj9JsLEXFuRybNZOPGjYwYMYLMzEzatWtX+3xFRQXdunWjqKiI/Px8oqOjG/2s9v8gVLoPtv4dNv3FJu4MvAmG3g1RKW5H5rqcnBw6derE66+/zqxZs9wO5/Dy18GO+bD9OSuQlDwUel5ik5uTBrsdnUit7du3069fP0455RS++uqreq+de+65LF68mP/85z+cdtppwIkdc0SOSkUeZCy2JN3dr0N1KXSeCH2ugh4Xh34ftmQPfHc/bHsa4nvbuUj/66zAkISsa6+9lvDwcJ544ol6z69du5aTTz6ZAQMGsHmzVrJpMVnLYf3vYe87tiLfKb+HzpPcjqpZrVq1ijFjxrB9+3b69OnjdjjNp+7/Lq4b9L4S+l8PCSH0O8pxu/zyyznppJO488476d27NxkZGVRVVR3x5zRuEmJK9kL6P2DrE5bI0GUyDLoF0s53O7LmVV1q48Eb/gipo+HU/4WOZ7kdVZtwLG1NTU0NJ510Erm5uWzbtq22MGZ1dTXDhg2jpKSELVu26Py6ofIc+O43sPmv0P40GPMsJA1yOyqR4KD+sBwjjfW2QW2lPywigbfrn/DFTYADw39tBVk94W5H1SYdy3no448/zvvvv99kgeItW7YwYsQI0tPT6dKlS6DDDl5OjR0rv74LqIHRj0HPi92OSkRE5Li9+uqrzJkzB7fTRkRERERERCRwwlzbslNllVeXTodu020lGxUKcN3cuXO55JJLOPfcc90OJXgk9reqwac/AduegsXnQMlut6M6NsU7YcUP4N2TrPjB+Lfg/I0w6L9CP8mqjRk8eDCVlZX1JvIAREVF0aNHD8rLyykrK2vyZ7X/B6HYbjDiPrhgJwz7hRUOeKsfbPiDFQ9ow5YsWYLH4+Gcc85xO5SmlWfZZMy3h1i1+T1vWpLn7HQ4b539X1UoQILM7t3WvxkyZEij1wYPts/rrl276j13vMcckaMSlWLFVc58AS7cb4kfeGDlj21FvC9+CgfXuh1l86sqgTW/gIUDrFjCmS/YSueD/kuFAtqAp556qlGhAICRI0cSGxvLtm3bdPG+JXUcB+MXwoyvILo9fDQZPv4eFG5xO7Jmk56eTnh4ON27d3c7lOax7x344AxYfDZU5sP4N2H2Ljj5QSVGSa2nn36au+++m4iIiGP6OY2bhJi4NBh6F5y/Fc7xFqb6ZBYsOhP2ved2dM0j5wt4d6QlgJ3xFExbqUIBLehY2ppPP/2UdevWcfHFF9cWCgAIDw/nBz/4Abt37+btt98OZLitU3R7GPVnmP6F7cPvnwqbH3U7KhF3qT8sx0ljvW1QW+gPi0hgVeTB8kth+Rzo8X2Ytc2uY6hQgGuO5Ty0f//+nH322U2+9pe//IULLrigbRcKAPCE2VzW8zdaMZ3ll8KKy6yfLSIiIiIiIiIiIhKE3CkWUJ4DS6bZColnvWhJHxEJroQifs888wzr1q3jj3/8o9uhBKf+c2H6aqguhvdPg6wVbkd0ZL6Vo94ZCrlfwVkLYMZqSJsJeNyOTlpQXl4eW7Zs4ZRTTiE5ObnR69r/g1xEAgz7JczeAQNvgm/vg3dGwL533Y7MNUuWLGH06NGkpKS4HUp92Z/DZ1fB6z1g/YPQZSpM+w/M3ADDfgXxvdyOUOSQBg8eTGRkJBs3bmz02saNG/F4PIwYMeKI73OkY47IcYlIgD5XwaRFcMEuOy4e+BjeOxkWnQXpL0JNudtRnri9C63vvvVxGPk7K6rX+3KbkCRtWnFxMaWlpQwfPhyPR+dyLa7dyTDxfZj0oa289+5J1ievbv2JEunp6aSlpREZGel2KCcm8xNYPA4+Ph9iu1pC7JRPbRKn2lBpoG4i7tHSuEkI84RB99kwdTmc+xlEd7TCMIvPhsxP3Y7u+G3+i7WLCX3ge99B3x+5HVGbcyxtzZIlSwAYPXp0o9d8z3300UfNE1goaneyjb8NmQerb4Xllyh5Q9oe9YclQDTW2waEan9YRAIr90sr1pX9mV23Of0JiExyO6o271jOQ6dMmcIdd9zR6PnCwkKef/55brzxxuYMrXWLTLYijBPfs2Pje6NsDp6IiIiIiIiIiIhIkGn52QHFO2HRWCjaBlNXQK8ftHgIwSonJ4fbb7+dfv36ER0dTffu3ZkyZQrPPfccpaWlAJSXl3PvvfcyePBg4uLiSE1N5fzzz+ett96iurq69r2qqqpYsGABU6dOpUuXLsTGxjJixAj+/Oc/U1NT02jbe/bs4Y477uCZZ54hMTGxxX7nVidpMEz9DDqcYSsK7v632xEdWvZn8O7JtgL5kHlw3jfQ82JUJCB4BGp/rqugoIAVK1Ywa9YsunTpwgsvvNDoe7T/tyKRyXDSb2DmZmuHPp4Jn5wPpfvcjqzFLVmyhMmTJ7sdhpdjyZ2LxtqtYD2MfgQu2GP37U9zO0AJQYE4hnTu3Jk//vGPrF27ll/+8pdkZWWRm5vLQw89xIcffsi9997LwIEDDxnT0RxzRJpFbDcYcqcVYpn+JST2g5XXwBs9LXm3Is/tCI9dRR6suNxW7+p4lv1ug2+FsCi3I2uz3Dw/b8o///lPAH71q181/y8rR6/LZCvAd9IDsOF/4b1T4eDXbkd1Qr799luGDRvmdhjHr2QPfH41fDjBvp7yCZzzBrQ/w9WwpHm0ZDt7OBo3aUM6nAnj34JpqyAqBT4cb+MuRTvcjuzo1VRYu7j6Nhh+D0x4z1aNlUMKhrbGV7Sve/fujV5LS7P/3+bNm09oGyEvLBJG3AeTFkPmcltZvWib21GJBJ76w21SsFxflBAUCv1hEQm89Bdh0ThI6A/Tv4IuU9yOKKgE27WFY/Xss8/Ss2dPzjnnnIC8f6vWdRrM+BoSesPis2DnK25HJCIiIiIiIiIiIlJPyxYLKNhkqxpExNqKBu1Gtujmg1lGRgannXYaL7/8Mn/+85/Jzs5m9erVTJgwgWuuuYYnnngCgJtvvplHHnmEv/zlL+Tk5LBhwwYGDx7M7NmzWbZsWe37vf/++1x22WVMmjSJDRs2sHv3bq677jpuv/127rrrrkbbv/baa7n88suZNGlSi/3OrVZkIpz9OvS/FpZfCtufdzui+qrLbPWcxWdD0kCYuckmyYVFux2ZNBCo/dnngQceIDk5mXHjxhEeHs7rr7/O8OHDG32f9v9WKC4NznwBJn0Aed9aYZDdr7sdVYs5ePAgmzdvZty4ce4G4tRA+j/gneHw6QUQ0wnOXQHTV0P/6yAi3t34JKQF6hhyyy238PLLLzN//nw6depE+/bt+cMf/sBTTz3Ffffdd8h4jvaYI9LsUkfZMXF2uq2WuvFheKsPrP116ykakPkpvDcSMj+GCe/C2BchpovbUbVpbp+fN3TgwAHuvvturr32Wi699NKA/d5ylDwRMOQOOG8dxHaBD8bA+ocAx+3IjsvatWsZObIVjs/VVFiBmIUDIedLW8Fs6nLodLbbkUkzaql29kg0btIGtT8dxi+EiR9A4VZ4Zxh89xuoqXQ7ssOrOAhLpsKeN2HCOzD811pN+igEQ1uTl2fnLvHxjceSEhISABsPk6PQeSLM+AoiEuGDMyF7pdsRiQSG+sNtWrBcX5QQ1lr7wyISeN/dD59dBYNuhonv2/VxqRVs1xaOleM4PPbYY9x4442DUL20AAAgAElEQVTN/t4hI6azHR8H3GhFwNf9zu2IRERERERERERERPycllK8y3Fe7+E4H4xxnPLcFttsa/GjH/3IAZwFCxY0em369OnOww8/7DiO4/Tp08cZO3Zso+8ZOHCgs3Tp0tqvFy5c6EyYMKHR91155ZVOZGSkk5+fX/vc3//+d6dv375OUVFR7XPz5893AOf+++8/kV8r9K35heO8FO44u15zOxJTlO447412nFeTHWf7825HI0cQiP25ofLycmfDhg3ODTfc4ISHhzu/+c1v6r2u/T8EVOQ7zqq5jvOix3G+usNxairdjijgli1b5gDOzp073Qti/2LHefcUx3kpwnE+u9px8ta5F4u0SYE4htTU1Dhz5851IiMjnT/96U9ORkaGk5WV5TzxxBNObGysM2fOHKey8tBtzJGOOSItovyg43z3gOO81sFxXmvvOBsedpzqcrejOrTNf3OclyMd55MLHKcsy+1oxMvN8/OGsrOznZNPPtmZM2eOU1VVdRy/jQRUTbXjrH/I9uNllzhOZdGRfyaIlJWVOZGRkc7LL7/sdijHJu8764svSHCc9X9wnOoKtyOSAGmJdjYtLc0JDw8/5OsaNxGnutxx1v3ecRbEO857pzpO/nq3I2paRZ7jvH+a47ze3XEOfuN2NK1KMLQ1U6dOdQBn5cqVjV7bvHmzAzijRo06wm8i9VQWOc7HMx3n1UTHyfrM7WhEmpf6w21eMFxflDaktfSHRSTw1vzScV4Ks+sa0qRgurZwpPPQprzzzjtOYmKiU1hYeEw/12ZtetT2ibX3uh2JiIjIUVmwYIHTkmkjIiIiIiIi0vJaZlmZykJYOh2ikm2lxKh2LbLZ1uT1121F6BkzZjR67b333uPWW28FYPr06Xz22Wdcd911rFy5kurqagA2bdrEhAkTan9m5syZLF26tNF7jRw5ksrKStatWwfArl27mDdvHs8880yTq9bIEYz8HxhwA6y4ArKWuxtL1gp4fzTUlMP0L6DP1e7GI0fU3PtzU6Kiohg8eDB/+9vfmDVrFvfeey8ffvghoP0/ZEQmwel/h7EvwJa/wZJzoTLf7agCav369SQkJNCjR4+W33jJbvjkfFupLy4NvrcWznwekoe2fCzSpgXiGDJ//nyefPJJbrjhBm677TY6d+5Mhw4duO6667j77rtZsGABjz766CFjOtwxR6TFRKXAsF/BrK3Qby6s/SW8PRQyFrsdWQMOrL4VvrgRht8D5/wboju4HZR4uXV+3lBxcTHTpk1j6NChvPjii4SHh5/orybNzRMGQ+bBxEVwYCl8eA6UZ7kd1VH77rvvqKys5OSTT3Y7lKO37Skb+wiPgRlfw5A7ISzS7agkQFpi3ORwNG4iAIRFwdCf20rlnkh4bxRse8btqOqrLoWlM6B0H0xeCikj3I6oVXG7rQFISUkBrP/XkO853/fIUYqIh7P/DZ0n2fXJg1+7HZFI81B/WHD/+qK0Ma2hPywigbfut7D+QTjjaZsjJU0KlmsLx+uRRx7h6quvJiEhoVnfN2QNvAlOfxLWPQDrf+92NCIiIiIiIiIiIiK0TLGAVT+B8hyY8J4KBTShvLyc/Px8YmJiSExMPOz3PvbYY7zwwgts376dyZMnk5SUxPTp02svOPjk5+dz7733MmLECNq1a4fH48Hj8TBv3jwASkpKAFi4cCH5+flMmDCh9ns8Hg9XXXUVAPfcc0/tc1u3bg3Abx8CRj0C3abB8jlQlulODPs/gKXToONZcO7nkDjAnTjkmDT3/nwk559/PgBvv/02oP0/5PS+EqZ+BgWb4KNJrSpJ6Vht2LCBoUOH4vF4WnCrDmx5HN4ZDoVbYfISGL9QRQLENYE4hrz//vsATJkypdH2Jk+eDNhElqPR8Jgj0uIik+Hk38H5myD1VFgyDVZdCxV5bkcGTg385wYr8jPuFSsWQEse0+Rw3Dw/r6uqqopLLrmEtLQ0nn/+eRUKCHadJ8C0VVCRDx9OhLIMtyM6KmvWrCE2NpYBA1rBGIJTBav/C1ZdZwlRUz+FxP5uRyUB1tLjJg1p3ETqSRwI5y6Hwbdav/KrO8CpdjsqwIGV19h40KSP1DYeB7fbGoDBgwcDsGfPnkav7d27F4CBAwce9/u3WWGRMO5VaH86fDK71fTRRJqk/rDU4fb1RWmjgrY/LCIBt+ufsPYeGP0o9P2R29EErWC5tnC8Nm/ezKJFi7jxxhub7T3bhH4/hlF/tuLlu//tdjQiIiIiIiIiIiLSxgW+WMC2p20w9KyXIK57wDfXGkVHR5OcnExZWRmFhYWH/V7fhNQPP/yQvLw83njjDRzH4cILL+RPf/pT7fedf/753H///cydO5fNmzdTU1OD4zg8/PDDADiOA8BNN92E4ziNbvPnzwfg/vvvr32uf39NOmmSJwzGPG+reKz6Sctv/8BS+GQW9LwYzn7NVsyRVqG59+cjiY6OBiA3NxfQ/h+S2o2EqcstSemjKVCZ73ZEAbFt27aWTWiqKoJlF8GXP7MJENNXQ+eJLbd9kSYE4hjS1AqGDRUVFR1VfA2POSKuiethySHj34L978O7IyD3S3dj+noebH/e+u49L3U3FmnEzfPzuq6//nrKy8t59dVXiYiIqH2+f//+rFy5spl+W2lWCX1hyidQU2kFSioP//kJBl999RUnnXRS8BejcKpg+WW2iuq4V+Ck+8ETceSfk1avpcdNGtK4iTTiiYCR/wNnvWiFn1Zcbm2Umzb+n11/Ofs1SBrkbiytlNttDcDEiTbOtHr16kav+Z7zFfGTYxQWZeeE4bHWn3Bq3I5I5NipPywNuH19UdqwYOwPi0hgFW6GlT+CQT+DAT91O5qgFizXFo7XI488wjnnnMPQoVos4ZgNvBn63wCf/xCKtrkdjYiIiIiIiIiIiLRhgS0WUJ4FX/8cBt0CnScFdFOt3fe//30A3n333UavnXLKKdx2220ApKSksHHjRgAiIyOZOnUqb7zxBh6Ph3feeQeA6upqVqxYQZcuXbjlllvo2LFj7erLpaWlLfHrtD1RKTDmGdj7Dux6reW2m78ell0IPb4PY57V5KBWJhD785133smVV17Z5PZ8q0Gfdtppgfh1JFgk9IEpS6E82xLcayrdjqjZZWdn07Fjx5bZWNE2+OAMyPocpn5iVeEj4lpm2yKHEYhjyBlnnAHARx991Oi1JUuWADBmzJja53TMkVYlbSbMWGMrYH04Hna96k4c256BjQ/Dmc9C2vnuxCBH5Pb5+X333ce6det48803ayfkSysRlwaTFkPZAfj8yqBPRluyZAnjx493O4zDc6rhsyut4MvED1RkpY3ROKgErV4/gInvwb634bOr3WvvCzbC2l/B8HtV1PAEBENbM378eIYOHcprr71GWVlZ7fPV1dW88sor9OjRg/POO++Et9NmRbWDcQsg+3PY9Ge3oxE5NuoPSxN0fVFcFyz9YREJLKcaPv8RJA2GU/7odjStgtvXFo5XQUEBL7zwAjfddFOzvm+bMuphSOxv+4yOiyIiIiIiIiIiIuKSwBYLWPc7W219xH8HdDOh4He/+x19+vThtttu45133qGwsJA9e/Zw4403sn///toLBgA33HAD33zzDeXl5WRmZvLQQw/hOA6TJllBhvDwcCZMmEBGRgZ/+MMfyM7OprS0lKVLl/L444+79SuGvk7joe8PYc3dLVNBv6YcVlwGycNgzHOAJ/DblGYXiP35pZde4je/+Q3p6emUl5eTnp7OXXfdxT/+8Q9GjRrFtdde25K/orghrgdMeAeyV8J397sdTbPLyckhNTU18Bsq2gEfToDwOJj+JXQYG/htihyD5j6G3HjjjQwYMIC//e1vPPLII2RmZpKTk8PTTz/Ngw8+SFpaGnfeeWe9n9ExR1qV6A4w6QPody2s+AGkv9Sy2y/cCqt/BkPvsgm1ErTcPD9/7rnn+O///m9WrVpFYmIiHo+n3m3bNq1KE/Tie8I5r8O+92yVvSC1f/9+Nm7cWPtZDVrf/jfseRPGvw0dx7kdjbhA46AStDqNh/ELYfe/3Rt7+ep2S9oYdrc72w8hbrc1YWFhPP300+Tm5nLNNdeQkZFBTk4ON910E1u2bOHJJ58kJibmhLfTprU7GYb/Cr65F8oy3Y5G5OipPyyHoOuL4rpg6A+LSGDteAFyvrD5SGGRbkfTKrTWuX/PPPMMCQkJtcUO5DiERcGZz9scnfR/uB2NiIiIiIiIiIiItFVOoJRlOc6CeMfZ8HDANhFqsrOznVtvvdXp06ePExkZ6XTt2tW57LLLnM2bN9d+z5o1a5zrr7/eGTJkiBMXF+ekpqY6Y8aMcZ588kmnpqam9vuysrKc66+/3unRo4cTGRnpdO7c2fnRj37k3H333Q7gAM6oUaMaxXD99dfXvl73Nm3atBb5G7R6hdsc56UIx9nxj8Bva80vHefVRMcp2hH4bUlABGJ/zs/Pd5566iln2rRpTu/evZ2oqCgnISHBGTVqlPO73/3OKSkpOWQ82v9D0Ka/OM7LkY6T+5XbkTSrDh06OI8++mhgN1Ka4Thv9nGc90Y5TkVeYLclchwC1SfMzc115s2b5wwePNiJjo52oqKinH79+jk333yzk5GRUS+GEznmiLju659bv33Pwpbb5keTHeedkxynuqLltinHza3z8/POO6/JPnnd2+eff97ifw85Dmt+ZefsxXvcjqRJ8+fPd6KiopyioiK3Qzm0/Ysc56Uwx9nyuNuRiEsC1edduHDhIdvYJ5988pDxaNxEmrT5MWurMpa07HYzlznOi1hbKSckmNqar776ypkxY4aTlJTkJCQkOJMmTXKWL18e8L9Bm1FZ7Dj/7uo4q29zOxKRo6P+sBxCsF1flDbOrf6wiARWdbnjvNHLcVZd53YkrY6bc/+O5zy0pqbG6d+/v3PvvfcG7o/Slqz8ic0z0bVAEREJQgsWLHACmTYiIiIiIiIi7vM4juM0V+GBejY/Cmt/Cd/fDxHxAdmESFBafgmU58DkJYHbRtkBeLMPnPwgDLolcNsRkVbOgUVnQXR7W90jRMTExPDkk09y1VVXBW4jn86GvHUwbZX9/UREJPSs+gnseQvO+xZiugR2W5mfwofjYepy6HhWYLclIsGhugzeHgQ9LoRTH3Y7mkZ+/OMfs3XrVj799FO3Q2maUw3vngRJg+Dsf7sdjYjI4X06G4q2w4w14AlvmW2uuByKd8C5n7fM9kRCxYY/wncPwIX7ITzW7WhEDk39YRFpTdzoD4tIYO1+HZZfDLO2Q3wvt6MRaT2KdsDC/nD269B9ltvRiIiI1PPqq68yZ84cApU2IiIiIiIiIu4LC9g77/onpM1SoQBpe3r9wJKByg4EbhubH4XIZOg/N3DbEJEQ4IHh98DedyDvO7eDaTbh4eHU1NQEbgM7F8Det+HM51QoQEQklI16xPrUX7ZA8a1N/wedzlahAJG2JDwGBt0GW5+CygK3o2lk6dKlTJ482e0wDi39RSjcAic/5HYkIiJHdvJDkL8Rdr7SMturKoI9b0Dfa1pmeyKhpM9VUF0Ce0OnsKqEKPWHRaQ1aen+sIgEXvp86DxJhQJEjlVCH+g80fYhERERERERERERkRYWmGIBNRWQvQq6TgvI24sEtS5TAQeyA7iq0+5/Q58rtfKNiBxZt+kQ1x32hM7qQxEREVRWVgZuAxsfhl6XQcdxgduGiIi4LyIeTvm99a2LdwZuOzXlsP8D6PPDwG1DRIKTLxntwBK3I6nn22+/JT09nalTp7odyqGlv2hFSBP7ux2JiMiRJQ2C7ufDjn+0zPayP4fqUkib2TLbEwklMZ2h/elwYKnbkYgcnvrDItKatHR/WEQCzIEDn2hVdJHj1W2m95xTqzaLiIiIiIiIiIhIywpMsYD8DZYQkXpqQN5eJKhFJkLiQMj9OjDvX7oP8tdD1+mBeX8RCTEeK96T8ZHbgTSbyMhIqqqqAvPmBZsgZxX0vz4w7y8iIsGl+2yI6WST8AMlexVUlXiLiolImxLdHtqdGnTJaK+88go9evTgzDPPdDuUplWV2N+sx4VuRyIicvR6XGjFYapLA7+t3NUQ3xNiuwV+WyKhqP0ZkPOF21GIHJr6wyLSGrVkf1hEAqtoO1TkWpEtETl2Hc6A8hwo2uF2JCIiIiIiIiIiItLGBKZYQNkBu4/rHpC3Fwl6cWn+/aC5FafbfdKgwLy/iISepEH+tiMExMTEUFZWFpg3z18HnjC7gCsiIqHPEwHtT7NiXIFSsgvCoiG+R+C2ISLBK2kgFO9yO4p6/vnPfzJnzhw8Ho/boTStZDfUVELKcLcjERE5esnDoabC2rBAK90PcT0Dvx2RUBXXw/YjkWCl/rCItEYt2R8WkcDy9ZV13ilyfHz7js47RUREREREREREpIUFplhAVbHdR8QH5O1Fgl5EIlQWBOa9K/LsPiolMO8vIqEnKhXKc92Ootl07tyZjIyMwLx5WYb9vcKiA/P+IiISfGLToHRf4N6/Ig+ikoEgTcoVkcCKagcVB92Ootbq1avZsmULc+bMcTuUQ6vIsfuoVHfjEBE5FtEd7L48O/DbqiyEiITAb0ckVEUmBe76jUhzUH9YRFqjluwPi0hgVRbavc47RY5PZJLd67xTRERERET+P3v3HR9Fnf4B/LPpvZJOCzXSAoQiTQgEAlKCHO3kuPNOEUX0VMR6WA7v5+lxNkQBOSwI0u4oCb1LJ2ACCCShQyrpve/z++PLhoTdTXY2uzu7m+f9eu0rOjs78yzJfL/PzHy/zzDGGGOMmZhxigXYu4ufqhsIZu727duYNGkSioqKsHXrVigUirqX0Z5cLJOdO3eiS5cusLOza3S92tpafP755+jduzdcXFzg6emJkSNHYv/+/WrrLl++vMG/mabXuHHjGt3fpEmToFAo8OGHH6q99+abb2LDhg3SvqjcqovuTwgyAkdf8dOKJv7WV/94ZNK5ublpPAZtbGzg5+eHyZMnIz4+XuNnExMTMX78eHh5ecHd3R1RUVE4fvy4TvuwsbGBt7c3wsPDMW/ePJw7d07tc717926yraj/erg9iI+Px1NPPYXQ0FA4OzvDx8cHPXr0wO9+9zt88803uH79et26+fn5WL58OUaOHAkfHx84Ozujc+fOmDVrFs6fP68Wm0W2M1JU5jwYpGMFgoODkZ5upEmdzsFAVR5Qa139v6GYoo1esmRJXTvQunVro+2HaadLvqhP/iclv1Sprq7GZ599hoiICLi7u8Pf3x/jxo1DbGwsiKhuPSLC8ePH8cILL6BLly5wdHSEv78/hg4dip9++qnBuvp8XwCoqanBf/7zHwwYMAC+vr7w9vZGREQEvvrqK1RVVTUrfhVd+2Kp61t9P9dcZamiYICxOPjcnyis/e/QEnHerr+SkhKN7eaIESPq1tG1zTRljs3n/nqqzDWrXHzDhg3o0KEDIiIi5A5FO0c/8bOFTDAwZXtqybn2+vXr62J3cnLS6TNSc0Sp1xLqM0YOrW88uuagxo7Hatt1bSruiZ9OAcbfl4OnRQ445/swmkk9b6yvsdxKhc8zNagu4GLMzLxxPmw0LS0flpq/6ZN/Dh06VGsu+fLLL6utL/Uaqz7XZAHjXeN+WIu8zqGNKfNhxphxWfBEZz7vVCe1rwbM5/6sxfal1fwQIMYYY4wxxhhjjDHGmDyMUyxAdQOwLNUomzekxMRE9OvXD2PGjIGHhwcmT54MIkJMTIzcoRnU9evXMWnSJLz11lvIyspqdN3a2lpMnjwZr7/+Op555hncvXsXiYmJaN++PcaMGYP169dL3v/gwYO1vvfjjz8iNjZW6/tz5szBW2+9hUWLFkner2zKUo13I9y1HQAFUJRknO3L6OHj0RRKSkrQuXNnTJgwwST7M7aSkhIkJCQAAGJiYkBEICLk5+dj5cqVOHnyJIYMGaI2yej06dMYPHgw3N3dceXKFdy8eRMdOnTAiBEjsHfv3ib3UV1djaSkJPz9739HUlIS+vXrhz//+c8oKytr8NlNmzbVxUREmDt3LgBg165dDZbXf8qlUqnEwoULMXjwYPj7+2PXrl0oKCjAlStX8Nlnn6GoqAjz5s1Dp06dUFNTAwBYuHAhXnzxRcTExODy5cvIzc3F6tWrkZiYiIiICGzdurVBXBbZzkhRlAS4tZc7CoMJCgpCRkaGcTbu2QMgJZCtfdB0S2WqNvq1114DESE8PFznz1hbW66JKb6jlHxRF/XzP33yy9LSUowcORLff/89PvvsM9y7dw9nz56Fm5sbJk2ahEuXLtWtm5ycjKFDhyIlJQWbN29GYWEhTp06hbZt22L27NlYuHBhs7/vn//8ZzzzzDOIiorClStXcO3aNcyYMQMvvvgifve73zUrfkBaXyx1favv55pDWQXknga8ehhvH67tAGU1UHLLePswMc7bm8fNza0u7w0ICICtrS2ICIcPHwYgvc00VY6tixZ37q+LomTAta3cUQAQv/eNGzdixowZUCgUcoejnUtrwMYRKLggdyRGZ+r2VJ9c21zMnDkTRIRRo0bp/BmpOaLUawmAcXNofeKRmoMaMx6rbde1KbgA2DoZtwiVilMQUHbH+PsxIL4Po1lzjtmmciuAzzO1Kr0DOAfJHQVj2nE+bDQtLR+Wmr/pk39KJfUaq9T1jZmfP6zFXufQxpT5MGPMuJyDxU8+7zRLhu7rHmZO92ctti8tvX/sqI4lxhhjjDHGGGOMMcYYMxUyBmU10XpnouurjbJ5QyksLKTWrVvT3Llz1d6LiYkhAFReXi5DZIb3+9//nj766COqrq6mkJAQsrW11bru999/TwDoxRdfbLBcqVRSWFgYeXt7U35+ft3yb775hmJiYjRuKyUlhRwdHSkjI0Pj+2lpaeTt7U2zZ88mALR48WKN6yUmJpJCoaANGzY09VXlV5lPtFZBdHeb8faxoyfRuZeNt30ZNHY8GlNRURF16NCBxo0bZ9L96sLV1ZWGDBki+XMJCQkEQONx+dNPPxEA6t69e92y2tpa6t69OwUFBVFZWVnd8pqaGuratSu1adOGKioqdN4HEdHrr79OAGjSpEmkVCqJiCg8PJw2bdrUYL25c+cSANq1a1eD5TNmzKhrD95++20CQCtXrtS4r5qaGho3bhwBoOrqaiIievrpp+nZZ59VWzcxMZEAUOfOnTW+ZzHtjCRKov8FE/32D7kDMZj333+funbtarwd7B1KdHSq8bZvgeRoo8PDwykkJESnda2xLX+YKb6jlHxRav4nNb8kInr++efJw8ODMjMzGywvKSkhR0dHunjxYt2yK1eukJ2dHeXl5TVYt7Kyknx9fcnR0VGtL5Pyfa9fv04AqE+fPmrvjR49mgDQmTNn9I5fal+sT99tvf1cM91aR7TOjqg01Xj7qK0k2uBGdHW58fZhQpy3q2tOWx8QEKDW/khpM02ZY/O5vx7Ks4jW2RClxsodCRERxcXFkUKhoCtXrsgdStMOPU50RPPfm7WQqz0lkpZrm5tRo0aRo6OjTutKzRH1uZZgzBxan3ik5KCmiMfq2vXGHJ4oXqaQeYhoLYhK75pmf83E92G0k3LM1qdLbsXnmY3Y8yhR/AtyR8FY4zgfNqqWkg9Lzd/0yfeGDBlC8fHxOsUj9RqrPtdkjZmf19dir3M0xpT5MGPMyJREm/2IrnwmdyA64/NO7aT01UTmdX+WyEL70iv/JvpvgNxRMMYYY2o2bNhAxpo2whhjjDHGGGPMPNgYpQKBwg5oNQhI322UzRvKJ598gszMTLz77rtyh2J0//nPf/Dmm2/Czs6uyXW3bNkCAJg4cWKD5QqFAjExMcjPz8fmzZvrlnfq1AnDhg3TuK2lS5di8uTJCAwM1Pj+nDlzMG3aNIwZM6bRmMLDwzF16lQsWLBA0lMNZZG5F1DYAn7anzTQbG2nAjd/AmpKjbcPE5PreHR3d8f169exc+dOk+5XLpGRkQCAS5cuoaCgAADwyy+/4NKlS5g6dSqcnZ3r1rW1tcXvf/973L17F3FxcZL2889//hMDBw7E9u3b6558mpiYiKlTp+r0+fXr1+Nvf/sbkpKS8M9//hMRERGYM2eOxnVtbW3VKomvWrUKK1asUFs3PDwczs7OuH79OohI7T2LaWekSN0GVGQCbabIHYnBhIWF4fr166ioqDDSDl4F7vwXyNxnnO1bIHPPmVpCW26K7yglX5Sa/0nNL7OysrBy5UrMmjULAQEBDT7j6uqKiooK9Ojx4EnwYWFhqK6uhre3d4N1HRwc0KZNG1RWVqq1GVK+7927dwEAjzzyiNp7YWFhAIA7dx48YUVq/FL7Yn36bqvt55qjuhBIfBNoNxNwMeITr2wcgODHgeurjbcPE+K83fiktJmmzLH53F8PN74D7NyBgEi5IwEAfP7554iOjq7ru8xa6GwgLQ4ovCx3JEZj7jm2NZCaI+pzLcGYObTUeKTmoMaOR/WeVbXr2hT8BqTvFG2XKfgOAOzcgLTtptlfM7Wk9k5KmyD1mK1Pl9yKzzO1KE8HcuOBgJFyR8JY4zgfZgYgNX/TJ9+TQuo1VqnrA8bNz+trsdc5tDF1PswYMzKFuJ6Ztk3uQHTWkvIKKX2dVOZ2fxaw0L40dZvZ3BNgjDHGGGOMMcYYY4y1LMYpFgAA7aYD6XFAdZHRdtEcRIRVq1Zh4MCBCA4Oljsco6s/uKspWVlZAAB/f3+194KCggAAx44dq1sWFRWFBQsWqK1bXFyMH374AfPmzdO4n9WrV+PSpUtYsmSJTnE98cQTSE1NxY4dO3RaXza31gGBIwHHVsbbR+cXgNoKIGWZ8fZhQi3teJRT/UE8CoUCAHDw4EEAQL9+/dTWVy07cOCApP0oFArMnz8fAPD111/rFSsArFy5EkqlEtOmTWt0vUGDBoGImryhWFpaivLycvTo0aPu+2vDiEUAACAASURBVNdnMe2MrqgW+G0x0Hoy4GEBE4J01LNnT9TU1CApKck4O2jzhMhjTj0NlGcYZx8WhNvolkNKvig1/5OaX27fvh21tbUYOnSozjFpUlBQgKtXr6JPnz7w9PRs8J6U7xsWFgZ7e3uN7U5SUhIUCgV69uxZt0xq/FL7Yn37bqvr55qDlMCZuUBtFRDxmfH3F/YKkHsGyDpo/H0ZEfcJpiG1zZRK3xybz/0lqikFkr8AOs8F7FzljgaXL1/GgQMH8NJLL8kdim7aTge8egIJCwHoPxnFXHF7Kq/GckRNGruWYMwcWmo8UnNQY8ejYjXtulYEJLwGePcWBV5Nwc4FaPs7iyhG1dLaOyltgr7nvbrmVnyeqcWN7wF7TyBkvNyRMNY4zoeZETWVvzV3fW2kXmOVuj5gmvy8xV7n0EqGfJgxZnyhs4GsI0DJdbkjaVJLyyuk9HVSmdv9WRWL6kuLU4B7R4HQP8odCWOMMcYYY4wxxhhjrAUyXrGAttMBhR1w9Ruj7aI5zp8/j6ysLISHhze6XmZmJmbMmAEvLy/4+vpiwoQJuH5d/WZIUlISJk+eDE9PT7i4uGDAgAGIi4tDVFQUFAoFFAoFnnnmGWzdurXu/xUKBW7duqXT9nNzc/Hqq6+iY8eOcHR0ROvWrREVFYXvv/8e5eXlBvt3AYBWrcQkd9UEhfqys7MBALdu3WpyO9999x3atm2Lxx57TO291NRULFiwAKtXr4a7u7tOcfXu3RsAsGfPHp3Wl0VxinjSR8dnjLsfR1+g2+vAbx+IfVo4bcfjhx9+WHes1L8ZtXv37rrlqr9XAJKPr4fXV1W0XrJkSd2y1q1bIz4+HqNGjYK7uztcXFwQGRmJ48ePa91OcnIypk+fDl9f37plOTk5ABoeyw4ODvD29sa4ceNw6NChuu2p9l9aWorjx4/XbcMQlcEPHz4MAOjevXvdTTnVIJvWrVurrR8SIp6ym5Ii/e9M9Ts7deoUqqur9QkXv/zyCwCgV69een3+YZs2bQIAvPPOOxrft4h2RoqkT4GCS0Cvv8sdiUF16dIFjo6O+O2334y3k/5fi0ldB0cDlTnG248F0NZGmyqnSUpKwvjx4+tyrKbaYEtry7Ozs/HSSy+hffv2cHBwgJ+fH6ZMmYLExMQmv6O+vwNj0pb/Sc0vf/31VwCAt7c3FixYgDZt2sDBwQHt2rXDSy+9hLy8vEbjKCoqwvHjxzFp0iQEBgbixx9/bM7XQkBAAJYsWYLz58/j7bffRnZ2NvLy8vDJJ59g//79ePfdd9GlSxe945faF+vbd1tdP6c3As6+CNzdCgz+ybhFvlRaPQoEjwfiXwCUlcbfn5Fw3m6avN1Q5+TaGDrHbpHn/rq4+J4o8hf2qtyRAAC++OILdOrUCdHR0XKHohuFDdBvKZCxF0j6Qu5oDE5beyq1XZPa/j5Maq59+/ZtzJgxA+7u7vD19cXs2bORn5+PW7duYeLEiXB3d0dQUBDmzJmD4uJitf3pkvvWj011rdXV1RXDhg1rVqEUQP8csalrCc3VWDsqJZ7m5tCGjkfFatp1ba58KgpC9VsKQP/Jc5J1fgHI+1VcizZjfB9GO32OWSm5FZ9nalBdDCR9DnSaA9g4yh0NY43jfJjzYSPkwypS89um1l+zZg169+4NV1dXeHp6YtiwYVi3bp3aelKvsUpd31D4OodEcuXDjDHjCh4LuHcUDyYwc3ze2TRd+2pzuz+rYlF96W8fAu6dgaAxckfCGGOMMcYYY4wxxhhriciYEt4g+q8/UWW+UXejjzVr1hAA+r//+z+N78fExBAAiomJoRMnTlBJSQkdOHCAPDw8qH///g3WvXr1Knl5eVFISAjt3buXiouL6bfffqOoqCjy8/MjR0dHnba/b98+cnZ2Vtt+RkYGhYaGUmBgIMXGxlJRURFlZmbS4sWLCQB99tlndetGRkaSj48PnTx5Uut3DwkJIVtbW63vL126lADQiy++qPZeREQEAaB+/fpp/TwRkVKppC5dutDXX3+t8f3o6GiaN29e3f+rfh+LFy/Wus3CwkICQMOGDWt037I69nui2K5Eylrj76u2imhXBNGufkTVJcbfnxE1dTy6urrSkCFD1JZHRESQr6+v2nIpx1f99cvLyxssDw8PJ1dXVxo0aFDdduLj46lXr17k4OBAhw8f1rid4cOH06FDh6i0tJROnTpFtra2lJ2dXXcsBwQEUGxsLBUWFlJycjJNmTKFFAoFffvttzp9bxVtx3tCQkLd91cpLCyk//3vf+Tv70/29va0b9++uvdGjx5NAOjUqVNq+7h69SoBoL59+za5j4eVl5cTxCNvKD09XeM6c+fOJQC0a9cuje8HBQURADp9+rTW/egqMzOTAgIC6JlnntG6jkW0M7rKPkm03onoN83HlaXr3bs3vfbaa8bdSWkq0bYORDt6EBVfN+6+zJg+OZMhcprw8HDy9PSkyMhIOnbsGBUXF+vUBltSW56enk7t2rWjgIAA2rFjR10OOXz4cHJycqITJ07o9B2l9nuGyBc1aSz/k5pfqr5TYGAgzZo1i65fv075+fn0ww8/kKurK3Xp0oUKCgo0xqH6ewJAI0aMoAsXLjQZu67fd+PGjdS6deu67bdq1Yr+85//qK0nNX6pfbE+fTeRlfVz+qqtIDr1NNE6O6K7W0y775LbRBvdic69bNr9GhDn7YbN24mIAgIC1Nqf5p6TmzLHbrHn/k3JPEi0zpbo2rdNr2sCeXl55OrqSl999ZXcoUh36SOin+2J0nbKHYlBNdWeSm3XpLa/+ubaU6ZMobNnz1JJSQn9+OOPBIDGjRtHMTExlJCQQMXFxbR8+XICQK+88kqDbUjJfTVda71w4QKNGTOG2rdvr/Faa1M5rj45IpFu1xJUDJ1DS42nOTm0MeJRsYp2XZu0ONFGXf5Env0fmUwU113kuGaK78NobxP0OWal5FZ8nqlBwptEGz2JKnPljoQx3XE+zPmwgfJhFSn5rS7rDxkyhGbPnk3nzp2jkpISSkpKotmzZ2u9rkGk+zVWfddXMUZ+3mKvc2gjdz7MGDOum2vFNc7cs3JH0ig+72y8r5PSV5vr/VmL6Utzzohj5tbPckfCGGOMabRhwwYy9rQRxhhjjDHGGGPyMu5ZX2WeKBZw5nmj7kYfn3zyCQGgZcuWaXxfdQE8Nja2wfInn3ySAFB2dnbdsmnTphEA2rx5c4N17927Ry4uLo3eLHh4+1OnTlXb/lNPPUUAaMOGDWrbGTt2bIObBcOHDydvb2+1yWX1NXWxvby8nCIiIsje3p6++uorysnJodu3b9MLL7xAgYGBOl2A37FjB7m7u1NxcbHaeytXrqQOHTpQScmDCe663EgnIlIoFNSpU6dG15FN+h6itSC6u810+yy+RrTZj+jwRCJljen2a2BNHY/6TjrS5fiqv76mSUcAKCEhocHyCxcuEAAKDw/XuJ2dOzUP2lIdyz//3PDGUEVFBQUHB5OzszNlZmY2+b1VtB3vqon89V8KhYJ8fX1p0qRJdObMmQbrNzYQNCUlhQBQRESExn00ViygrKzMYMUCHo5ZqpycHOrduzfNmDGDamoaP1bMup3RVdHV+23DBItuGxrz7LPP0uDBg42/o9I7RLv6Em3yEe18C6RvztTcnEbVBj88AKKpNtiS2vI//elPBIDWrl3bYHlGRgY5Ojqqtb1NFQvQtd8zRL6oSWP5n9T8Mjo6mgBQaGgoVVdXN9jWhx9+SABo0aJFWmOprKykK1eu0HPPPUe2trb097//vdHYm/q+SqWS5syZQ/b29vTpp59SZmYmZWdn04oVK8jZ2ZlmzJjRIE6p8Uvti/Xpu1Wsop/TV2kq0Z5HxeSQ1Nim1zeGW+uJ1iqIrq2SZ//NxHm7YfN2Is3FApp7Tm6qHJuohZ77N6UoReSOR6cTkVLuaIhIDNT09PSkoqIiuUPRg5Lo1F9EITQrysebak+ltmv6TI7SJ9fesWNHg+Xdu3cnAHTkyJEGy0NDQ6lr164NlknJfbVda01LSyNHR0eN11p1yXGl5ohSriUQGT6HlhpPc3NoQ8dTn0W369qk7ST62ZHo1DMkW3tffEMUo0p8W57964Dvw2hvE6Qes1JzKz7PfEj2STFpI+UbuSNhTCLOh+vjfLh5+bDU/Fbq+vUNGDBArV+Reo1V6voPM3R+3mKvc2hjDvkwY8y4lLVE+0cQxT5CVFPe9Poy4fNOaX2diqa+2tzuz9Zn9n1pbYUo6Lh/JHG/yBhjzFxxsQDGGGOMMcYYs342MCYHb6DvZ8C1FUD6DqPuSqqKigoAgL29faPr9e/fv8H/h4SEAADS09Prlu3evRsAEB0d3WBdPz8/hIWFSdp+mzZt1La/ZcsWAMC4cePUPr9r1y68/PLLdf9/+PBh5OXlYdCgQY3utzFOTk44dOgQ/vrXv2LJkiUICgrCwIEDQUTYtGkTACAwMLDRbXz55Zf44x//CDc3twbL79y5g4ULF2L16tVwdXWVHJudnR3Ky8slf87oKrOB008DbacBrSeZbr9uHYHh24GsA8CxGYCy0nT7NiBdj0epdDm+muLq6orevXs3WNazZ08EBwfj/PnzyMjIUPvMgAEDNG5LdSyPHz++wXJHR0eMGjUK5eXl2LNnj86xNXW8x8TEgERRGCiVSuTk5GDbtm1q/y5eXl4AgNLSUrVtqJap1pFC9W9jb2+PVq1aSf48AAQHBwMAcnJy9Po8IL5DdHQ0unXrhrVr18LW1rbR9c22ndFV0RXgQCTgFgoMWQ8oGv++lmrYsGE4e/YsysrKjLsjlzbA6GNA8Djg0Fjg7HygpsS4+zQz+uZMzc1pAJGTDBw4sMGyptpgTcy1Ld+6dStsbGwwYcKEBssDAwPRvXt3nDt3DqmpqTptC9C93zNEvqiJtvwPkJ5fqvLEqKgo2NnZNdjWxIkTAaDRf2cHBweEhYXhm2++waRJk/Duu+9i//79en+3NWvW4Ntvv8Vzzz2HV155BQEBAWjVqhWeffZZvPnmm9iwYQO++uorveOX2hc3p++2+H5OXze+B3b2BKoKgOjTQMiEJj9iFO1mAD0WAWeeA26vlyeGZuC83Th5+8MMcU7eGEPk2Cot7ty/KSU3gIOjAfdOwKDvASjkjgj5+fn49NNP8eqrr8Ld3V3ucPSgAAZ8C7SdDhyZCFxfLXdABqFLe6pPuyaFPrl2v379Gvy/qj15eHlISIhaGy4l99V2rTU4OBhdunTR+H10aWul5IhSryXoq7EcWmo8zc2hDR1PfRbbrmtzbSXwSwwQOgsYsAKytfduoUCffwGXPwbSd8oTQxP4Pox2Uo5ZfXIrPs+sp+IecHwmEBgFdJ4rdzSMScT5cH2cD+ufD0vN35qbD0+dOhUAEBsbW7dM6jVWqesbAl/n0JG55MOMMeNS2AADVwPlaeIeuZni8079aOqrze3+bH1m35eemSuOlUe/A/eLjDHGGGOMMcYYY4wxuRi3WAAAtH8SCJ0NnPijGDRtJpycnAAA1dXVja7n6enZ4P9tbMQ/mVKpBABUVlaiuLgYTk5OGgdRent7S9q+g4OD2vYLCwvh5ORk0kHd7u7u+Ne//oWbN2+iqqoKGRkZWLZsWd2gsL59+2r9bEpKCvbu3Yt58+apvRcbG4vCwkKMGDECCoWi7jV79mwAwKJFi+qWXbt2Te3zNTU1cHZ2NtC3NBCqAY7PAhR292+Gm1irR4ERu4HM/cDhiWIClIXR9XiUqqnjSxfaBkD6+/sDAO7du6f2nqZBIk0dywEBAQCAzMxMnWMzFNVNTU0TUtPS0gBA6+Cjxhw7dgwAMGjQIL0nlA0fPhwAcOHCBb0+X1NTg2nTpiEkJAQ//PCDToOZzLKd0VXOSWDfY4BrOyByD2AnfcCSpRg2bBiqqqoQHx9v/J3ZOgODfxKv2xuAHT2A1O3G36+Z0DdnMkRO4+vrC4VC/WZ6Y22wJubYlqu2pVQq4enp2SAvUigU+PXXXwEAV69ebXJbKobo9/TVWP6nIiW/bN++PQDxN/Aw1e8tOztbp9hUg1fi4uJ0Wl8T1eCgqKgotfdGjRoFQAziUZEav9S+uDl9t0X3c/ooTgEOjROFvTr8CRh7DvDoKm9MvT4Awv4KnPiDxQ3y57zddHl7c87Jm9LcHFulxZ37N6XoCrB/OODYCojcJXJIM/Dhhx/Czs4Or7zyityh6E9hI4ovPLIQOP0McO5liy2WqKJLe6pPuyaFPrm2h4dHg/+3sbGBra0tXFxcGiy3tbVt0IZLyX2butaqiq+5GssR9bmWoA9dcmgp8TQ3hzZ0PA9/xuLadU2UlcDZF0Xhp+5vAwNXiTZKTp3mAqF/BI7/HihoXt9uDHwfRjspx6w+uRWfZ95XWw4cnSLu3wxeC560wSwS58MNcD4sPR+Wmr8ZIh8OCgoC0PDfUeo1VqnrNxdf59CBOebDjDHjcgsVefSN74Er/5I7Go34vFM/mvpqc7s/W59Z96WX/wnc/AkY8jPg2lbuaBhjjDHGGGOMMcYYYy2Yae7c9fsacGsPHIoGKrJMssumqC56FxYWNms7jo6OcHd3R0VFBUpK1J803NyBCo6OjvD09ERFRQWKi4ubtS1DUE3+nTJlitZ1vvzySzz22GPo1q2b2nsvvPBC3ZPO67/WrFkDAFi8eHHdsk6dOjX4bFFREYio7ndnHgg4PQfIOQ4M2wQ4NH5zyGj8hwGjDgKFl4A9/YGCi/LEoaemjkcbGxtUVVWpLS8oMH5hhNzcXBCR2nLVsa3roJymjuWsLNE21n9CqKZBSsYQGRkJADh37pzae6plqkE3ulIqlVi2bBkAcdzra+7cubCzs8PmzZsbXe/111+HjY0NkpKS1D5fWVmJjRs3Nqh83qlTJ5w6dUptO+bZzujo6jfA/hGigEjkXsBB80A6a9GuXTu0bdsWv/zyi+l22v5JYPwloNVg4JfJYjJYrgmKFcjMkDmT1JxG2z6ltsHm2JY7OjrCy8sLdnZ2qK6u1pgfEVFdG23uGsv/mqIpvxw6dCgAaHyCl+r3ppqw2xRHR0cAQF5enuTYVDQ9WfFh9c8FpMYvtS/Wt++26H5Oqop7QPwLosBLeRow+ijQ9zPAzqXpz5pCnyVA97fEIP+EhQDVyh2RTjhvlzdvB3Q7J29Kc3NslZZ17t+E9B3AnkdF0a6R+wEHH7kjAiAm9n3zzTdYtGiRWQxAbR4FEP4hMGQdcGM1sHuAxV37qE+XHFtKu6ZP+2uoXFsXUnLfpq61NienezgmbduTei1BX7rm0LrG09wc2tDxqFhku65J/nlgd3/g5o/A0PVAz/dhNpOOBywHfPoBB0eL68NmhO/DaCflmNUnt+LzTIhCAUdigKIkYPh2wFF9wgtjloPzYRXOh6Xnw1LzN0Pkw6qnKNf/d5R6jVXq+s3F1zmaYM75MGPMuEImAH3/DSS8AaQskzsaNXzeqR9NfbW53Z9VMeu+NPlLIPFtIOJzIGis3NEwxhhjjDHGGGOMMcZaONMUC7BzAUbsFP99KFpM3JBZjx49AGh+SopU48aNA/Cgur1KZmYmUlJSmr39J554AgCwc+dOtff69Olj8KfD5eTkwMbGpu7GgEpRURFWrVqFmTNnan2CTFFREX788cdmTQ7WRvX0GtXvTn4EnH0JuLUWGLpZDMiUk09fYNw5wDkE2Pvo/Zt06oNozFFTx2NQUFDd718lMzMTd+7cMXpsFRUVak8uv3jxItLT0xEeHi7pZpTqWN6xY0eD5ZWVlThw4ACcnZ0RHR1dt9zFxaXB4KauXbti5cqV+nyNRg0fPhzdunXD5s2bUVFRUbe8trYW69evR5s2bTB+/HhJ23zrrbdw5swZPPHEE5g2bZresXXp0gXvvfcezp49i9WrNT95Nzk5GStWrMD06dPrnoAFAO+//z4uXbqEbdu21d2IbIr5tTM6qMwFjs8Ezs4XT/F4bJv5TIQ0spEjR2Lv3r2m3amTvxiQGX0SAAF7BgK/PAHknjFtHCZkyJxJak5TUlKC8+fPN1imTxtsrm35lClTUFNTg+PHj6vt5+OPP0bbtm1RU1Ojc2xy0SX/k5pfPv744wgJCcHu3bsb9E2AeIoTAEyePLlu2WuvvYY//OEPGveterpU//79pX2xegYOHAgAOHDggNp7Bw8eBAA8+uijescvtS/Wt++2yH5OqopMIPENILYTkLoV6P8NMC5BFHoxN70WA4PXAClfAYfGAuXpTX9GZpy3myZvb845uS6ak2PXj6XlnPs3gmqAC+8CRyYBbX4HjDpgVkW7Fi1ahICAADz77LNyh2I47WYC4xIBe3cxSeHCe2IioIXRJceW0q7p0/4aKtfWlZTcV9u11pycHCQnJ+u8T31yRH2uJehD13ZUSjxSc1Bjx6NiUe26JjVlwIVF4vzfwQt4/DzQdrrcUTVk4yAmQnuEAQdGmtU1Cr4Po11zjlldtPjzzOpC4PAEIO8cMHIf4Cm9uCFjZonzYc6HJeTDgPT8Tcr6q1atQkREhNpyIsLGjRsBPHiqMCD9GqvU9ZuDr3M0whLyYcaY8XX9K9D7I+Dsi8CVf8kdTQN83qmd1L7a3O7PqphtX3r5n8C5l4E+nwBd5ssdDWOMMcYYY4wxxhhjjAFkSiU3ibZ1JIrtSlRy26S7fphSqSR/f38aMmSIxvdjYmIIAJWXlzdY/sYbbxAASkhIqFt27do18vHxoZCQENq7dy8VFxfTxYsXaezYsdSuXTtydHRs1vYzMjIoNDSUgoKCKC4ujoqKiuju3bv0/PPPU0BAAN2+/eDfMjIyknx8fOjkyZNav3tISAjZ2tpqfT87O5sA0JgxY+jq1atUUVFBp0+fpkGDBlF4eDjl5uZq/exnn31GQUFBVF1drXUdTdasWUMAaPHixVrXWbduHQGgLVu2SNq2USiriU7+iehnB6Lbm+SOpiFlNdH5RUTr7Ij2jyAqviZ3RE1q6nicP38+AaClS5dScXExXbt2jaZPn04hISHk6+urtr6U46ux9cPDw8nT05NGjRpFJ06coJKSEoqPj6devXqRg4MDHT58WKftqKiO5YCAAIqNjaWioiJKTk6mKVOmkEKhoJUrVzZYf+zYseTp6Ul37tyhEydOkJ2dHV2+fLnufW3He0JCAgGgmJgYjXFocvLkSXJycqKZM2dSRkYG5eTk0Ny5c8nOzo52796ttv7D+6itraWsrCzaunUrjRw5kgDQX/7yFyorK2t0v3PnziUAtGvXrkbXe/PNN8ne3p7eeOMNSk5OpsrKSkpNTaVVq1ZRUFAQDR06lEpKSurW/+677wiiWobWl6Z20qzaGV3c+R/RfwOItrQhytgrdzQmt2nTJrK1taWcnBz5gri7jWj3AKK1INo/kih9DxEp5YvHCAyZM0nJacLDw8nV1ZWGDh1Kp06d0rsNNue2PCsrizp27EgdOnSgnTt3UkFBAeXm5tLy5cvJxcWFNmzYoFNsUvs9Q+SL9emS/+mTX+7atYvs7OwoJiaGUlJSKD8/n3788UdydXWlgQMHNuhjFixYQAqFgj744AO6efMmVVRU0M2bN+n1118nABQREdFon9TU983Pz6fOnTuTvb09ffHFF5SVlUU5OTm0atUqcnFxoZCQEEpPT9c7fiLpfbHU9YkssJ+Tougq0ZnnidY7ib7x0sdE1SVNf84c5MYTbe9CtMmH6PZGuaNpFOfths3biYgCAgLU2p/mnJMTGS/Hrq/FnPs3pihZ5IEbXIhSvpE7GjWXL18mW1tbWrNmjdyhGIeyhujKv4k2ehBtbS/OjSxIU+2p1HZNavtrqFw7OjpaYw41fPhwcnV1bbBMSu6r6VrrpUuXKDo6mvz9/TVea9XU1krNEfW9lqBi6Bxan3ik5qDGjofIgtp1Te78l2hrO9HWJH1OpKyVO6LGVRcTHXpc9E1m0i7yfZjG2wR9j1mVpnKrFnueWXKTKK470ZYQorxEuaNhzDg4H26wPufDmvsmqfmb1PW//fZbAkDz5s2jq1evUnl5OSUlJdGsWbMIAL344osNYpR6jVWfa7L1GTo/18SqrnNoYmn5MGPM+JI+J1pnS3R6rhibZAb4vFN7Xye1ryYyr/uzKmbXl9ZWEZ2eI46F5KVyR8MYY4zpbMOGDWTqaSOMMcYYY4wxxkzL9Gd9ZelEO3oS/TeQKPuEyXdf39tvv012dnaUlpZWt+zkyZNqN73feecdIiK15ePHj6/7XHJyMk2ePJk8PDzIxcWFBg8eTEeOHKERI0aQi4tLs7efk5NDL7/8MoWGhpK9vT0FBQXRzJkzKSUlpcF3GjZsGHl7e9OJEw3/bWNjY7Xe1P/222/V/m327dtHkyZNosDAQHJ2dqYePXrQ4sWLG72Ir1QqqVOnTvTuu+/q8s9PRA8mMTz8io6OVlt32rRpFBISQlVVVTpv3ygqc4kORIlBl+mNT76QVe5Zoh09xISpxHfMfrKUpuNRpaCggJ555hkKCgoiZ2dnGjp0KMXHx1NERETd38wbb7wh+fjasmWL2vJZs2bV7Tc8PJxCQkLo8uXLFB0dTe7u7uTs7EzDhw+nY8eO1a2nab/aLqo9fCx7enpSdHQ0HThwQG3dpKQkGjZsGLm6ulKbNm1o2bJlDd7XdLy7urqqxdG1a1edfge//vorjRs3jjw8PMjNzY1GjhzZ4Hs2tg+FQkGenp7Us2dPev755+ncuXON7kvbgKPi4mKtnzlz5gzNnj2b2rRpQ/b29uTu7k6PPvooffHFF1RZWdlg3fHjx+s1gN1s2pmmFF4hOjhWTFA/+WeiqgK5I5JFYWEhOTg40Nq1a+UOhSjzgOgb1kJM+LzyKVFlntxRGYwhc6amcpp//etfdZ8LCQmhM2fOUGRkJLm5uWlsgy29Lc/NzaVXX32VOnToQPb29uTn50djxoyhffv2Nfkdo4v8XwAAIABJREFU9f0dGCpfJJKW/+mTX544cYKio6PJ09OTHBwcKCwsjN5//321zxQWFtKqVasoOjqa2rdvTw4ODuTm5kYRERH00UcfadyH1O+bl5dHCxcupLCwMHJ0dCQHBwfq2LEjzZ8/nzIzM5sVv4qufbG+61tMP6crZQ3R3a1EB6OJ1tkQbQslSvmaqEbzBHCzVl1CdPpZorUKosMTxeQWM8V5u2HydhV/f3+yt7dXW65Pm2nsHFulxZz7a1NTTnThfXGuvauvyM3NjFKppMjISOrTpw/V1lr5QP6ydKLjs0T7uedRkZdbiMbaU13bNRVd21+puba29jo+Pl5t+UcffURHjx5VW/7ee+/VbU+X3Fel/rVWZ2dn6t+/P8XFxdGoUaPqtv3000/Xra+prZWaI+pzLcGYObS+1zak5qDGjsfs23VNMvYR7R4o2pYTs4nKM+SOSHfKalFEa62CKOF1s5i8wfdhGm8TpB6zRNJyqxZ3npkaS7TZl2hnOFHpXbmjYcz4OB8mIs6HiTT3TVLzN6nrV1RU0KZNm+iJJ56gjh07kqOjI3l6etKIESNo3bp1Gn/vUq+xSl3f2Ne4VazqOocmlpwPM8aM7+5Wog2uRHuHmE3Ozeedmvs6ffpqIvO6P0tkZn1pyW2iPYPEMXB3m9zRMMYYY5JwsQDGGGOMMcYYs34KIiKYWnURcGIWkLEP6PcF0GmuyUMAgMLCQnTv3h0TJkzA8uXLjbKPsLAwlJeX4/bt20bZfktx/vx59OnTB+vWrcPMmTPlCyTvV+DYdICqgce2At595ItFF8pqIGUpcPHvgL070OvvQOhsQGEnd2RqTHE8StW7d2/k5OQgNTVV7lCYCZhNO9OYiizg0v8BV78BPLsBEV8A/sPljkpWo0aNQmBgINauXSt3KELBRfH7ufUToKwB2k0H2s8GAiIBhY3c0enNHNtoXXFbzphgEf2cropTgJs/ATe+B8rTgMDRQOfngZAJgMJW7uiaJ+sQED8PKLsDdHsTCHsVsHOVO6oGzLFPsOS23t3dHU5OTsjOzpY7FLNg9m3V3S1A4htAeQbQ830g7K9meX69YsUKzJ8/HydPnkS/fv3kDsc08s4C5/8GZOwRuXf3t0T/YMYaa08tuV1jrD6zb9cbICBjL3DpI+DeESB4HNBrMeATIXdg+rnxPXD2BXH9etAPgFtH2ULh+zDWy6yO8dpy4Pw7QNLnQIc/Af2WAXYu8sbEmClxPsyYWTKrvrJJVpYPM8aMq/AScHQaUJkNDFgJtHlC3nD4vNNqmVVfemczEP8c4BQIDN0oxuwwxhhjFmTjxo2YMWMG5Jg2whhjjDHGGGPMNOSZtWbvATy2Dej2upgIcXQqUJVn8jA8PT0RGxuLzZs3Y9myZXpvJzMzEz4+Pqiurm6w/NatW7h+/TpGjhzZ3FBbtBs3bmDKlCl466235LvwT0og6VNg7yDAtR0QHW/+hQIAwMZeTDCamAwEPw6cmQvEdQNurQWoVu7oGjDU8ciYPsyinWlMZQ6Q+CawvSNwZxMQ8SUw9lyLLxQAAOPHj8euXbtQVVUldyiCV0+g/9fA5DSg77+BwivAwShgWzsxsazgotwR6oXbaMYsm9n3c7qozAZSvhL5eGxX4MZqoP3vgYkpQORuoHWM5RcKAMSA/sfPA93/BlxZAmzvBFxdLoqAmQnuE/T33HPP4fXXX6/7/6ysLJSUlKBXr14yRmU+zLqtuncU2DsEOPo7MUh+whXgkQVmWSggIyMDb775JhYsWNByCgUAgE8/0R9E/SL6g4NjgF19xPUPpZmcKzyE21Nm7cy6Xa9PWQXcXAPs7A0cGgvYOgKjjwIjdlr2xKgOTwFjTgM1JcDOXkDyF+Iatwz4Pox1MqtjPPu4OIavrwYGfQ88+h0XCmAtD+fDjJkds+orG2Ot+TBjzLg8uwNj48W9maNTgOO/F2Ma5AqHzzutktn0pZXZwLEZ4uFCbaYA0We4UABjjDHGGGOMMcYYY8wsyfeIW4WNeMr5yANA7mlge2fg2koApq1Y16dPH5w9exa7du1CUVGR3tvJz8/H3LlzcffuXZSVleHMmTOYMWMGPDw8sGjRIgNG3PKsWLEC//jHP/CPf/xDngDyzwP7hgEJb4gncYzcCzj5yxOLvpwCgAErgIlXxQSkk08BW9sCF9+XpVCHNoY6HhmTSvZ2RpviFODcX4Ft7YHrq4Aei4CJ14DOz1nHhEgDmDZtGgoKCrB//365Q2nI3l085Tr6NDAhCej4NHDnv2KA/vYO4veafQymznuag9toxiyX2fZzTanMBm7+CByZCGwJARJeB1zaAMO3AzG3gN4fy/qEVKOxcRDnHZNuiCdi/vpKvdw9X+7oAHCf0BwbNmxASkoKcnNz8fbbbwMQRQSYObZVBKTFAgdHA/sfE4tGHwWG/Ay4tJY3tEbMmzcPfn5+eO+99+QORR7+w4CR+4BxiaKQ18mngP8FiuKJ+efljk4Nt6fMmplfu/6QoiRRmHFrG+DUU4BrW3EOH7kH8Bsqd3SG4dUDGHsW6PGuyKV39gTSd8oSCt+HsT5mcYyXpYk+fv9jgFsoMP4iEPpH+eJhzBxwPsyY2TCLvrIxLSEfZowZl50rMHCVKFiUfRyI7QJc/hhQVsoSDp93Wh/Z+1JltSi+GNsFyD4KDN8GDFjJxekYY4wxxhhjjDHGGGNmS0FE8s9SqyoALr4HpCwD/AYD/b4WA9ksyIEDB7Bs2TIkJCQgPT0d3t7eiIqKwgcffICOHa1wAktLUFMK/LYYuPJvwLu3eFK0b3+5ozKM4mtAylLgxncAkZiE1OVFwKOr3JGZhSVLlmDhwoUNlr3zzjv48MMPZYqItSikFAO3k78AMg8AHl2Ari+Jga52bnJHZ5YGDRqEsLAwfPfdd3KH0gQCck4Cd/8nXiU3Add24okLwY8D/sMBWye5g7Qa3JYzZolIDFxP3ykm6OacFsVXgseLJ3UEP94yB+CU3gGSPxeFg2ADdJ4LdHkJcAmROzLZWVpbn5GRgQ8++AA7duxAdnY2unTpgldffRVPPfWU3KGx+pSV4ol6V/4NFCWLtqfbQpGrmbn169fjySefxL59+zBq1Ci5wzEPZXfFtY/r3wGlt4BWg0Qhr7bTRR9jZiytXWPM4lQXA7fXAzdWAzmnxOTiDn8WLzMuBGMQhZeBhIUi1w6ZCPT5BPAIkzsqyfg+DAMgjuXL/wSSPgOcg4E+HwNtfid3VIyZJ86HGWP1teR8mDFmXFaUo/N5JwMIuLNZFNWpyATCXgW6vcHjdRhjjFm8jRs3YsaMGTCHaSOMMcYYY4wxxozDPIoFqOSdBeLnAfmJQNe/iifemOFABWbtCLj1M5DwmqgS3PtjoOOfASjkDszwqouA66uBlK+AkhtA8FgxKTlwND+1nDFTqyoAbq0BkpeKgh5BY0RfGDwWVtn+GNCnn36KxYsXIzMzE46OjnKHo7u8X4G7/wXSd4jJsXauQOAoMSEtcIwYpMUYY9auqgDIOiQmLWXsEk+GdAoEQsYDrScDQaMBGwtq242pqgC4thxI/hKozAXaPwl0fRnwDpc7MsasQ2UOcG2lyMer8oHQWUDYAsCzm9yR6SQzMxPh4eF44oknsHz5crnDMT+kBLIOimsgqVsAhR3QbrqYENFqMKCwkTtCxpixkFI84fDGd8CdjQDVikJUHf4CBES2vOM/cz/w6wKg6ArQaS7QYxHg5C93VIzpRlktjuUL74kCTz3+BnSZD9g4yB0ZY+aP82HGWi7OhxljplR6Bzj/NnBrHeA/FOjzL8B3oNxRMaa7nJOi2GLOSaD9H4Dwf3BBHcYYY1aDiwUwxhhjjDHGmPUzr2IBAAAST3D7dQGgrAI6Pw90exNw8JI7MGb1CEiLAy5+ICZwhv4B6PtvwNFP7sCMTzVIKPkLIG0H4OgjqnyHzgb8hoAnKjNmJMpKIGMvcGeTmDROSqDtNOCR1wGvHnJHZzHu3LmD9u3bIzY2FuPHj5c7HP1U3AMydot+KGOPKObiHAT4DQUCo0Rb7Nld7igZY6z5qouB3NNiklL2MSD3jBig6t1HtHchE3iQelOUVeIJYJc/AQoviYnMoX8EOjwFOAXIHR1jloVqRcGSayuB1G2ArZM4lh5ZaFEDAGtqajB69GikpaXh7Nmz8PDwkDsk81ZdCNzeAFxbIa7/OLYCgseJc7GgMVykhjFrQDXiSal3NoknwZWnP8iZOj4tjvuWjJTArZ/EE/Iq88Rk0e5vAR6PyB0ZY5rVlADX/wMkfQqUZ4jJzb0Wc6ELxvTF+TBj1o/zYcaY3PLOiXF/946I+9zd3hD3f3jsETNLBGQeuD9mLg5o9SjQ91Og1SC5A2OMMcYMiosFMMYYY4wxxpj1M8NiAfdVFwNXvwYufyxuZnaeJ24eOHjLHRmzNqQUT3W++D6Qnyie6NzzA8Cnr9yRyaP0tph8dOM7oCgZcG0HtJspBuB5dJU7OsYsHymBnBNigM6tteKppa0GiYF47f8AOPrKHaFFGjp0KNq0aYOff/5Z7lCaT1kF5JwG7h0WAyhyTgI1ZWLCWkAk4D9cvNw7yR0pY4w1rSoPuHdUtGlZh4GCC2K5Zw8gYMT9Nu0xHqCqr7xzYpLz7fVATanoJ0Jni7zC1lnu6BgzX4WXRKHKG98BlTkiHw/9I9D+ScDOTe7oJHvjjTfw5Zdf4sSJE+jTp4/c4ViWwktA6lbg7lbRptq7i4lSrZ8QP+258AJjFqO6EEjfBdzdAmTsAqpLAN9+QOvJ4uXZTe4IzY+yUkwWvfQRUJwirot3/aso4sWYOajIAq5+AyR/CSirgY5/AcJeFfcsGGOGwfkwY9aD82HGmDnKPibG/aXtEPe2u7wAdHqW718w8/Bwce66whYT5Y6MMcYYMwouFsAYY4wxxhhj1s98iwWoVBWIyq3JX4gJll3mA52fB1xC5I6MWbraigcX/YuTgbYzgB5/4xvl9eXGA7fXiUGj5RmATz+g3QwgZDw/aYoxKZTVQPZRIHU7cGejOJ58B4jJSO1mAE6Bckdo8VasWIGXX34ZGRkZ8PLykjscw1JWiSdv3zsCZB0RxSZqSkUu5B8J+A0W7bN3OGDjIHe0jLEWjYDia0De2QdFTwouire8eonCAAEjAL9hXBzH0GrKgNT/ATd+BLIOiCJ77WYCbaaIYgwKO7kjZEx+RVfEBJhbPwGFl0UxvNA/igIbLm3kjk5vcXFxmDRpElavXo2nnnpK7nAsW9ldIHWbmCyVdQRQ2AKBI8VTzwJGAh5hckfIGHtY0RUg8yCQFgtkHQJAIudsPRloHSOK7rGmkRJI3QJcWSKeQNtqMNB1vpgoauskd3SsJco5AVxdIe7fOPoCXV8COj0HOFjZNT/GzA3nw4xZHs6HGWOWouAikPRv4NbPIsfvMh8I/ROP/WPyKEsFbnwPpCwTRc/bzwIeWQB4dpc7MsYYY8youFgAY4wxxhhjjFk/8y8WoFJdJJ4ekrIUqMwDWk8Ug4MCowCFjdzRMUtSnCIGmt34HqgpAdpOB3q8w4NcGkO1YoDBrXVA2nagMhdwCxVPmwoeLyZ9ceVvxhqqyATSdgLpO4HMfaIf8+wOtJsOtHuSnwpvYIWFhQgKCsLSpUvx9NNPyx2OcSmrHxQPuPeLGMhfXSgKBXj1Ek+K8ekvfnp24wmijDHjKbsrikvlnX3ws6oAsLG/XxxgmChq4j9MTF5nplGWKiZD31oLFPwm/u2Dx4kBwkFj+amArOWgWiD7hDiHTd0GFF8FHFsBbaeKIgGtBskdYbPdvn0bffv2xdSpU7FixQq5w7EuVXlAWpz428ncL87nnIOBwFFiolTASMC1rdxRMtbylN4Gsg6KCVFZB0QxRnsPIHC0yHVCJnDe2VzZx4Ar/xZtoL2bKEAV+ieg1aNyR8asXVkacPNH4OYPQFGyOKcMe1lM2uDimIyZHufDjJknzocZY5auLA1I+RK4tkrc3w4cDXT4kyhywsXqmDHVVohCiTd+EON3HLyBjs+I4nTOwXJHxxhjjJkEFwtgjDHGGGOMMetnOcUCVJRVYmDCtZVA5gHArQPQaQ7Q8S+Ao5/c0TFzdX+ye/7ZJchK2ouwjkHi6YFd5nNFfamoFshPFE8oSIsD8n4VN+38hogBCK0nA67t5I6SMdMjJZCfIAbOpcUCOSfFQFa/oaKwTesYLkpiZNOnT8e9e/dw+PBhuUMxvfJ0IO+ceGUfF39/NaViwq57Z/F36DcE8IkAPB7hQkuMMemqCoDC30Qbk30MyD0rCuMA4pxM1caoXlxIyjyU3gIy9orcJGOPyFdaPQq0nQa0mWLRT1NnTKPa8vv5eByQul20U24dxLlqyETxdD0be7mjNIjy8nIMGTIECoUCx48fh5MTD6Y1GtV1kMz94pV9XPytqfo/v6GikCI/CY0xw6vMBrIOi/wz+7g457V1Bnz6Prje4v8YTyQ2hopM4PYGUXA3PxHw6CoKB3R4CnBtL3NwzGooK0XOdvNHIH23KFDRdrq4d+M3VO7oGGMqnA8zJh/Ohxlj1kpZJe5Z3FwDpG4FbF2A1pNEkdfAUQAUckfIrEXeOXHOeWutuNcZECnOOdtO43uZjDHGWhwuFsAYY4wxxhhj1s/yigXUV3gZuLocuLUGqCkHgqPFQKKQify0RCYmwmQfBW5vBO7+F6jMxqpfe2DOkgvo1KkTJk6ciAkTJmDYsGGwt7eOyQKyKEsTT05P3ykGCdWUAO5dxBNk/YaJn24d5I6SMcOjGnFj8d4xIPsXMUinMlcUywh+HAgZL56uwzcYTSYuLg6TJk3CtWvX0KFDC293qBYoSnpQQED1qq0AbBwB945iMq9nd8Czm/jpFgoeeMEYQ3WRePp24SVxvqX6WXITAAHOQQ2LAvgN5adVWYqqPJGzp24HMnYD1cWi/Q8YAfiPAAKGcwE+ZnmUlUDOaSDrEHDvMJBzClBWi6IYIZPuF+zqKneUBldbW4vp06fj0KFDOHv2LOe+plZbAeScuP8kx4NAbrzIvz26Ar4DHry8e1tNcQrGTEJZJSYi5p558CpKARS24pgKvP8U41aD+GmDppYbL572fmudOF/wGyL62NYxgFtHuaNjlqa6EEjfJYqCp+8SxS6DokUhitYTxXUrxph543yYMePgfJgx1lKVZwC3fhLF6govi/PMNpOBkBjAb7BoBxnTFdWKsTup28Sr5Lq4F9bhKSD0D4BToNwRMsYYY7LhYgGMMcYYY4wxZv0su1iASk0ZcGcTcGejmKyssAGCxgLtpgPBEwB7d7kjZKZCSlFZ/84mUSCgPAPw6iUqAofOhtK5DRISEhAbG4u4uDicO3cOrq6uiIyMxMSJExETE4OAgAC5v4XlUlYC947ef8LBL2KAUG2FeJqI32OA/1Dx06s7eEIqszg1ZUDuaeDeL6IQSc4pMZjVyV9MlPR/TDzBw7O73JG2WDU1NWjbti3+8pe/4MMPP5Q7HPOjrALyzwP5Cfcn/14CCn4DKrLE+w5egEc3wKvH/SIC3UV7zTfMGbNONSVA4RWg8Dcx+KrgIlB0BSi9I963c31QTMSzmxjg7dOPCwNYC2UlkHVEnD/fOwzk/SrOpbx63C8cEClyG0dfuSNlrCFllSgOcO+QOO/MOSWeaOnaXhS+CIgEgsdZfeGLl156CatWrcKePXswbNgwucNh1cXiGkjOKfH3mXtGTIS0cQR8+tyfLDVQ/HTvJHe0jJmP4qsNJ0LlJYgcxcHrwSTDVo+Ka4l8fd88KCuBtDjg7hZRhKoqX+SPIfcLB/j2A1/zZRqV3QXSYoG7W4F7R8S5h/9j4u+m7TRRlI4xZrk4H2ZMP/Xy4bMnD6GtQzL83ao4H2aMtWy58cDdzWKSd1GyuM4bMkGcOwSOBuxc5I6QmaOaMiBjD5C2XVy3qMwRhaxaxwBtpgK+/eWOkDHGGDMLXCyAMcYYY4wxxqyfdRQLqK8qH0jdKp4mn3UAUNgBwWOBoHFA0BjxxGdmXaqLxZMrMvaIG0bl6WKQYtvpYqCZR5jWj966dQt79+5FbGws9u7di9raWvTu3RsTJkzAxIkTERERYcIvYoVqK8TNvOxfxNPXc46L35eDj3gClW9/wKcv4N2XBwQy80K14uZz3jkg/1cxwC3vrHhKqWt7wH8Y4DdM/GykjWGm99Zbb+GHH37AnTt3YGdnJ3c4lqEyt95k4d+AovuThitzxfuOvmKysEdXwK0T4N7xwU87N3ljZ4w1TlkNlN4WT80oviZ+FiWLogAltwAQYOsMeD6iXizErT14ok8LUl0kCiLdOywmYOcnAiDAq6coiuTTX+TuHmGiOB9jplKeDuSeBfLigZyT4lVTBri2fVDYImCEyNFbiA8++ACLFy/Gxo0bMWXKFLnDYRqR6G9VE6VyTwMFF0S/7OgrJnx4hYs21qsH4PEIP3GVWTdl1YMiVQUXRRG73DNAVZ742/cKB1oNfDAhyqMrOA+1AFQj8sfUbUDqdqD0ligYG/y4eOJtwAguPtiS1ZYD2SeArENAxm5RnMzeTRT5bj0JCB7PhegYs2qcDzPWgA75cKc5V3EjrQjdwjoictRYjBgxAsOHD0erVq3kjp4xxuRTlPTg6fC5pwFbJyBglHiAQ8BIfkhJi0ZiXEPWQVEUO/OAKHDYahAQMkkUCfDoKneQjDHGmNnhYgGMMcYYY4wxZv2sr1hAfZW5onDA3S1i0kNNqZjcEDQGCIoWA8u56rDlIaV4KnLGHiBjL5BzQkzs9e4rKkq3my4GlkhUWlqKgwcPIi4uDtu3b0dmZiY6dOiAqKgoTJgwAdHR0XBwcDDCF2pBqFZMPMo+BmQfFxOxS26I95yDReEAnwjxu/SJEANMGTM2qhGDdPJ+fVAcID9R9Bk2DmLAmu8AUeDC/zHApY3cEbNG3LhxA507d8bWrVsxceJEucOxbBVZ9YoH/CaeclNyHShLFX0xIAb+u3cSL7eODX/yoG/GTENZKfKpoqsNiwIUXxOFAqhGrOfg8+B49ewOeHYDPHsAbqGAwlbe78DMT1UBkH1UTO7JOSXOv2orxFPMvPuKwgG+/UURAbdQuaNl1qKqQBQFyL3/yosHytJEgQr3LiIn9x8uJh+6dZA7Wll8++23ePbZZ7F06VLMnz9f7nCYFLUV9wvRnRF/2wUXxAQqZbWYHOIRJvpl717ip1ePFlUEg1mR0ltiAlTBb+LvvPA39b91r173c4kBgHcfMdifWb78RPEEv/Q9YvIb1QCe3VDqMRSu7ceIPtyRJ7tZLWWlmBScdejBOYSyEnDvDASOEhM1AiLFU8YZYy0T58OspdAzHy4pKcGpU6ewf/9+HDt2DGfOnEF1dXXdWIWoqChERkZy8QDGWMtVkQWkxQJpO4B7R8SDhJz8718vjhQvfsiDdSu68uCcM+sIUJkt7n0GDBcF6UImir8JxhhjjGnFxQIYY4wxxhhjzPpZd7GA+pSV4snmmXvFJPP8C2ISqP9QcfOg1WBxQ9beXe5I2cOoVtxUzz4uXpn7xUV/p0AgOFoUfgiMAhz9DLbL2tpaJCYmIjY2FnFxcTh37hy8vb3rCgdMnDgR3t48CdIgqvIbTtLOOwcUXwdAgFOAKBrg1fP+QKFu4qe9h9xRM0tVlioq0BddEU9Rz08UT/CoLReD0716ib85n75iIpxXT36ijQWKioqCi4sLtm/fLnco1kk1Mbn4WsNJySXXxcRkZbVYTzUx2a0j4NpOFIBxbQe4tBYvA/bbjFm1mjKg7Lbow8pSgdI7QNldcRxqKuDh0blh8Q4u4MEMQVktBjfnxt9/KmC8yKWoRkz68u1//6mAPe7n7I/wxD+mHSmB0ptAwSVRlCj/ApB3VuQTIFGcSzVo3rc/4NOPzwEBxMbGYsqUKXj33XexaNEiucNhhqCsEuenqkkkBRdFW1t6R7xv73m/Xe0uJlu6dwLc7hf+4TaWyam2QhSTK74GlFwT/11wSfz9VheJdVzb3Z/o1/PBpD+PML7G0kLUVhZi54bP8X9LVqKNVwU2Pl8IgMTfg99jDwpPuXcRRYGY5anIul/c6ay4Z5NzQpy7urZ/MFEnYCQXA2aMNY7zYWapTJAP1y8esH//fiQkJECpVDYoHjBy5Ej4+voa8YsyxpiZIqUY56GaOJ79/+zdeXhU5d3/8U9C9gRCgLAjAir7GhRxBoIQiFIQpUaUx0LdwI0EqRa3PlptCzxFEawLarXwq6xWRUDFDPsMixgEFUHUsDYJe0I2sp7fH2cmmUAQiMBJJu/Xdc01w2Rm+EYPZ+5zzv393OukomwptJl5LNKwj9SwtzuQJdTqalEVxXlS5jbzuPPoZnOBqPx08zpB4/7lx531u3NeAQCAC0BYAAAAAAD4vtoTFnC6UxnmKjcZyeaKibn7zRU163cxgwMa9TVvda+yutLap/C4dHSjufrMEZd58r84xzzp3+h6qckgMyAgqpskv8tS0k8//VQWHLBu3TpJUr9+/XTzzTcrPj5e3bp1uyx11BpFWdLxr8sDBLJ2mKsulJwyfx7W0pxQUa+jFNmxPEggpIm1daN6MIqlnD1mA5t3MMDJH8on6QQ3MrcdTzhAVC+pfmfJL8Da2nFRLFy4UP/zP/+jPXv2qFWrVlaXU7sYxWZgQPbP7kly7vvcA2ZDc8GR8tfWCZHCrjAnjoe1ksKvKA8SCHM/prkZvq7klNn4n3fQfX/AKxRgn7miduHx8tcHhElh7tCNiDblgQCe+4Bw634X1D7FeeZY/dhX7lUBv3WvlFZoHltHtHGHfnUsv4/swGqitYoh5ew1j+eydphj8qwd5vi8OM98SXhrs/GjQW9342BvM/gEFaxcuVLDhw/X73//e73++utWl4NLrTDTbDLJ/E7K3G4e12b/aI4LJEl+Unir8kapuleZzVM0TuFiKsn3Cohz33saovJh4JVPAAAgAElEQVQOSnJfUghraW539dznWOp3Nc+vB0ZaWj6sceLECb399tt69dVXlZGRod/+9reaNGmSruvZXjq8zt3E4TKDO0sLzPP9DWK8xgHXsop0dVSYaYYCeMIBjm0xj13lZ/77b9invFEjoo3V1QLwBYyHUR1Us/Fwdna2Nm/e/IvhAYMGDVKDBg0u6t8LADWCUWxepzi8xlxx/vgWqeCYOfejfmepwbXlx5yRXQgyrG5Ki8zrS8e3lB93Zu6oGFbtCQhoEMOcHgAAfgXCAgAAAADA99XesIDT5aeZDepHNpj3x7eaE9ZCGptpw2UXd7uaTcn+QVZX7Bty9rhXivjWXE0wc7t0crckQ6rXvjy0oVFfs4GgGiQCZ2Zm6vPPP9fSpUuVnJysI0eOqHnz5oqPj1d8fLzi4uJI8b8UjBIpd6+UtdNsLjm5q7wZvDDTfE1QlLkiVcSVUnib0+5b05jkSwozzdVIc/aedu9e7by0UOaEsSvcYRIdzYk6nmCJ4EYW/wK4lAoLC9WyZUslJibq2WeftboceCvJr6QZ+qA50dOzcrpnny6Zjc9hV0gh0eZqECFNpOBoKbS5+VxIY/NxcDSTQFF9GKVSwWHp1BFzlYtTh8ygjPx06dRh85afZoaXnTpc/j7/YHOic1hLM0AjzOuxJ0wjiMmeqOZKi8wJ1Jk7vBrEd5iTqUuLzElcEW3dARdt3bd25Y8Dwqz+DXChjGIzFCjnZ3MsXnb72QyPKM41XxfWyhyH1+9SMUAisK619dcAy5YtU0JCgn77299qzpw5qlOnjtUlwSrFeV5NKj9VfFzWrOJnjhnCW58WxtW6fJwRHG31b4Lq4NTh8uMyz7FY3kEzUNdznOa9TXka8SKuKl/Zt+5VrNAHSVJqaqreeustzZ49WyUlJbrnnns0adIktW7duvI3lBaZ1wE8oVPHtpjneY0Scx8V1c0dNNXZPKcX2UUK5nz7JVeS7z7nvrM84CnzWzMIUoa5L2h4rbvRprd5H1Tf6qoB1CaMh3Ex1fDxcGXhAZLUoUMH2e12wgMAICfV3Xi+xTz2PLFVKso2rydHdjFDBOp1Ms9ZR3Yyg+uqwXw0n2aUuud8eYKF3bfMb92BgnXNRT48wQ4NriWQDgCAi4ywAAAAAADwfYQFnE1pgRkYcHSTdGKbu6F9h9mA6h9oNrJHdnVPXOtU3uxAo9qZjBLzgnpOqtkskLnd/O+Z+a17lW+/8lUn63eTGl5nhgPUkAmAO3bs0LJly+RwOLRu3ToVFxerZ8+eZSn+sbGxCgwkmfqSyk8vDxDI/rFiA3lRlvtFflJYc3d4QBvzYl9EG7PJNLSF2XAa0ti63wHlSgvdjZT/lfIPmZN0Tg8FKGsm9jMbiCPalAdD1GvvDgZoLwVEWPd7wFJ/+MMf9MEHHyg1NZWGqpqmOMeckOcdKuBpri444n6cbr7OW2CkFNrUvT9vYq5KHNLYfR9tBsoERZnN1kFRrMCO81daJBUelwpPuG/HzRVJPNviqcNmIMCpDDMgoOCwOeHFwz/Ia1tsUh5+EdrMDMPwTFoOaWLd7whcaqVF5rHgye/N5iNPY3n2z+a/HY/QZmeGCIS1MvfvoS1oLLdCaYGUn2GOzfPSvAK63P8P8/ab/38l8/+P9/+7uteY4QCRnVhhuooWLVqku+++W7///e/15ptvyt+fCas4i9NXvcw9UN7wknvAHEd71AmpOAYJb23elwVyNTUbqAhwqZmK89zHTe6xaX7aaUFtB8xbyany94Q0Pq2R7gqvRihW58XZpaSkaObMmZo/f75atmypBx98UOPGjVNUVNSFf1hxrnTia7OJI+s7d/PAzvJzu8HR7tChDuZ9xFUExFaFUWoex+buNcfkWTvNMXrmDnOcZ5Sa17/qXuNumuksNXA3a4Q0tbp6ADg7xsPwqKXj4crCA/z8/NS+ffuy8IC4uLiqjdMAwBcYJeZ8omNfmXPWPMeceQfMnweEmceb9TqZQQJ127vnoLQ2ryvj/BWecB9z7nUH0rnD6LJ2mmM2yWvRj85S/e7mMWe9DgQ2AABwiREWAAAAAAC+j7CAC2EUu5vdv5FOfGPeZ35bfvFAksJaVLJCYjvzRHdIY3MlRV9UeNxcFdh7NUFP80DuXvcq3zIbBOp3NW9R3c37yC5SYD1Ly79YcnNztXHjRi1dulRLlizRvn37FBERoQEDBmj48OG66aabdMUVV1hdZu1SeLyS1ef3uC9O7Sm/GCWZEyFDmrgnBLnvQ5uaE4NCm0uh7ubToCif2WYvG6PEvChYcMxsqMxPK7/PzzAn7eSnmeEA3pO2JCm4UcWAB08ogOeeCcGoxA8//KCOHTvq888/15AhQ6wuB5dCSb57P5JuTvo7leFu2D7s9di9mntZcIwX/6Dy4ICgKCm4wZmBAqc/H1DPnCzCpJCapzjHnChanC0VnNb4X9lj79ecHkwhmRNEQxqb44PgaPfjZuZ9sOdxdPm4AcDZFeedtiJ9qtdx5R6zWd0jILw8XCOslfu+pTtMoKX732CjGhM8Z6niHHNfdyrdHI/nHTS/O/MOuO8Pms9XGJv7eZ3zaFd+7qOu+zGrM15U8+bN09ixYzVu3Dj94x//kJ+fn9UloSYrOWWGe3iapfK8wrk8QV1FJyu+JyC8PIgrONo9tnGPcYIbuUOQmrjHyvUJ67tUirLN45nCE+5jHPdxjncDVMGR8mOh4tyK7w+sZ35neprgvBviwlqZtxrQ/ITqo7S0VMuXL9eUKVO0ceNGxcTEKDExUaNHj1ZAwCW49pF30L3C/Q538JT7VnjC/QI/cywY7m7i8AQIhF9pXpMJbV67QotK8t0rJR8oPweeu8/rfn/5tRr/YHcodkezQaNeR7MpJuIq8zw5APgSxsM1F+PhKjly5Ig2bdokl8slh8OhrVu3yt/fXz169JDNZpPdbtfgwYNVv359q0sFAGsVnXQfc35X3tietdM8fpJ7OmVgpNfxpvettblgSXC05FdLFi8wSszv3by0isebOXvKH5eNqfzM/0YVjjndIYDMtwIAwBKEBQAAAACA7yMs4GIozilvjPduls/52TwZ7lllz8/fbB4KaWxOsA9p7F7RvInZUBQcbZ4QD6pvXmwIrGfdpKzCE+6L7yel4pNmg29+urshz9Po67Xyt3cDR2gzr5UE21UMT6hlK6ampqaWJfh//vnnys7OVtu2bRUXF6dhw4Zp8ODBCgnxvQkINUrhCfd2nVG+Xef997SG9nSvCahufgGVNJKefu/+WUBdc5XNOqHmhJPASLNJtaasjGqUmhNxSk6ZE06Lss1JpUVZ5RN0ypoqj1febHl6o65fnfJVlj1BDKFe+8XQJuakq9Cm5n83oAr69eunpk2bavHixVaXAquVFp1/Y3iF15youMKQt4AwqU64uS8PrCfVCTMnkAbVN+/rhLl/Ful+bVj5pFH/QPN5P//y7wa/OuUTIwLr1Z5JJR5FJ80JJp7vGs93j2R+7xjF7sb9PKkkz3x90UnzcXGuVJhp3pfklU8g9by2MLPyv9PP/8zv7bMGSJz2s4Dwy/ffBqjtTh2uvIk9/2D5ivf5h8z9RBk/97/hBmZwQJDn8WnPBTdwH3cHm/+2/YPNfXZN2A8XnTSPw4uyzf1faYG5vyvKMo/fC46Vj809jwu8/uxpEvMIbmgey4e2KA9fCG3qFc7gvvcPsub3rWVmz56thx9+WE888YSmTp1qdTmoLYrzpILDpzXfeMK4jpz5M8/5Tg+/OuYYN6i+O2QxUgqKlALrl997P+cZR/vVMd/jeb9fQM05X3I2ZePXTEml5r1R4h7DZktFmVJhlnlflFX+uNDrPItnn26UVPxs/0CvZrWmXo9Pb2RjRVxcXCdPntR7772nGTNm6MCBAxo6dKiefPJJ2Ww2awoqC4j1NMLvLV+5MHdfxXOR/sHl/y5CmrgfNyl/HNzYvd+KMI/ZA+qa+yWrFee6g+9y3PuEbKnwWHmg06nD5nnrgiPlKyd7h935B7mDE1qXN7J4N7eENmfVRgDwxnj44mE8XO0cPnxYmzdvJjwAAM5Xyakzw9fKjkH3mMdlnjAB+bm/h9zHl6FNKwaNB0e75w25jzmDosqvF1uptMh9vHmi/Niz4Lg5zslPN8dApz8+dUQVfu/QZu5FP66seOzpuffBQB4AAGoywgIAAAAAwPcRFnCpGSXuFQkOlq/Yd0ZT8mFzgoFReub764SWTxbwTDCQX8UVSuuEVGym9f5ZcU75ZAXPRfjTf1acU95w5blVJjDSveK6d9iBewX2kKblKwzS2Fup/Px8rVu3TitWrNDnn3+unTt3KiwsTAMGDFB8fLzi4uLUqVMnq8vE2ZSccq9QcfgsDaZnaTQtzvvlz60sQMDznGT+2e+0Vbk8DabeTl+1uLTwzNUzPA2YFZ7LL2+E9Q4B8A4GqNB4VQnPxKdfCkzwPBfcsHzVZSaj4hKbO3euHnjgAR04cECNGze2uhzUVMV5Xvt0d0NmWdN6rle4Um55Y3rZKvbuCf2ehvazjbHcTuRKUd496J4xXmVBAqeP/7y/O04XEGY2R1T6s/CzNH4aZ2+y927kP9fPjGLzv5HkntxZWv7d4x6b5pyS0jOlq5tW/pEV1Akxaw6MdH9nekIaos4McPCENnhCGgLCyyfhBDeoXatLAr7OKC1fXa7g6GmN8sdVoWne+8+nT+z35pmcHxDuDhOoX3Hfe/qY3Htf7XH6vrmy/WdlY3RPgIrnGL44zx0GcMK8P9cxRlDUuUMSPD8LbWpO6Dvb9wQuu+nTp+uPf/yj/vKXv+jpp5+2uhzg7AqPu8+ReDXyFGWZjz2hgac3/Xgeezezno1/kHs85973esa03pOpKxvn+vlXPs6r7LVn26d6xq1ne63nfKrnOc/4tjj3zDCWygREnNYwdlrjWFB9rzBZr4azkMbmvhu4jPbs2aPZs2dr9uzZKikp0V133aU//OEPuuaaa6wu7ZcVnjDDpvLTyps6KzQ7ZLibPo+c/d9tYN3yZg7P9Rk//zObOjzXbKQz90He516lM8+1FmZKMtxjPndzRlF2+fOVCWlcyQrX0e6GFHeDStgV5gqXnroAABcf42HGwzXY4cOHtXbtWjmdTrlcrgrhAXFxcbLZbOrfv78iIzmHDgCVKi0wgwM8cwA9gUKe6xTej8/2ve8fbIbWeRYTCogwv/c9ocYep3+He88h8r4O66nL+7vd891ccsprbmCWVJRTcVEgbwERFY8vQ5qWhyF45geGNjXDALiuAABAjUJYAAAAAAD4PsICqgujxGxc8JyYL8wsb9wv9mri907e9/C+8H5688HpzQkVQgZCvRqu6nndPBfl3X8OqGc2ExACcFHt379fK1as0IoVK7Ry5UplZmaqadOmuvHGGzVw4EANHDhQbdu2tbpM/FreF908k2WKstxN+dlejT+Z7gb/nIr/pgtPVPy8yhqMTt8nSJU3K1W2GolnspHknmAUZP77L1tVta47xCCyfEJSYD33c16TZIFqKD8/Xy1atNATTzyhp556yupyAFPRSa9VlVQW3rRm/SbdOmayVi7+u2I6NHL/zP194Jl8KZU3DHi+Pyp87mmrLJX9rJLJnefzs8oCa8p+9gurbnv/zHtyqufzyia5+ElB9XXP46/ry+2pSvniDYWERpR/L3nGrZ5AA75zAFxsnsCX0xvxi7KkkoLyhq2SUxWb9isLVKlsgr13eJ+HdzOZZE7wD4io+JqyyX9+7pAC97F7UH3JP8Q9Tq/nnkxYt7x5wDOJnn1ljVRcXKyJEyfq9ddf14wZM5SUlGR1ScCl472q6BkrjhaXhxkW557ZeOQ97q20iamS8ESp7H1LNpr77xF961d+7kSqPFDL+7Wex2c0cIWXny852wqxvzSOBqqRlJQUzZw5U/Pnz1d0dLTGjRunpKQkRUVFnfvNNY1nBeOi7PLxX2Gm+8/ZZzbwe+97Tj9X6338Lp1/k0dARHk4geeca2CEFOB+Lsi9AnVQ1NmP0wEANYeF4+EKGA/D7dChQ1q3bl2F8IA6deqoe/fuZeEBsbGxqlevku0FAPDLPMH0ZcebJ8qPMys08Hu+/0+/Bnxm6NySjeY8ohF9o9zXHNxOnxPkOSatLJjAcwwaFFX+56Ao5gYCAODDCAsAAAAAAN9HWABQDZSUlGjbtm1lF+BXrFihkydPqlmzZrLb7YqLi1N8fLxat25tdakAUKM88cQTmjdvnvbu3avAwMBzvwGwwDfffKPY2FjdeOONWrx4serUqV2TJQ8ePKhu3brp3nvv1fTp060uBwCAyy47O1ujR4+Ww+HQP//5T40ePdrqkgCfdccdd0gyJ0QBqKi0tFTLly/X1KlTtWHDBsXExCgxMVGjR49WQAAN6gAAALVFRkaG1q9fL4fDIafTqe+//14BAQGEBwBANcH5LQAAUBWEBQAAAACA7yMsAKiGiouLtX37djkcDjkcDq1fv14FBQVq27Zt2QX4uLg4NW/e3OpSAaBa27dvn9q1a6f58+crISHB6nKAM/z000+y2+3q0qWLli9fruDg4HO/yQe9++67euCBB7Rq1SrFxsZaXQ4AAJfN7t27ddtttykzM1NLlixR7969rS4J8GlMpgbOlJ2drXfffVczZszQgQMHNHToUCUlJSkuLs7q0gAAAFANnCs8wDN/ITSU1agB4HLg/BYAAKgKwgIAAAAAwPcRFgDUAHl5edqwYYOcTqdcLpfWrl2roqKisvAAzy0qKsrqUgGg2rntttt07NgxrVu3zupSgAr++9//ym63q3Hjxlq5cqUiIiKsLslSI0eO1LZt27R9+3bVrVvX6nIAALjkPvroI/3+979Xhw4d9J///EctW7a0uiTA5zGZGii3d+9evfnmm5o9e7aKi4s1evRoTZo0Se3bt7e6NAAAAFRj6enpcjqdvxgeYLfbFRISYnWpAOCTOL8FAACqgrAAAAAAAPB9hAUANVBOTo42bdokh8Mhh8Ohr7/+Wn5+furRo0dZcn9sbKzq1atndakAYLnVq1dr4MCB2rJlCyu1otrIzMzUgAEDVFxcrLVr16phw4ZWl2S5w4cPq2vXrho5cqTeeOMNq8sBAOCSKS4u1tNPP63p06dr3LhxmjlzpoKDg60uC6gVmEwNSCkpKZo5c6bmz5+v6OhojRs3TomJiWrQoIHVpQEAAKAGSktLk8vlksPhUHJysvbs2UN4AABcQpzfAgAAVUFYAAAAAAD4PsICAB9w5MgRrVmzRk6nUy6XS1u3blWdOnUqXIDv168fzQcAaq3rrrtOrVq10n/+8x+rSwGUl5enIUOGaP/+/XI6nbriiiusLqnaWLhwoe666y4lJydr0KBBVpcDAMBFl5qaqrvvvlvbtm3TG2+8obFjx1pdElCrMJkatVVpaamWL1+uadOmyeVyqVevXkpKStJdd92lwMBAq8sDAACAD/EOD/jiiy+0d+9ehYaGqlevXrLb7cxdAIBfifNbAACgKggLAAAAAADfR1gA4IMyMjK0fv36Chfgw8LCdMMNN8hms8lutys2NpaJoABqjY8//lgjR47U9u3b1bVrV6vLQS1WVFSkW265RSkpKVq3bp06dOhgdUnVzsiRI/Xdd9/pm2++YaUhAIBPWbx4scaNG6cWLVpo3rx56tatm9UlAbUOk6lR22RnZ+vdd9/VK6+8ov3792vo0KFKSkpSXFyc1aUBAACglvAOD1ixYoX27dunsLAw9ezZk/AAAKgCzm8BAICqICwAAAAAAHwfYQFALZCamiqn0ymXy6VPP/1UBw8eVEREhK6//nrFxcUpLi5OvXr1kp+fn9WlAsAlYRiGunfvrq5du+r999+3uhzUUqWlpRo9erQ+++wzrVq1SjExMVaXVC0dOHBAnTp10uOPP67nnnvO6nIAAPjVjh49qkceeUSLFy/WxIkTNWXKFCbAAxZhMjVqi/T0dM2ePVuzZs1SUVGRRo8erccee4zAOgAAAFjOe+7C559/rv3795+x8EH//v0VFBRkdakAUC1xfgsAAFQFYQEAAAAA4PsICwBqodTUVDkcDjkcDq1cuVLHjx9XdHS0BgwYUHYBngZGAL5mwYIFuvvuu/X999/rmmuusboc1EJJSUl68803tWzZMg0ePNjqcqq16dOn69lnn9X27dvVvn17q8sBAKDKPvjgAz3yyCMKDg7WO++8oyFDhlhdElCrMZkavi4lJUUzZ87U/Pnz1ahRI40fP16JiYlq0KCB1aUBAAAAlfIOD/jss8904MABhYeHq2/fvoQHAEAlOL8FAACqgrAAAAAAAPB9hAUAtVxJSYm2bt2q1atXa9WqVXI6ncrNzVWrVq00YMAAxcbGqn///rr66qutLhUAfpWSkhJ169ZNXbp00cKFC60uB7XMs88+q6lTp2rhwoX67W9/a3U51V5xcbGuvfZa1a9fX6tWrZKfn5/VJQEAcEEOHTqkCRMm6IMPPtB9992n6dOnKzIy0uqygFqPydTwRaWlpVq+fLlmzZolh8Ohnj17auLEibrrrrsUGBhodXkAAADABfEsfOB0OrVmzRrCAwDgNJzfAgAAVUFYAAAAAAD4PsICAFRQWFioL7/8UitXrtTatWu1adMm5efnq3nz5urfv7/69++v2NhYdezYkcY9ADXOxx9/rJEjR2rjxo3q06eP1eWglnjttdc0YcIEvf3227rvvvusLqfG+PLLL9W3b1/9+9//1l133WV1OQAAnJfi4mK99tpreu6551S/fn29/fbbGjx4sNVlAXBjMjV8SU5OjubNm6eXX35ZP/74o4YOHaqkpCTFxcVZXRoAAABw0XiHB6xevVoHDx4sCw+Ii4uTzWZTnz59CMoCUGtwfgsAAFQFYQEAAAAA4PsICwDwi4qLi7V9+3Y5nU65XC4lJycrMzNT0dHR6tOnj+x2u+Li4tSzZ0/5+/tbXS4AnJPNZlNQUJBWr15tdSmoBd5//32NGTNG06ZN0+OPP251OTXOuHHjtHTpUu3evVt169a1uhwAAH7R2rVrNWHCBO3atUsPPfSQ/vKXv/D9BVQzTKaGL0hPT9fs2bM1a9YsFRUVafTo0XrsscfUoUMHq0sDAAAALjlPeIDD4dDq1at19OhRRURE6Prrryc8AECtwPktAABQFYQFAAAAAIDvIywAwAUpKSnRtm3bysIDVq5cqePHj6tu3brq06dP2QX46667TkFBQVaXCwBnWLdunWJjY5WcnMxqe7ikli1bpttuu01PPPGE/va3v1ldTo107NgxXXXVVZowYYJeeOEFq8sBAKBSaWlpevLJJ/Xvf/9bgwYN0qxZs9SxY0erywJQCSZToybbunWrXnnlFS1YsEANGzbU+PHjlZiYqAYNGlhdGgAAAGAZ7/CAVatW6dixYxXCA1j4AICv4fwWAACoCsICAAAAAMD3ERYA4FcpLS3Vzp075XK5KqT3h4eHq2/fvrLZbLLb7erXr5+Cg4OtLhcAJEnDhw/Xvn37tHXrVgUEBFhdDnzQxo0bNXjwYN1+++1677335OfnZ3VJNda0adP05z//Wbt371bLli2tLgcAgDJFRUV6/fXX9ac//UlNmjTRjBkzNGzYMKvLAvALmEyNmqa0tFTLly/XrFmz5HA41KNHDz300EMaM2aMQkJCrC4PAAAAqHYqCw/wXviA8AAANR3ntwAAQFUQFgAAAAAAvo+wAAAXnecCvNPp1Nq1a7V//36FhYWpZ8+estvtiouLk81mU2hoqNWlAqilfvrpJ3Xp0kXTp0/Xo48+anU58DHffvutYmNj1b9/f33wwQcEUvxKp06dUvv27XXzzTfrzTfftLocAABkGIb+85//6KmnnlJ6erqeeeYZTZo0iYA8oAZgMjVqipycHM2bN08vv/yyfvzxRw0cOFCJiYkaPny41aUBAAAANYp3eMDKlSt1/PhxwgMA1Gic3wIAAFVBWAAAAAAA+D7CAgBccqmpqXI6nXK5XEpOTtaePXsUEBCg7t27lwUH9O/fX5GRkVaXCqAWmTx5st5++23t3r1bjRo1sroc+Iiff/5ZdrtdHTt21KeffspKjxfJv/71L91///365ptv1KlTJ6vLAQDUYp9++qn+9Kc/adu2bbrzzjs1bdo0tWzZ0uqyAJwnJlOjusvIyNCbb76pV199VXl5eUpISNBTTz2ljh07Wl0aAAAAUOOVlpZq586dcrlcZQECJ06cUHR0tPr06VO28EGvXr3k5+dndbkAUCnObwEAgKogLAAAAAAAfB9hAQAuu7S0tLIL8E6nU99//31ZeIDNZiu7CB8VFWV1qQB8WHZ2tjp06KDhw4ezWjkuirS0NNntdjVq1EgrV65U3bp1rS7JZ5SWlqp379668sor9eGHH1pdDgCgFnK5XHr22We1Zs0axcXFadq0aerVq5fVZQG4QEymRnX19ddfa8aMGVqwYIEaNGigBx98UBMmTFDDhg2tLg0AAADwWSUlJdq1axfhAQBqFM5vAQCAqiAsAAAAAAB8H2EBACyXkZGh9evXy+l0yuVyaevWrfL391f79u3LLsAPHDiQybEALrp///vfGjt2rFwul66//nqry0ENlpWVpQEDBig3N1fr169XkyZNrC7J53z66af6zW9+I5fLpRtuuMHqcgAAtcSXX36pF198UcuWLZPNZtOUKVPUr18/q8sCUEVMpkZ1UlpaquXLl2vWrFlyOBzq0aOHHnroIY0ZM0YhISFWlwcAAADUOiUlJdq2bVvZvIXk5GRlZmaqcePGio2NLVv4gPAAAFbi/BYAAKgKwgIAAAAAwPcRFgCg2jl06JDWrVundevWac2aNdqxY4f8/PzUtWtXxcbGql+/frLZbGrWrJnVpQLwAUOGDFF6erq2bt2qwMBAq8tBDZSfn68hQ4Zo7969cjqdat26tdUl+az+/furXr16WrZsmcfEV38AACAASURBVNWlAAB83I4dO/TnP/9ZH3zwgfr06aO//vWvGjhwoNVlAfiVmEyN6iAnJ0fz5s3TjBkztHv3bg0cOFCJiYkaNmwYDUcAAABANXJ6eMAXX3yhrKwsNWnSRP379yc8AIAlOL8FAACqgrAAAAAAAPB9hAUAqPaOHTum9evXa+3atVq3bp22b9+ukpIStWvXruwCvN1uV4cOHbgID+CC7d27V126dNHTTz+tp59+2upyUMMUFRXp1ltv1Zdffql169apY8eOVpfk05YvX67hw4dr69at6tGjh9XlAAB8kNPp1KxZs/Thhx+qU6dO+tOf/qSEhASrywJwkTCZGlbKyMjQm2++qVdffVW5ubm644479OSTT6pTp05WlwYAAADgPHjCAxwOh5xOp9avX094AIDLjvNbAACgKggLAAAAAADfR1gAgBonNzdXX3/9tVwul5xOp5xOpzIzM1WvXj1dd911FQIEQkJCrC4XQA0wbdo0Pffcc9q2bZs6dOhgdTmoIQzD0D333KPFixfL4XCob9++Vpfk8wzDUK9evdS1a1fNnTvX6nIAAD6itLRUH330kf7+979r8+bNstvteuKJJzR8+HAmdgM+hsnUsMK2bdv08ssva8GCBWrQoIEefPBBPfroo2rUqJHVpQEAAAD4FYqLi7V9+/ay8IB169bp5MmTatq0qfr166e4uDjZbDZ17tzZ6lIB+BDObwEAgKogLAAAAAAAfB9hAQBqvJKSEu3atassPGDt2rXav3+/AgMD1a1bt7LwgIEDB6phw4ZWlwugGiouLta1116runXras2aNfL397e6JNQAjz32mF5//XV98sknio+Pt7qcWmPu3Lm6//779eOPP6p169ZWlwMAqMEKCgq0cOFCTZkyRbt379bQoUP11FNP6YYbbrC6NACXCJOpcbmUlpZq1apVmjlzppYtW6bu3bvr4Ycf1pgxYwg3BQAAAHyUd3iAw+GQy+VSfn6+mjVrJrvdTngAgIuC81sAAKAqCAsAAAAAAN9HWAAAn5SWllYWHuByubR161YZhqG2bduWhQdwIR6Atx07dqh379568cUX9fjjj1tdDqq5559/Xn/5y180f/58JSQkWF1OrVJUVKSrr75at912m2bMmGF1OQCAGigrK0v/+te/9H//9386evSoRo0apaeeekodO3a0ujQAlxiTqXGpnTp1SosWLdLUqVO1a9cuDRo0SImJiRo2bJj8/PysLg8AAADAZXR6eIDT6dSpU6cqhAcMHjxYbdq0sbpUADUI57cAAEBVEBYAAAAAAL6PsAAAtcLJkyf15ZdfloUHeF+Ij4mJKQsP6NOnjwIDA60uF4BFpkyZoj//+c/asmWLunbtanU5qKZef/11Pfroo5o9e7YeeOABq8uplV555RU9++yz2rt3rxo1amR1OQCAGuKbb77RG2+8oblz5yokJEQPPfSQJkyYoCZNmlhdGoDLhMnUuFQyMjL05ptv6h//+IdycnJ0xx136Mknn1SnTp2sLg0AAABANUF4AICLgfNbAACgKggLAAAAAADfR1gAgFqpqKhI33zzTVl4wMqVK3X8+HFFRESoe/fuZeEB/fv3V2RkpNXlArhMSktLNWDAAOXk5Gjz5s2Eh+AM8+fP1913362//e1vmjx5stXl1Fo5OTm64oor9OSTT+qPf/yj1eUAAKqxgoICffDBB3rjjTfkcrl0zTXX6JFHHtG9996riIgIq8sDcJkxmRoX27Zt28qCaOrVq6eHHnpIjz76KKFmAAAAAM7pfMIDhgwZoiuvvNLqUgFUI5zfAgAAVUFYAAAAAAD4Pn+rCwAAKwQGBiomJkZJSUlatGiRjh07pp9//lmvvfaaOnfurKVLl+qWW25Ro0aN1Lt3byUlJWnx4sU6fPiw1aWjmpg+fbr8/Pzk5+enli1bnvN51Az+/v565513tHv3bj377LNWl4NqxuFw6J577tEjjzxS64ICqts+LyIiQnfffbfeeustlZaWXra/FwBQc/z888968skn1apVK40dO1ahoaH65JNPtGvXLiUmJhIUAKBWqW7j+ZqutLRUDodDw4cPV69evbRp0yb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Mp4yFKklRR1bmLFy4kD59+nDrrbeyZs2a/a4dNmwYQ4YMoW/fvvz444+kp6czZswYZs6cSfv27XnzzTeLKeoIVEkOh0ilTIVtS+DtY+CHe8PvqiRJioTDAiRJkiRJkiRJkiRJkiRJklSyLR4HU9rCtsVhU0qncWGTigpk0aJFvPzyy7Rr144HHniApKQkEhMTufnmm+nevTuTJ09m+vTpe7ymb9++BEGQ5zF//nzi4uK48sorI3o3EYmJhdbXw1lzoE57+PeZMP1/SuEuyAEseB7ePhrWfgodx4bNiIknRR1YmXeoObVq1SqGDh1K//79izniUiaxA/T4DLq8CWs/D7/jC54HgqgjKxmsr0XmUHJ7+vTpe33NE088EcE7iFiZqa8FtHlOOMBnzmNw3H3Q61tI6hx1VGXWnXfeSadOnZgxYwYJCQkHXH/55Zfzpz/9ifr161OtWjU6d+7M+PHjyc7O5uabby6GiCOWdBr0+g6Ouwd+/Cu81xE2z4s6KkmSyiWHBUiSJEmSJEmSJEmSJEmSJKlkyt4R7gT9xX9D84E/N0idFnVUZcby5csBOOqoo/I817p1awCWLVuWe6xFixZ07rz3BrWnn36afv36Ub9+/SKItBSo1ghOnQCnToSlE+DdE0tPs1RGKnzUE6ZfAy0Hw9nzoNllQEzUkZV5BcmpK6+8kvPPP58ePXoUZYhlR6PecNZ/oMUgmD4YpvaCjP3vGl2mWV+LlPWyEJXm+lpQi14M32/FqnDmLDjqxnCIgorM6NGjueWWW4iNPfDnPGrUKJ577rk8x9u2bUvVqlVZuHAhQVAOBtNUqARHDYNeM8P/frc9LHk56qgkSSp3vEuUJEmSJEmSJEmSJEmSJElSybN9JXx6DmxZCF3fhoa9oo6ozGndujWVKlVi7ty5eZ6bO3cuMTExHHvssbnHUlJSSElJybN2y5YtvPjii0yaNKlI4y0Vmp4HiSfDtAvg/VPgd69AgzOijmrf1kyFzy6BStXD3dcTT446onLlUHNqzJgxzJ49m1dffZW33nqrqMMsOypWhXaPQJNz4fP/gintwhwtb03y1tciZ70sAqWtvhZEkA0z/wxz/hfaDIO29zskoJhUrVq1wOfYtm0bO3bs4LjjjiMmphwNXkpoAd2nwaxb4fPLYMP3cPyDEFMx6sgkSSoXKkQdgCRJkiRJkiRJkiRJkiRJkrSHzXPh/Y6wc2PYwGwjI5mZmdx11120bt2aatWqUadOHXr37s0///lPsrOzc9dlZWUxYcIEunfvTv369alatSrHHnssTz75JDk5OXucMzk5mUcffZRZs2Zx2223sXbtWtavX8/DDz/MBx98wF133UWrVq0OGNsLL7xA06ZN6dKlS6G/71Ipvil0/xga94N/nw0LR0Ud0d4tGAkf9YC6HaDndAcFHEBR5OC+7C+nVqxYwY033siYMWNISEgotPdXrtQ9BXp9C/U6w4enw/zhUUdUfKyveZSU3AYYN24cxx9/PPHx8dSsWZPOnTszfvz4QnmfZUJpqa8FkbMTPrsI5j0DHcfC8X8td4MC0tPTueGGG2jevDlxcXE0btyYlJQUxo4dy44dO4Dizdv8mjhxIgC33357kZy/RKtQCdo9Cr8bD/OfgU//ANkZUUclSVK54LAASZIkSZIkSZIkSZIkSZIklRwbvoN/dYFqTaDnV1CjddQRlQjXXnstTz31FE8//TTp6enMmTOH1q1b07dvXz799NPcde+++y4XXXQR3bp1Y86cOSxfvpxBgwZxww038Oc//znPea+77jpeeeUVxo0bR1JSEomJiTzyyCOMGjWKu++++4BxBUHA8OHDGTx4cGG+3dKvQhyc8gIcfSt8NQjmPRV1RL8SwLc3wNdXwXF3Q5c3oXKtqIMq8YoqB3/rQDk1cOBALrnkErp161Zo761cqlQDTn0Vjv1/8M0Q+O5mIIg6qqJlfd2rkpLbABs2bGDMmDGkpaXx9ddf06xZMy699FKuu+66QnmvZUKJrq8FlLUd/n0mpH4Ap38AzS6LOqJil5qaykknncQrr7zCk08+ybp165gxYwZdu3ZlwIABPPfcc0Dx5W1+rVmzhltuuYWBAwdywQUXFPr5S43DLoLfvwdrPoZP+kL2jqgjkiSpzIsJgqCM/4tWkiRJkiRJkiRJkiRJkiRJpcKWn+Bfp0KtY6HLWxAbH3VEJcYRRxxBgwYN+Oyzz/Y4fuSRR/Lcc8/RtWtXACZPnsxjjz3G1KlT91jXv39/JkyYwLp166hRowYQNi5eddVVjB07lr/+9a9ccsklVKxYkX/84x8MHTqUPn368PLLLxMbu+8dbd955x0uuugiVq1aRfXq1Qv3TZcVcx6B7/4Mp4yGIwZEHEwA06+FhSOh44tw2MURx1N6FEUO7s3+cmrkyJE89NBDfP/998THh78fX375Zfr378+9997LHXfcUQjvtBxa8jf4cgC0/B9o/wQQE3VEhc/6uk8lIbf3p0OHDnz99dd8+eWXdOjQ4eDfWHlQouprAQVZ8HE/SP8Sun0AtY+POqJIDBgwgLFjxzJhwoQ8zfa9evWiZ8+eDB06tFjytnHjxqSmppKVlXVQsaenp5OSksKRRx7J3/72NypWrHiQ77oMWz8DPuoBSadC579DzL7/TSFJkgqmQtQBSJIkSZIkSZIkSZIkSZIkSWSmw9QzIP7wcKdzGxn3cMYZZ/D5558zaNAgvvzyS7KzswGYN29ebkMUwNlnn52nIQqgbdu27Nq1i9mzZ+ceGzduHCNHjuTqq6/m+uuvJzk5mbp16zJo0CBuueUWJkyYwDPPPLPfuJ566ikuu+wyBwXsz1HD4Ojbwh2QV78fbSzf/TkcFPC7Vx0UkE9FkYN7s6+cWrZsGcOGDWPMmDG5gwJUSA6/FDqNh/n/BzNvizqawmd93a+oc/tAzjvvPAAmTZqUr9eVCyWpvhbU9MGQ9m/o+na5HRQA8MYbbwDhYIDfmjJlCkOHDgWKL28P1rZt2+jZsydt2rRxUMCv1WkPXSdB6gfwzZCoo5EkqUxzWIAkSZIkSZIkSZIkSZIkSZKiFeTAF/0hZxd0nQyxNp7/1vDhw3nppZdYtGgRp59+OjVq1OCMM87IbarabdOmTdx1110ce+yx1K5dm5iYGGJiYhg2bBgA27dvz1377rvvApCSkpLneqeffjoQNmbty/z583n//fcZPHhwgd9fmdf2XjjsAvj8Uti+PJoYFo6GOY/CKS9Akz9EE0MpVhQ5+Fv7y6lJkyaxadMmunbtmnvOmJgY+vfvD8Cdd96Ze2zBggWF+M7LiabnhbuT//hXWPRi1NEUHuvrAUWd2wfSoEEDANLS0vL92nKhJNTXglo4BhaMCoeWJHaIOprIZGZmsmnTJqpUqUJCQsJ+1xZH3h6srKwszj//fBo1asSLL77ooIDfqtsJOr4MPz0Hi1+KOhpJksoshwVIkiRJkiRJkiRJkiRJkiQpWvOfgdQPofNEiKsXdTQl0u6m4A8++ICNGzfy5ptvEgQBf/jDH/jf//3f3HW9e/fm3nvv5corr2T+/Pnk5OQQBAGPP/44AEEQ5K7dtm3bAa+7devWfT731FNP0aVLF9q0aVOAd1ZexMDJz0OVJPjij0BwoBcUro3fh7sWH3N7uIu68q0ocvC39pdT11xzDUEQ5HmMGzcOgHvvvTf3WIsWLQr53ZcTzS6DNn+G6VfDpsLZbTpy1tcDijq3D2TVqlUAJCUl5fu15UPE9bWgti6CGUPC3z2N+0QdTaTi4uKoWbMmGRkZbNmyZb9riyNvD9ZVV11FZmYmr732GrGxsbnHW7RowZdfflng85cJTc6Bo24I70W3LY06GkmSyiSHBUiSJEmSJEmSJEmSJEmSJCk621fC93fCUcPK9W6qB1KrVi3mzp0LQKVKlejevTtvvvkmMTExvP322wBkZ2fz2WefUb9+fa677jrq1atHTEwMADt27Mhzzg4dws/7ww8/zPPcRx99BMApp5yy13g2b97MSy+9xDXXXFPwN1dexMbDKS9A2sewqBh3Vs3ZBV/8NySeDMfeU3zXLWOKIgd/zZwqIdreB7XbhTkTZEUdTcFYXw9KScjtUaNG0b59+zzHgyDgtddeA8KmZ+1DVPW1MHxzLcQ3g+OszwDnnHMOAO+8806e59q1a8f1118PFH3eHqy7776b2bNn89ZbbxEXF1co5yyz2t4P1ZqE33lJklToHBYgSZIkSZIkSZIkSZIkSZKk6My+HyrXDnc8135dffXVfP/992RmZpKWlsbDDz9MEAR069YNgIoVK9K1a1dSU1N55JFHWLduHTt27GDq1KmMGDEiz/kGDx5My5YtefbZZ3nqqadIS0sjPT2d0aNH89BDD9GoUSNuuummvcYyZswYqlevntvUpYOUeDK0GBQ28ObsLJ5rLhwJm+bAKWMgxv99vCAKOwd/zZwqIWIqQsexsPEHWDg66mgKxvp60EpCbn/77bdcc801LFiwgIyMDObNm0f//v2ZMWMGQ4YMyR3wo32Ior4W1JqpsGoKnDQcKlSOOpoS4cEHH6RZs2Zcf/31vP3222zZsoUVK1YwePBgVq9enTssAIo2bw/G2LFjueeee/jqq69ISEggJiZmj8fChQsLfI0ypUIcnPR/sHIypH0SdTSSJJU5MUEQBFEHIUmSJEmSJEmSJEmSJEmSpHJox2r45xFwwuPQ8uqooynRZs2axbPPPssnn3zC0qVLqVKlCq1ateKKK67giiuuyN0pdd26ddxxxx288847pKamUqdOHXr16kX9+vV56KGHAGjfvj3ffPMNABs2bODBBx9k0qRJLF68mCAIaNKkCb169eKOO+4gOTk5TyxBENCqVSsuueQS7rnHnXDzbfsK+GfzsGGq+RVFe63sjDDHml4A7Z8o2muVcUWVg3BoOXX11Vfz3HPP5Tnes2dP3n333UJ4x+XcN0NgxRvQZ2HY4FjaWF8PWknI7czMTCZNmsT48eP5/vvvWbFiBVWqVKFdu3YMGjSIiy++uGg/hLKiOOtrYfioBwRZcPpHUUdSoqSnp3Pffffx1ltvsWLFCurWrctpp53GX/7yF1q2bAkUXd5OnjyZ3r177zWukSNHMnDgwNw/n3322bz99tv7fS9ffPEFp5xySoE/kzLlg65QsSr8fkrUkUiSVKY4LECSJEmSJEmSJEmSJEmSJEnRmPu/8MO9cM5qqFgl6mik4vP5pbBtKXSfVrTXWfoqfN4f+i2Dqg2K9lpSWbJ9Jbx1GPzuFWh6ftTR5J/1VeVVcdXXgtq+HN48DE57CxrtvTldKpNWvAmfngt9l0G1RlFHI0lSmVEh6gAkSZIkSZIkSZIkSZIkSZJUTi17HRr3s5FR5c9hF8Paz8OG5KK05G/QoKeDAqT8qtYIGvQIc6g0sr6qvCqu+lpQy/4OlWuFNVoqTxr2gko1YPnfo45EkqQyxWEBkiRJkiRJkiRJkiRJkiRJKn45mbB+BtTvHnUkUvFL7gYxFWHdF0V3jSAH0j6FRmcV3TWksqzhmZD2cZhLpYn1VeVZcdTXwrB2GiR1gQqVo45EKl4V4qDeqbD2s6gjkSSpTHFYgCRJkiRJkiRJkiRJkiRJkorfph8hZyfUOSHqSKTiF1sNahwJG2YW3TW2LoBdmyDxpKK7hlSWJZ4MOzfC1kVRR5I/1leVZ8VRXwvDxu+hTvuoo5CiUedE2Dgr6igkSSpTHBYgSZIkSZIkSZIkSZIkSZKk4peRFv6s2jDaOKSoVG0ImWlFd/4dqeHPao2L7hpSWbY7dzJSo40jv6yvKu+Kur4Whow1ULVB1FFI0ajaIMwBSZJUaBwWIEmSJEmSJEmSJEmSJEmSpOKXtT38GVst2jikqMTGw66tRXf+rG3hz4rxRXcNqSyLTQh/7toSbRz5ZX1VeVfU9bUwZG2HiuaoyqnY6r/cp0qSpELhsABJkiRJkiRJkiRJkiRJkiQVv0o1wp+7Nkcbx0FaunQpffr0YfPmzbz55pvExMTkPjIyMqIOr1BkZ2fzxBNPcPzxx1OtWjVq1qxJt27d+OCDD/b5mpkzZ3LWWWdRq1YtEhISSElJ4bPPPsuzbsSIEXt8Znt79OrVa4/XnHrqqftcO3To0D3W3nLLLUyYMKFwPojismsTVK5ddOevXOuX65Qy5SHfdnvnnXdo1aoVsbGxB1y7a9cuHn/8cdq3b09CQgJJSUn06tWLSZMmEQRB7roNGzYwYsQIunXrRp06dahatSotW7bk0ksvZdasWXs9d1ZWFqNHj+bkk08mMTGR2rVr0759e5555hl27txZoPWlMj8Bdm4If8bViTaO/LK+llj5yfdDWb9bnz59iImJ4b777ivw+lKZXqEwMwAAIABJREFUv0VdXwtDpRqlJkfBPN2b/Nw3H8p98G+VqTzdtREq1Yo6CkmSyhSHBUiSJEmSJEmSJEmSJEmSJKn4VW0Q/ty2LNo4DsLMmTM58cQT6dGjBzVq1KBfv34EQUDfvn2jDq3QZGdn069fP26++WYGDhzI8uXLmTlzJocffjg9evTg1VdfzfOar776ik6dOpGQkMCcOXNYvHgxRxxxBF27duX999/PdwydOnU65PivvPJKbr31Vu68885DPkex27YMqtYvuvNXbfTzdZYU3TWKQHnIN4CFCxfSp08fbr31VtasWXPA9du2baNbt26MHTuWxx9/nLS0NL755huqV69Onz59mD17du7aYcOGMWTIEPr27cuPP/5Ieno6Y8aMYebMmbRv354333wzz/kHDBjAwIEDSUlJYc6cOSxYsIALL7yQIUOGcO655xZofanMT/gld6o2jDSMfLO+ljj5zff8rv+1l156iUmTJhXa+lKZv0VdXwtD1QawfXnUURwU8zSvQ7lvPpD93QeXuTwtDTkqSVIp47AASZIkSZIkSZIkSZIkSZIkFb8aR0JsdUifHnUk+7V582Z69+7Nueeey7XXXht1OEXm5ZdfZvLkyVx99dVce+21JCYm0qxZM0aPHs2RRx7J4MGD2bhxY+76nJwcrrjiCmrVqsULL7xAgwYNqFu3Ls8++yzNmzdn4MCBZGZm7nGNvn37EgRBnsf8+fOJi4vjyiuvzBPX9OnT9/qaJ554Yo91zZs354033uD+++/ntddeK5oPqTBlpsPWRVCnfdFdI74pVKkP674sumsUsvKSbwB33nknnTp1YsaMGSQkJBxw/bBhw/j+++95//336dKlC1WrVqVp06aMHTuWuLi4POsvv/xy/vSnP1G/fn2qVatG586dGT9+PNnZ2dx88817rF20aBEvv/wy7dq144EHHiApKYnExERuvvlmunfvzuTJk5k+ffohry91+bnbui/DQQHVmkQdSf5YX0uc/OZ7ftfvtmrVKoYOHUr//v0LbX2py9/iqK+FoU77Ep+jYJ7uS37vm+HQ7oOhjObp+m9Kfo5KklTKOCxAkiRJkiRJkiRJkiRJkiRJxS+mItT7Hax6J+pI9uvhhx8mNTWVu+66K+pQitQbb7wBQO/evfc4HhMTQ9++fdmwYQOvv/567vFPPvmE2bNnc95551G1atXc4xUrVuTiiy9m+fLlTJ48Ofd4ixYt6Ny5816v/fTTT9OvXz/q1y/YDqNt27blvPPO48YbbyQrK6tA5ypyq6dAhUpQt2PRXqd+Cix/o2ivUYjKS74BjB49mltuuYXY2NgDrl2zZg3PP/88l156KcnJyXs8Fx8fT0ZGBsccc0zusVGjRvHcc8/lOU/btm2pWrUqCxcuJAiC3OPLl4e7Wx911FF5XtO6dWsAli1bdsjrd1+71OTnbsv/EeZQaWN9LXHyk++Hsn63K6+8kvPPP58ePXoU6vpSlb/FVV8LKuk0WPsp7NocdST7ZZ7uXX7vmwtyH1zm8nTXJlj7WZgDkiSp0DgsQJIkSZIkSZIkSZIkSZIkSdE47EJY/S7sXB91JHsVBAGjRo2iQ4cONGzYMOpwitSaNWsASEpKyvNcgwYNAJg2bVrusY8++giAE088Mc/63cc+/PDD3GMpKSnceOONedZu2bKFF198kcGDBxcg+l+cc845rFixgrfffrtQzldkFv8NGvSAyrWL9jpHXAbrvoBNPxbtdQpBeco3YI8hGwfyz3/+k+zsbE499dQCXXPbtm3s2LGDY445hpiYmNzjrVu3plKlSsydOzfPa+bOnUtMTAzHHnvsIa/frdTkJ8DG/0D6V9DssqgjOTTW1xIlP/l+KOsBxowZw+zZs3n00UeLZH2pyd/iqq8F1aQfBDnhUJISyjzdt/zeNx/qfXCZzNNlf4cggMb9oo5EkqQyxWEBkiRJkiRJkiRJkiRJkiRJikaT86BiNZj3dNSR7NWsWbNYs2YNbdu23e+61NRULrzwQmrVqkViYiJnn302CxcuzLNu7ty59OvXj5o1a1KtWjVOPvlkJk+eTEpKCjExMcTExDBw4EDefPPN3D/HxMSwZMmSgzp/eno6N9xwA82bNycuLo7GjRuTkpLC2LFj2bFjx37fQ926dYFfmp9+be3atQAsWbJkj/cC0Lhx4zzrGzVqBMD8+fP3e02AF154gaZNm9KlS5e9Pj9u3DiOP/544uPjqVmzJp07d2b8+PH7PN/xxx8PwHvvvXfAa0dm439g9XvQYlDRXyv5dKjZBv5zT9Ffq4DKU77l17fffgtA7dq1ufHGG2nSpAmVK1fmsMMO47rrrmP9+oNrCJ84cSIAt99++x7Hk5OTefTRR5k1axa33XYba9euZf369Tz88MN88MEH3HXXXbRq1eqQ1+9WKvJztx/+ArWOheTfRx3JobG+ltp8PxQrVqzgxhtvZMyYMSQkJBT6eigl+Vuc9bWgKteBpufB3MeAIOpo9so83bf83jfvy/7ug8tkngY54Xf+sAugcq2oo5EkqUxxWIAkSZIkSZIkSZIkSZIkSZKiUSkBjhwC856EzLVRR5PHDz/8AOy9If7Xhg4dytChQ1m5ciUTJ07k008/5eKLL95jzYIFC+jYsSPffPMNr7/+Omlpabzwwgs8+eSTfP/998TFxeXu4NqvXz+CIKBv3755zj9hwgQ++uijPOdPTU3lpJNO4pVXXuHJJ59k3bp1zJgxg65duzJgwACee+653LXdunUjMTGRL7/8MvdYz549AZg8eXKe9/fuu+8C4a7ku23cuBGA+Pj4POurV68OwIYNG/b7uQVBwPDhw/e5m+ruc4wZM4a0tDS+/vprmjVrxqWXXsp111231/W7BxXs/rsrkb6/M2xCbnR20V8rpgIcdy8smwhrpx14fYTKU77l1+rVqwG4/PLLWbNmDR9//DFpaWnce++9jBkzho4dO7Jp06b9nmPNmjXccsstDBw4kAsuuCDP89dddx2vvPIK48aNIykpicTERB555BFGjRrF3XffXeD1UEryEyDtk3Dn4+PuDXOoNLK+ltp8PxQDBw7kkksuoVu3bkWyHkpJ/hZnfS0MbW6FTT/CkleijmSvzNN9y+99894c6D64TObp0vGweS4cfWvUkUiSVOaU0n+5SpIkSZIkSZIkSZIkSZIkqUxofSPExsO3N0UdSR67G3Rr1qy533UDBw6kY8eOxMfH061bN84++2ymT5/OunXrctfcdtttbNy4kSeffJLu3btTvXp1jj76aMaPH3/AZqJfnz8lJYWzzjorz/lvvfVWFi9ezJNPPsnZZ59NQkICycnJ3HHHHZxxxhl7nC8nJ4cgCAiCYI9rtG/fnhEjRjB8+HDS09NZtmwZ1157LStXrgSgatWqB/W57T5vTEzMftdNmTKF1atX079//70+P23aNF566SVOOOEE4uPjOfLII3nppZc4+eSTefrpp/nqq6/yvKZGjRrExMTk/t2VOCvehBX/hPaPA/v/fApNk3OgYS/4cgBk7f+7FqXylG/5lZGRAYQ5OHbsWI444ghq1arFZZddxq233sr8+fN57LHH9vn69PR0zjjjDLp27cqIESPyPB8EAYMGDeLSSy/lhhtuIDU1lbVr13L//fdz7bXXctFFF5GVlXXI63cr8fkJsGtLmCuNzobGfaOOpmCsr6Uy3/Nr5MiR/PTTTzz88MNFsn63Ep+/UdTXgqp1DDS/Ar69EXZujDqaPMzT/cdU0Pvm/d0Hl8k83bk+/K63uApqHBV1NJIklTkOC5AkSZIkSZIkSZIkSZIkSVJ0KiXAic/A4nGw7LWoo9nD7gbdSpUq7XfdSSedtMefd+/quWrVqtxju3cZ3b0T6W716tWjdevW+Tp/kyZN8pz/jTfeAKBXr155Xj9lyhSGDh2a++d///vfrF+/no4dO+Yeq1KlClOnTuVPf/oTjz76KA0aNKBDhw4EQcDEiRMBqF+/fu76WrVqAXvfNXX3sd1r9uWpp57isssuo3r16vtd91vnnXceAJMmTdrr87GxsezYsSNf5ywW21fC11fBEX+E5IPfJbZQdBgJOzfAl5cDxdfEmh/lKd/yKz4+HoCUlBRiY2P3eK53794AvPfee3t97bZt2+jZsydt2rThb3/7GxUrVsyzZty4cYwcOZKrr76a66+/nuTkZOrWrcugQYO45ZZbmDBhAs8888whr/+1EpufAATw5R8hayt0eD7qYArO+loq8z0/li1bxrBhwxgzZkzu74nCXP9bJTZ/o6yvBXX8X8OfX19JSavP5um+5fe+eW/2dR9cNvM0gC+vgAqV4PgHow5GkqQyyWEBkiRJkiRJkiRJkiRJkiRJilbjvtDqGvhqIGyaHXU0uapUqQLArl279rvutzuuVqgQ/i+6OTk5AGRmZrJlyxaqVKmy18b42rVr5+v8lStXznP+TZs2UaVKFRISEvZ7rv1JSEjgkUceYfHixezcuZPVq1czfPjw3Ob/E044IXft7sauFStW5DnP7h1VW7Vqtc9rzZ8/n/fff5/BgwfnO84GDRoAkJaWttfns7KyDriba7HLyYTPLoTKdeDEp4r/+lUbwqmvw4o3YNadxX/9g1De8i0/Dj/8cAASExPzPJeUlATA2rVr8zyXlZXF+eefT6NGjXjxxRf3OigAfmniTElJyfPc6aefDoTNloe6/rcxlbj83G3mbbBycpgrVfbf5FlqWF/zdf6SkO/5MWnSJDZt2kTXrl2JiYnJfezeqfzOO+/MPbZgwYJ8r/+tEpm/UdfXgqpcG343Hpa/AXMeizqaPZin+5ef++bf2t99cJnM0x8fDutrp1egUs0Dr5ckSfnmsABJkiRJkiRJkiRJkiRJkiRF74THoFZbmHoGbFsWdTTAL03pmzZtKtB54uLiSEhIICMjg61bt+Z5fl9N7/k5f82aNcnIyGDLli0FOtfeTJs2DYA//OEPucd+//vfAzBjxow863cf2900vDdPPfUUXbp0oU2bNvmOZ/dOsrubpH9t8+bNBEGQ+3dXIgTZ8NklYaNu59chNm+jXLFI7gonPwezH4DZ90cTw36Yb/t26qmnArB69eo8z+1+P8nJyXmeu+qqq8jMzOS1114jNjY293iLFi348ssvc/+8u7Fxf379WeZ3/W4lMj93+889MOdh6DASkjpHHU3hsr4W6PzFne/5cc011xAEQZ7HuHHjALj33ntzj7Vo0SLf63+tROZvSamvBZX8ezj+rzDzz7D0laijyWWeHpq93Tf/1v7ug8tcni55GWbeCu0eKXv1VZKkEsRhAZIkSZIkSZIkSZIkSZIkSYpehcpw2j/DHVY/6l4iGhqPOeYYAFasWFHgc/Xq1Qv4ZUfu3VJTU5k/f36Bz3/OOecA8M477+R5rl27dlx//fX7ff26deuoUKFCbiP+bps3b2bUqFFcdNFFtGrVKvf4aaedRps2bXj99dfJyMjIPZ6dnc2rr75KkyZNOOuss/Z6rc2bN/PSSy9xzTXX7DOeUaNG0b59+zzHgyDgtddeA6B37955nl+5ciXwy99d5IIs+HIArJoCXd6CmkdHG88RA+DkZ2HWnTDrNiCINp5fKU/5ll9nnnkmjRo14t13390j3yDcgRigX79+exy/++67mT17Nm+99RZxcXH7PX+HDh0A+PDDD/M899FHHwFwyimnHPL63UpcfgIQhA26P/wlHKbR7LKoAyp81tcCKe58L6lKXP6WtPpaUEfdCEcOhS/+CMv/HnU0gHm6P/m9b/7tmgPdBx+qEpeny16DLy+Ho26C1kOjjkaSpDLNYQGSJEmSJEmSJEmSJEmSJEkqGSrXhm7vQ8U4+KAzbJ4XaTht27YlKSmJWbNmFfhcDzzwAHXq1GHo0KH861//YuvWrfzwww8MGDCA+vXrF/j8Dz74IM2aNeP666/n7bffZsuWLaxYsYLBgwezevXqPZqkunXrRmJi4h47i0PYiD9gwAAWLFhAZmYmX3/9NWeccQbJyckMHz58j7UVKlRg9OjRrF+/ngEDBpCamkp6ejrXXHMNP/30EyNHjqRKlSp7jXXMmDFUr149t7FrX7799luuueYaFixYQEZGBvPmzaN///7MmDGDIUOG5DYs/9rMmTMB6NGjx0F9bkUqOwOmXRA2/XV5A5K6RB1RqMVVcMoLMOcx+OxiyN4RdURA+cu3/IiLi2PUqFGkp6dz0UUX8dNPP7Fx40bGjRvHgw8+SIcOHbjuuuty148dO5Z77rmHr776ioSEBGJiYvZ4LFy4cI/zDx48mJYtW/Lss8/y1FNPkZaWRnp6OqNHj+ahhx6iUaNG3HTTTYe8frcSlZ8QfvenXQRzn4COL0LzgVFHVHSsr4esuPO9pCpR+VtS62tBnfAotBgE0y6EhWOijsY8PYD83Df/2sHeBx+KEpWnC0fBZ5dAy8HQ7q9RRyNJUtkXSJIkSZIkSZIkSZIkSZIkSSVJZnoQvHdKEEysHQSr3os0lNtuuy2IjY0NVq5cmXvsiy++CAi3ZM993H777UEQBHmOn3XWWbmvmzdvXtCvX7+gRo0aQbVq1YJOnToFH3/8cdC1a9egWrVqBT7/unXrgqFDhwbNmjULKlWqFDRo0CC46KKLgvnz5+/xnjp37hzUrl07+Pzzz/c4/q9//Svo06dPUL9+/aBq1arBMcccE9x7773B9u3b9/n5fPvtt0GvXr2CGjVqBNWrVw+6desWTJs2bZ/rc3JyghYtWgR33XXX/j72ICMjI5g4cWJwzjnnBM2bNw/i4uKCmjVrBl27dg3Gjx+/z9edf/75QaNGjYKdO3fu9/xFbvvKIHi3QxBMrBUEaZ9GG8u+pH4Y5tjbxwXB5nlRRxMEQfnKt0mTJuU5/+7HyJEj9/r5fP7550HPnj2DmjVrBpUrVw5at24d3H333Xly9KyzztrnuXc/vvjiiz1es379+mDYsGFB69atg7i4uKBy5cpB8+bNg2uvvTZITU3NE0t+1wdBCcrPIAiCTXOC4O1jg2BinSBInRp1NMXH+loq8v1Qfj8EQRBcddVVe31Nz549C7y+xORvaaivBTXrjiD4W0wQfPfnIMjJjjQU83TfeXco980Hex/8a6UuT3OyguDbm8Lv8KyDf5+SJKlgYoIgCPYyQ0CSJEmSJEmSJEmSJEmSJEmKTnYGfDUQlk6AtvfCUTdDTIViD2PTpk0cffTRnH322YwYMaJIrtG6dWt27NjB0qVLi+T85cWsWbNo164d48eP56KLLooukLSPw51UK9WALm9CjSOji+VAti0Jd2fePBdOeAKaDwBiIgvHfCu7Skx+EsCCUfDtDVDzaDh1AsQfFmE8EbC+Kp9KTP6WpvpaUItfgq+vguTfQ8cXIa5eJGGYp6VHicjTjDXwxWWQ9gl0GAmH/1c0cUiSVA4V/7/oJEmSJEmSJEmSJEmSJEmSpAOpWAU6vQzt/grf/z+Y2gN2rCr2MGrWrMmkSZN4/fXXGT58+CGfJzU1lTp16rBr1649ji9ZsoSFCxfSrVu3goZari1atIg//OEP3HrrrdE1SOXsgu/vhA9Ph7odoOeXJb+RMf5w6D4NWlwFXw+CqWfCtmWRhWO+lU0lIj8hHI7xUU+Y/j/QajB0/6T8DQoA66vypUTkb2msrwXV7DJI+Rg2zYF32sLq9yMJwzwtHUpEnq5+N/yublkA3T91UIAkScXMYQGSJEmSJEmSJEmSJEmSJEkquVrfAD0+h23LYXIbmPckBNnFGkK7du345ptvmDJlCps3bz7k82zYsIGrrrqK5cuXs337dr7++msuvPBCatSowZ133lmIEZc/zz33HPfffz/3339/NAGkfQJT2sGcx+Ck4dD5H1CpZjSx5FeFytDukXBowLYlMLk1zLwFdh36d70gzLeyJ/L8zNoG/7k7rCFbF8HpH8Hxfw2/++WZ9VUHIfL8Lc31taAST4YzZ0LSaTD1DPi8f7hzezEzT0u+SPN0x2r4/FKY2gvqp0Cv76DOicUfhyRJ5VxMEARB1EFIkiRJkiRJkiRJkiRJkiRJ+5W9A378K8x+CGq2hpP+D+p2ijqqfPnwww8ZPnw43333HatWraJ27dqkpKRwzz330Lx586jD06HYuR5m3goLRkL9bnDi8NK923HOLvjp/8LG6phYOOYOaHUtxFSMOrJ8M99EkANLXobv/gw5mdDmz3Dkn6BilagjK1msryqJylp9LaiVk+Cb62DXRjj27lJZm83TMibIgYWj4LuboVICnPA4ND0v6qgkSSq3HBYgSZIkSZIkSZIkSZIkSZKk0mPzPPjmWljzERxxObS9H6okRR2VypucXbBwJMy6A2KrQ/snock5UUdVeDLXhQMDFjwPNduEu7A36Bl1VNLBWzUFZv4ZNs+Flv8Dx9wFcYlRR1WyWV9VEpT1+loQWdvgh/tg7mNQ6zg48Rmoe0rUUak8WvsZfDMENs2Go26Co2+H2GpRRyVJUrnmsABJkiRJkiRJkiRJkiRJkiSVPktfhW9vhF2boOXVcNQwqJIcdVQq63J2weIXYfYDsH0FtL4+bEKOjY86sqKxeW64Y+zKSVC7XdgQdtgFEBMbdWRSXjm7YNkEmPMYbJgJjftCu4choVXUkZUu1ldFobz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"text/plain": [ "" ] @@ -204,54 +204,54 @@ "name": "stdout", "output_type": "stream", "text": [ - "csa2 | {'hgnc': '20266'}\n", - "csa4 | {'hgnc': '1974'}\n", - "csa8 | {'hgnc': '7562'}\n", - "csa7 | {'hgnc': '7794'}\n", - "csa3 | {'hgnc': '5991'}\n", - "csa10 | {'hgnc': '6859'}\n", - "csa13 | {'hgnc': '11312'}\n", - "csa17 | {'hgnc': '15631'}\n", - "csa11 | {'hgnc': '10059'}\n", - "csa12 | {'hgnc': '1974'}\n", - "csa15 | {'hgnc': '660'}\n", - "csa21 | {}\n", - "sa1 | {}\n", - "sa3 | {'hgnc': '30834'}\n", - "sa10 | {'hgnc': '16400'}\n", - "sa14 | {'pubmed': '32172672'}\n", - "sa11 | {'hgnc': '12033'}\n", - "sa25 | {'hgnc': '1499'}\n", - "sa38 | {'hgnc': '12036'}\n", - "sa41 | {}\n", - "sa42 | {}\n", - "sa48 | {'hgnc': '18348'}\n", - "sa49 | {'hgnc': '7562'}\n", - "sa50 | {'hgnc': '10059'}\n", - "sa56 | {'hgnc': '16379'}\n", - "sa65 | {'hgnc': '7797'}\n", - "sa67 | {'hgnc': '17274'}\n", - "sa70 | {'hgnc': '660'}\n", - "sa74 | {'hgnc': '16288'}\n", - "sa75 | {'hgnc': '1144'}\n", - "sa76 | {'hgnc': '10065'}\n", - "sa77 | {'hgnc': '29938'}\n", - "sa81 | {'hgnc': '7794'}\n", - "sa34 | {'uniprot': 'P0DTC2'}\n", - "sa83 | {'ncbiprotein': '1796318600'}\n", - "sa87 | {'hgnc': '9075'}\n", - "sa88 | {'hgnc': '5434'}\n", - "sa92 | {'hgnc': '5992'}\n", - "sa93 | {'hgnc': '11849'}\n", - "sa132 | {'ncbiprotein': 'BCD58760'}\n", - "sa141 | {}\n", - "sa142 | {}\n" + "Hops Complex_complex | {'uniprot': 'J9TC74'}\n", + "IKBKG/IKBKB/CHUK_complex | {'hgnc': '1974'}\n", + "LPS/TLR4/MYD88_complex | {'hgnc': '11850'}\n", + "P65/P015_complex | {'hgnc': '7794'}\n", + "LPS/TNF α/IL-1_complex | {'hgnc': '11916'}\n", + "TAB2/TAB3/TAK1_complex | {'hgnc': '17075'}\n", + "TRIM27/TRIM21_complex | {'hgnc': '11312'}\n", + "TLR7/8/9_complex | {'hgnc': '15631'}\n", + "TRIM30a/TRIM38_complex | {'hgnc': '10059'}\n", + "NEMO/IKKA/IKKB_complex | {'hgnc': '1974'}\n", + "TRIM14/TRIM23_complex | {'hgnc': '16283'}\n", + "NFKB1:NFKNIA_complex | {}\n", + "Orf3a | {}\n", + "TRIM59 | {'pubmed': '22588174'}\n", + "NLRP3 | {'hgnc': '16400'}\n", + "PYCARD_ubiquitinated_ubiquitinated_ubiquitinated | {'pubmed': '32172672'}\n", + "TRAF3 | {'hgnc': '12033'}\n", + "CASP1 | {'hgnc': '1499'}\n", + "TRAF6 | {'hgnc': '12036'}\n", + "double-stranded RNA_rna | {}\n", + "ssRNA_rna | {}\n", + "TICAM1 | {'hgnc': '18348'}\n", + "MYD88 | {'hgnc': '7562'}\n", + "TRIM38 | {'hgnc': '10059'}\n", + "TRIM22 | {'hgnc': '16379'}\n", + "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated | {'hgnc': '7797'}\n", + "TRIM29 | {'hgnc': '17274'}\n", + "TRIM23 | {'hgnc': '660'}\n", + "TRIM9 | {'hgnc': '16288'}\n", + "BTRC | {'hgnc': '1144'}\n", + "TRIM39 | {'hgnc': '10065'}\n", + "CACTIN | {'hgnc': '29938'}\n", + "NFKB1 | {'hgnc': '7794'}\n", + "S | {'uniprot': 'P0DTC2'}\n", + "E | {'ncbiprotein': '1796318600'}\n", + "SERPINF2 | {'hgnc': '9075'}\n", + "IFNB1 | {'hgnc': '5434'}\n", + "IL1b | {'hgnc': '5992'}\n", + "TLR3 | {'hgnc': '11849'}\n", + "ORF8b | {'ncbiprotein': 'BCD58760'}\n", + "IRF6 | {}\n", + "TLR4 | {}\n" ] } ], "source": [ - "for initial_name, initial in tm.initials.items():\n", - " print(f\"{initial_name} | {initial.concept.identifiers}\")" + "for initial in tm.initials.values():\n", + " print(f\"{initial.concept.display_name} | {initial.concept.identifiers}\")" ] } ], From 7f122b510d41f670e575b36503277bc8cb841fff Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 23 Apr 2024 10:07:43 -0400 Subject: [PATCH 34/44] Add script for processing sbml qual models from covid-19 disease map --- .../process_covid19_diseasemaps_sbml.py | 28 + .../stockflow_amr/Apoptosis.json | 633 +++ .../stockflow_amr/Coagulation-pathway.json | 2524 ++++++++++ .../stockflow_amr/ER_Stress.json | 3334 +++++++++++++ .../stockflow_amr/ETC.json | 1651 +++++++ .../stockflow_amr/E_protein.json | 619 +++ .../stockflow_amr/HMOX1_Pathway.json | 3036 ++++++++++++ .../stockflow_amr/IFN-lambda.json | 853 ++++ .../stockflow_amr/Interferon1.json | 2166 +++++++++ .../stockflow_amr/JNK_pathway.json | 348 ++ .../stockflow_amr/Kynurenine_pathway.json | 2722 +++++++++++ .../stockflow_amr/NLRP3_Activation.json | 1265 +++++ .../stockflow_amr/Nsp14.json | 2959 ++++++++++++ .../stockflow_amr/Nsp4_Nsp6.json | 1294 +++++ .../stockflow_amr/Nsp9_protein.json | 4280 +++++++++++++++++ .../stockflow_amr/Orf10_Cul2_pathway.json | 1129 +++++ .../stockflow_amr/Orf3a.json | 798 +++ .../stockflow_amr/PAMP_signaling.json | 1409 ++++++ .../stockflow_amr/Pyrimidine_deprivation.json | 1712 +++++++ .../stockflow_amr/RTC-and-transcription.json | 670 +++ .../stockflow_amr/Renin_angiotensin.json | 1421 ++++++ .../stockflow_amr/TGFB_pathway.json | 345 ++ .../Virus_replication_cycle.json | 4138 ++++++++++++++++ tests/test_sbml_qual.py | 4 + 24 files changed, 39338 insertions(+) create mode 100644 scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Apoptosis.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Coagulation-pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/ER_Stress.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/ETC.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/E_protein.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/HMOX1_Pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/IFN-lambda.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Interferon1.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/JNK_pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Kynurenine_pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/NLRP3_Activation.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp14.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp4_Nsp6.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp9_protein.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Orf10_Cul2_pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Orf3a.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/PAMP_signaling.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Pyrimidine_deprivation.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/RTC-and-transcription.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Renin_angiotensin.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/TGFB_pathway.json create mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Virus_replication_cycle.json diff --git a/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py new file mode 100644 index 000000000..e09bd9fc4 --- /dev/null +++ b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py @@ -0,0 +1,28 @@ +import json +import tqdm +import requests + +from mira.modeling.amr.stockflow import template_model_to_stockflow_json +from mira.sources.sbml import template_model_from_sbml_qual_string + + +models = ['Apoptosis', 'Coagulation-pathway', 'ER_Stress', 'ETC', 'E_protein', + 'HMOX1_Pathway', 'IFN-lambda', 'Interferon1', 'JNK_pathway', + 'Kynurenine_pathway', 'NLRP3_Activation', 'Nsp14', 'Nsp4_Nsp6', + 'Nsp9_protein', 'Orf10_Cul2_pathway', 'Orf3a', 'PAMP_signaling', + 'Pyrimidine_deprivation', 'RTC-and-transcription', + 'Renin_angiotensin', 'TGFB_pathway', 'Virus_replication_cycle'] + + +SBML_URL_BASE = ('https://git-r3lab.uni.lu/covid/models/-/raw/master/' + 'Executable%20Modules/SBML_qual_build/sbml') + + +if __name__ == "__main__": + for model in tqdm.tqdm(models): + url = f'{SBML_URL_BASE}/{model}_stable.sbml' + model_text = requests.get(url).text + tm = template_model_from_sbml_qual_string(model_text) + regnet = template_model_to_stockflow_json(tm) + with open(f'stockflow_amr/{model}.json', 'w') as fh: + json.dump(regnet, fh, indent=1) diff --git a/scripts/covid19_diseasemaps/stockflow_amr/Apoptosis.json b/scripts/covid19_diseasemaps/stockflow_amr/Apoptosis.json new file mode 100644 index 000000000..861860b64 --- /dev/null +++ b/scripts/covid19_diseasemaps/stockflow_amr/Apoptosis.json @@ -0,0 +1,633 @@ +{ + "header": { + "name": "SIR Model", + "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/stockflow_v0.1/stockflow/stockflow_schema.json", + "description": "SIR Model", + "schema_name": "stockflow", + "model_version": "0.1" + }, + "properties": {}, + "model": { + "flows": [ + { + "id": "0", + "name": "tr_csa11", + "upstream_stock": "sa43", + "downstream_stock": null + }, + { + "id": "1", + "name": "tr_csa2", + "upstream_stock": null, + "downstream_stock": "csa2" + }, + { + "id": "2", + "name": "tr_csa1", + "upstream_stock": null, + "downstream_stock": "csa1" + }, + { + "id": "3", + "name": "tr_csa3", + "upstream_stock": "csa11", + "downstream_stock": null + }, + { + "id": "4", + "name": "tr_csa6", + "upstream_stock": null, + "downstream_stock": "csa6" + }, + { + "id": "5", + "name": "tr_csa5", + "upstream_stock": null, + "downstream_stock": "csa5" + }, + { + "id": "6", + "name": "tr_sa29", + "upstream_stock": "sa42", + "downstream_stock": null + }, + { + "id": "7", + "name": "tr_sa10", + "upstream_stock": null, + "downstream_stock": "sa10" + }, + { + "id": "8", + "name": "tr_sa79", + "upstream_stock": "sa29", + "downstream_stock": null + }, + { + "id": "9", + "name": "tr_sa31", + "upstream_stock": null, + "downstream_stock": "sa31" + }, + { + "id": "10", + "name": "tr_sa50", + "upstream_stock": null, + "downstream_stock": "sa50" + }, + { + "id": "11", + "name": "tr_sa25", + "upstream_stock": null, + "downstream_stock": "sa25" + }, + { + "id": "12", + "name": "tr_sa40", + "upstream_stock": null, + "downstream_stock": "sa40" + }, + { + "id": "13", + "name": "tr_sa19", + "upstream_stock": null, + "downstream_stock": "sa19" + }, + { + "id": "14", + "name": "tr_sa17", + "upstream_stock": null, + "downstream_stock": "sa17" + }, + { + "id": "15", + "name": "tr_sa14", + "upstream_stock": null, + "downstream_stock": "sa14" + }, + { + "id": "16", + "name": "tr_sa41", + "upstream_stock": null, + "downstream_stock": "sa41" + }, + { + "id": "17", + "name": "tr_sa89", + "upstream_stock": null, + "downstream_stock": "sa89" + } + ], + "stocks": [ + { + "id": "sa43", + "name": "Orf7a", + "grounding": { + "identifiers": { + "ncbigene": "1489674" + }, + "modifiers": {} + } + }, + { + "id": "sa69", + "name": "E", + "grounding": { + "identifiers": { + "pubmed": "32785274" + }, + "modifiers": {} + } + }, + { + "id": "sa79", + "name": "BAD", + "grounding": { + "identifiers": { + "uniprot": "Q92934" + }, + "modifiers": {} + } + }, + { + "id": "sa2", + "name": "FASLG", + "grounding": { + "identifiers": { + "uniprot": "P48023" + }, + "modifiers": {} + } + }, + { + "id": "csa2", + "name": "FAS/FASL_complex", + "grounding": { + "identifiers": { + "uniprot": "P25445" + }, + "modifiers": {} + } + }, + { + "id": "sa3", + "name": "TNF", + "grounding": { + "identifiers": { + "uniprot": "P01375" + }, + "modifiers": {} + } + }, + { + "id": "csa1", + "name": "TNF/TNFRSF1A_complex", + "grounding": { + "identifiers": { + "uniprot": "P01375" + }, + "modifiers": {} + } + }, + { + "id": "csa11", + "name": "BCL2/MCL1/BCL2L1_complex", + "grounding": { + "identifiers": { + "uniprot": "P10415" + }, + "modifiers": {} + } + }, + { + "id": "sa10", + "name": "FADD", + "grounding": { + "identifiers": { + "uniprot": "Q13158" + }, + "modifiers": {} + } + }, + { + "id": "sa44", + "name": "TRADD", + "grounding": { + "identifiers": { + "uniprot": "Q15628" + }, + "modifiers": {} + } + }, + { + "id": "csa6", + "name": "TRADD/FADD_complex", + "grounding": { + "identifiers": { + "uniprot": "Q13158" + }, + "modifiers": {} + } + }, + { + "id": "sa25", + "name": "CYCS", + "grounding": { + "identifiers": { + "uniprot": "P99999" + }, + "modifiers": {} + } + }, + { + "id": "sa27", + "name": "APAF1", + "grounding": { + "identifiers": { + "uniprot": "O14727" + }, + "modifiers": {} + } + }, + { + "id": "sa47", + "name": "CASP9_cell", + "grounding": { + "identifiers": { + "uniprot": "P55211" + }, + "modifiers": {} + } + }, + { + "id": "sa29", + "name": "AKT1", + "grounding": { + "identifiers": { + "uniprot": "P31749" + }, + "modifiers": {} + } + }, + { + "id": "csa5", + "name": "Apoptosome_complex", + "grounding": { + "identifiers": { + "uniprot": "O14727" + }, + "modifiers": {} + } + }, + { + "id": "sa42", + "name": "M", + "grounding": { + "identifiers": { + "pubmed": "16845612" + }, + "modifiers": { + "property": "ncbiprotein:APO40582" + } + } + }, + { + "id": "csa3", + "name": "BAD/BBC3/BCL2L11_complex", + "grounding": { + "identifiers": { + "uniprot": "O43521" + }, + "modifiers": {} + } + }, + { + "id": "sa89", + "name": "BID", + "grounding": { + "identifiers": { + "uniprot": "P55957" + }, + "modifiers": {} + } + }, + { + "id": "sa31", + "name": "BAX", + "grounding": { + "identifiers": { + "uniprot": "Q07812" + }, + "modifiers": {} + } + }, + { + "id": "sa48", + "name": "Orf3a", + "grounding": { + "identifiers": { + "pubmed": "32555321" + }, + "modifiers": {} + } + }, + { + "id": "sa50", + "name": "MAPK14", + "grounding": { + "identifiers": { + "uniprot": "Q16539" + }, + "modifiers": {} + } + }, + { + "id": "sa19", + "name": "CASP9_cell_active", + "grounding": { + "identifiers": {}, + "modifiers": {} + } + }, + { + "id": "sa14", + "name": "CASP8", + "grounding": { + "identifiers": { + "uniprot": "Q14790" + }, + "modifiers": {} + } + }, + { + "id": "sa40", + "name": "CASP7", + "grounding": { + "identifiers": { + "uniprot": "P55210" + }, + "modifiers": {} + } + }, + { + "id": "sa17", + "name": "CASP3", + "grounding": { + "identifiers": { + "uniprot": "P42574" + }, + "modifiers": {} + } + }, + { + "id": "sa75", + "name": "Orf6", + "grounding": { + "identifiers": { + "ncbigene": "1489673" + }, + "modifiers": {} + } + }, + { + "id": "sa76", + "name": "S", + "grounding": { + "identifiers": { + "pubmed": "32075877" + }, + "modifiers": {} + } + }, + { + "id": "sa73", + "name": "Orf8a", + "grounding": { + "identifiers": { + "ncbigene": "1489676" + }, + "modifiers": {} + } + }, + { + "id": "sa74", + "name": "N", + "grounding": { + "identifiers": { + "pubmed": "16112641" + }, + "modifiers": {} + } + }, + { + "id": "sa72", + "name": "Orf3b", + "grounding": { + "identifiers": { + "ncbigene": "1489670" + }, + "modifiers": {} + } + }, + { + "id": "sa77", + "name": "Orf9b", + "grounding": { + "identifiers": { + "ncbigene": "1489679" + }, + "modifiers": {} + } + }, + { + "id": "sa41", + "name": "Apoptosis_phenotype", + "grounding": { + "identifiers": { + "pubmed": "31226023" + }, + "modifiers": {} + } + } + ], + "auxiliaries": [], + "observables": [], + "links": [] + }, + "semantics": { + "ode": { + "parameters": [], + "initials": [ + { + "target": "sa43", + "expression": "3", + "expression_mathml": "3" + }, + { + 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"csa429", + "name": "Host_space_translation_space_complex_complex_epithelial_space_cell", + "grounding": { + "identifiers": {}, + "modifiers": { + "property": "GO:0070992" + } + } + }, + { + "id": "sa2345", + "name": "S_space_ds_space_sgmRNA_rna", + "grounding": { + "identifiers": {}, + "modifiers": {} + } + }, + { + "id": "sa2295", + "name": "S_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "grounding": { + "identifiers": {}, + "modifiers": {} + } + }, + { + "id": "sa2325", + "name": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "grounding": { + "identifiers": {}, + "modifiers": {} + } + }, + { + "id": "sa2245", + "name": "Orf7a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "grounding": { + "identifiers": { + "ncbigene": "43740573" + }, + "modifiers": {} + } + }, + { + "id": "sa1986", + "name": "Orf7a_SARS-CoV-2_space_virion", + "grounding": { + "identifiers": { + "ncbigene": "43740573" + }, + 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"sa2378", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2379", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2398", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2400", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2401", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2402", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2619", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2624", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2625", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2626", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2627", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2628", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2629", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2630", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2631", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2632", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "csa526", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2645", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2646", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2647", + "expression": "3", + "expression_mathml": "3" + }, + { + "target": "sa2697", + "expression": "3", + "expression_mathml": "3" + } + ], + "time": { + "id": "t" + } + } + }, + "metadata": {} +} \ No newline at end of file diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index 1cb16261e..a3b73ef3c 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -1,3 +1,7 @@ +""" +These tests are smoke tests to determine whether we can convert SBML Qual documents into MIRA +template models. They do not test for correctness. +""" import requests from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string From 47a6575d682abdf9de6c6c0054a2a04a5116dfe5 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 23 Apr 2024 20:29:04 -0400 Subject: [PATCH 35/44] Delete stockflow amrs, add regnet amr for BIOMD0000000562.json --- mira/modeling/amr/regnet.py | 251 +- .../regnet_amr_sbml/BIOMD0000000562.json | 445 ++ .../stockflow_amr/Apoptosis.json | 633 --- .../stockflow_amr/Coagulation-pathway.json | 2524 ---------- .../stockflow_amr/ER_Stress.json | 3334 ------------- .../stockflow_amr/ETC.json | 1651 ------- .../stockflow_amr/E_protein.json | 619 --- .../stockflow_amr/HMOX1_Pathway.json | 3036 ------------ .../stockflow_amr/IFN-lambda.json | 853 ---- .../stockflow_amr/Interferon1.json | 2166 --------- .../stockflow_amr/JNK_pathway.json | 348 -- .../stockflow_amr/Kynurenine_pathway.json | 2722 ----------- .../stockflow_amr/NLRP3_Activation.json | 1265 ----- .../stockflow_amr/Nsp14.json | 2959 ------------ .../stockflow_amr/Nsp4_Nsp6.json | 1294 ----- .../stockflow_amr/Nsp9_protein.json | 4280 ----------------- .../stockflow_amr/Orf10_Cul2_pathway.json | 1129 ----- .../stockflow_amr/Orf3a.json | 798 --- .../stockflow_amr/PAMP_signaling.json | 1409 ------ .../stockflow_amr/Pyrimidine_deprivation.json | 1712 ------- .../stockflow_amr/RTC-and-transcription.json | 670 --- .../stockflow_amr/Renin_angiotensin.json | 1421 ------ .../stockflow_amr/TGFB_pathway.json | 345 -- .../Virus_replication_cycle.json | 4138 ---------------- 24 files changed, 600 insertions(+), 39402 deletions(-) create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Apoptosis.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Coagulation-pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/ER_Stress.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/ETC.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/E_protein.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/HMOX1_Pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/IFN-lambda.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Interferon1.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/JNK_pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Kynurenine_pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/NLRP3_Activation.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp14.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp4_Nsp6.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Nsp9_protein.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Orf10_Cul2_pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Orf3a.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/PAMP_signaling.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Pyrimidine_deprivation.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/RTC-and-transcription.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Renin_angiotensin.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/TGFB_pathway.json delete mode 100644 scripts/covid19_diseasemaps/stockflow_amr/Virus_replication_cycle.json diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index b7f7d7af4..8482a687e 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -2,8 +2,11 @@ at https://github.com/DARPA-ASKEM/Model-Representations/tree/main/regnet. """ -__all__ = ["AMRRegNetModel", "ModelSpecification", - "template_model_to_regnet_json"] +__all__ = [ + "AMRRegNetModel", + "ModelSpecification", + "template_model_to_regnet_json", +] import json @@ -22,10 +25,12 @@ logger = logging.getLogger(__name__) -SCHEMA_VERSION = '0.2' -SCHEMA_URL = ('https://raw.githubusercontent.com/DARPA-ASKEM/' - 'Model-Representations/regnet_v%s/regnet/' - 'regnet_schema.json') % SCHEMA_VERSION +SCHEMA_VERSION = "0.2" +SCHEMA_URL = ( + "https://raw.githubusercontent.com/DARPA-ASKEM/" + "Model-Representations/regnet_v%s/regnet/" + "regnet_schema.json" +) % SCHEMA_VERSION class AMRRegNetModel: @@ -42,12 +47,18 @@ def __init__(self, model: Model): self.states = [] self.transitions = [] self.parameters = [] - self.model_name = model.template_model.annotations.name if \ - model.template_model.annotations and \ - model.template_model.annotations.name else "Model" - self.model_description = model.template_model.annotations.description \ - if model.template_model.annotations and \ - model.template_model.annotations.description else self.model_name + self.model_name = ( + model.template_model.annotations.name + if model.template_model.annotations + and model.template_model.annotations.name + else "Model" + ) + self.model_description = ( + model.template_model.annotations.description + if model.template_model.annotations + and model.template_model.annotations.description + else self.model_name + ) self.rates = [] self.observables = [] @@ -62,25 +73,27 @@ def __init__(self, model: Model): # on the key otherwise vmap[key] = name = var.concept.name or str(key) state_data = { - 'id': name, - 'name': name, - 'grounding': { - 'identifiers': {k: v for k, v in - var.concept.identifiers.items() - if k != 'biomodels.species'}, - 'context': var.concept.context, + "id": name, + "name": name, + "grounding": { + "identifiers": { + k: v + for k, v in var.concept.identifiers.items() + if k != "biomodels.species" + }, + "context": var.concept.context, }, } - initial = var.data.get('expression') + initial = var.data.get("expression") if initial is not None: # Here, initial is a SympyExprStr, and if its # value is a float, we export it as a float, # otherwise we export it as a string try: initial_float = float(initial.args[0]) - state_data['initial'] = initial_float + state_data["initial"] = initial_float except TypeError: - state_data['initial'] = str(initial) + state_data["initial"] = str(initial) self.states.append(state_data) self._states_by_id[name] = state_data @@ -102,8 +115,16 @@ def __init__(self, model: Model): # Natural degradation corresponds to an inherent negative # sign on the state so we have special handling for it - if natdeg or natrep or (contprod and (transition.control[0].key - == transition.produced[0].key)): + if ( + natdeg + or natrep + or ( + contprod + and ( + transition.control[0].key == transition.produced[0].key + ) + ) + ): if natdeg: var = vmap[transition.consumed[0].key] sign = False @@ -120,9 +141,9 @@ def __init__(self, model: Model): # We just choose an arbitrary one deterministically rate_const = sorted(pnames)[0] if pnames else None if state_for_var: - state_for_var['rate_constant'] = rate_const + state_for_var["rate_constant"] = rate_const if state_for_var: - state_for_var['sign'] = sign + state_for_var["sign"] = sign if transition.template.rate_law: rate_law = transition.template.rate_law.args[0] @@ -134,25 +155,43 @@ def __init__(self, model: Model): # - ControlledReplication / GroupedControlledProduction # - ControlledDegradation else: + # group controlled production, + # signs for each of the parent + # in a for loop, loop thorugh the parents and create a transition for each parent + + # single upstream controller and and downstream target in amr + # if isinstance( + # transition.template, GroupedControlledDegradation + # ): + # continue + # pass tid = f"t{idx + 1}" - transition_dict = {'id': tid} + transition_dict = {"id": tid} # If we have multiple controls then the thing that replicates # is both a control and a produced variable. if len(transition.control) > 1: - indep_ctrl = {c.key for c in transition.control} - \ - {transition.produced[0].key} + indep_ctrl = {c.key for c in transition.control} - { + transition.produced[0].key + } # There is one corner case where both controllers are also # the same as the produced variable, in which case. if not indep_ctrl: indep_ctrl = {transition.produced[0].key} - transition_dict['source'] = vmap[sorted(indep_ctrl)[0]] + try: + transition_dict["source"] = vmap[sorted(indep_ctrl, key=lambda x: str( + x))[0]] + except TypeError: + pass else: - transition_dict['source'] = vmap[transition.control[0].key] - transition_dict['target'] = \ - vmap[transition.consumed[0].key if - transition.consumed else transition.produced[0].key] - transition_dict['sign'] = (is_production(transition.template) or - is_replication(transition.template)) + transition_dict["source"] = vmap[transition.control[0].key] + transition_dict["target"] = vmap[ + transition.consumed[0].key + if transition.consumed + else transition.produced[0].key + ] + transition_dict["sign"] = is_production( + transition.template + ) or is_replication(transition.template) # Include rate law if transition.template.rate_law: @@ -161,64 +200,77 @@ def __init__(self, model: Model): # We just choose an arbitrary one deterministically rate_const = sorted(pnames)[0] if pnames else None - transition_dict['properties'] = { - 'name': tid, - 'rate_constant': rate_const, + transition_dict["properties"] = { + "name": tid, + "rate_constant": rate_const, } - self.rates.append({ - 'target': tid, - 'expression': str(rate_law), - 'expression_mathml': expression_to_mathml(rate_law) - }) + self.rates.append( + { + "target": tid, + "expression": str(rate_law), + "expression_mathml": expression_to_mathml(rate_law), + } + ) self.transitions.append(transition_dict) idx += 1 for var, rates in intrinsic_by_var.items(): rate_law = sum(rates) - self.rates.append({ - 'target': var, - 'expression': str(rate_law), - 'expression_mathml': expression_to_mathml(rate_law) - }) + self.rates.append( + { + "target": var, + "expression": str(rate_law), + "expression_mathml": expression_to_mathml(rate_law), + } + ) for key, param in model.parameters.items(): if param.placeholder: continue - param_dict = {'id': str(key)} + param_dict = {"id": str(key)} if param.value is not None: - param_dict['value'] = param.value + param_dict["value"] = param.value if not param.distribution: pass elif param.distribution.type is None: - logger.warning("can not add distribution without type: %s", param.distribution) + logger.warning( + "can not add distribution without type: %s", + param.distribution, + ) else: - param_dict['distribution'] = { - 'type': param.distribution.type, - 'parameters': param.distribution.parameters, + param_dict["distribution"] = { + "type": param.distribution.type, + "parameters": param.distribution.parameters, } self.parameters.append(param_dict) for key, observable in model.observables.items(): - display_name = observable.observable.display_name \ - if observable.observable.display_name \ + display_name = ( + observable.observable.display_name + if observable.observable.display_name else observable.observable.name + ) obs_data = { - 'id': observable.observable.name, - 'name': display_name, - 'expression': str(observable.observable.expression), - 'expression_mathml': expression_to_mathml( - observable.observable.expression.args[0]), + "id": observable.observable.name, + "name": display_name, + "expression": str(observable.observable.expression), + "expression_mathml": expression_to_mathml( + observable.observable.expression.args[0] + ), } self.observables.append(obs_data) if model.template_model.time: - self.time = {'id': model.template_model.time.name} + self.time = {"id": model.template_model.time.name} if model.template_model.time.units: - self.time['units'] = { - 'expression': str(model.template_model.time.units.expression), - 'expression_mathml': expression_to_mathml( - model.template_model.time.units.expression.args[0]), + self.time["units"] = { + "expression": str( + model.template_model.time.units.expression + ), + "expression_mathml": expression_to_mathml( + model.template_model.time.units.expression.args[0] + ), } else: self.time = None @@ -228,7 +280,7 @@ def to_json( self, name: str = None, description: str = None, - model_version: str = None + model_version: str = None, ): """Return a JSON dict structure of the Petri net model. @@ -251,31 +303,33 @@ def to_json( A JSON representation of the Petri net model. """ return { - 'header': { - 'name': name or self.model_name, - 'schema': SCHEMA_URL, - 'schema_name': 'regnet', - 'description': description or self.model_description, - 'model_version': model_version or '0.1', + "header": { + "name": name or self.model_name, + "schema": SCHEMA_URL, + "schema_name": "regnet", + "description": description or self.model_description, + "model_version": model_version or "0.1", }, - 'model': { - 'vertices': self.states, - 'edges': self.transitions, - 'parameters': self.parameters, + "model": { + "vertices": self.states, + "edges": self.transitions, + "parameters": self.parameters, }, - 'semantics': {'ode': { - 'rates': self.rates, - 'observables': self.observables, - 'time': self.time if self.time else {'id': 't'} - }}, - 'metadata': self.metadata, + "semantics": { + "ode": { + "rates": self.rates, + "observables": self.observables, + "time": self.time if self.time else {"id": "t"}, + } + }, + "metadata": self.metadata, } def to_pydantic( self, name: str = None, description: str = None, - model_version: str = None + model_version: str = None, ) -> "ModelSpecification": """Return a Pydantic model specification of the Petri net model. @@ -301,9 +355,9 @@ def to_pydantic( header=Header( name=name or self.model_name, schema=SCHEMA_URL, - schema_name='regnet', + schema_name="regnet", description=description or self.model_description, - model_version=model_version or '0.1', + model_version=model_version or "0.1", ), model=RegNetModel( vertices=[State.parse_obj(s) for s in self.states], @@ -313,8 +367,12 @@ def to_pydantic( semantics=Ode( ode=OdeSemantics( rates=[Rate.parse_obj(r) for r in self.rates], - observables=[Observable.parse_obj(o) for o in self.observables], - time=Time.parse_obj(self.time) if self.time else Time(id='t') + observables=[ + Observable.parse_obj(o) for o in self.observables + ], + time=Time.parse_obj(self.time) + if self.time + else Time(id="t"), ) ), metadata=self.metadata, @@ -341,7 +399,7 @@ def to_json_file( name: str = None, description: str = None, model_version: str = None, - **kwargs + **kwargs, ): """Write the Petri net model to a JSON file. @@ -362,9 +420,10 @@ def to_json_file( **kwargs : Keyword arguments to be passed to json.dump """ - js = self.to_json(name=name, description=description, - model_version=model_version) - with open(fname, 'w') as fh: + js = self.to_json( + name=name, description=description, model_version=model_version + ) + with open(fname, "w") as fh: json.dump(js, fh, **kwargs) @@ -426,7 +485,7 @@ class Parameter(BaseModel): @classmethod def from_dict(cls, d): d = deepcopy(d) - d['id'] = str(d['id']) + d["id"] = str(d["id"]) return cls.parse_obj(d) @@ -439,7 +498,7 @@ class RegNetModel(BaseModel): class Header(BaseModel): name: str schema_name: str - schema_url: str = Field(..., alias='schema') + schema_url: str = Field(..., alias="schema") description: str model_version: str @@ -456,9 +515,9 @@ class Ode(BaseModel): class ModelSpecification(BaseModel): """A Pydantic model specification of the model.""" + header: Header properties: Optional[Dict] model: RegNetModel semantics: Optional[Ode] metadata: Optional[Dict] - diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json new file mode 100644 index 000000000..f3f8939e9 --- /dev/null +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json @@ -0,0 +1,445 @@ +{ + "header": { + "name": "Chaouiya2013 - EGF and TNFalpha mediated signalling pathway", + "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/regnet_v0.2/regnet/regnet_schema.json", + "schema_name": "regnet", + "description": "Chaouiya2013 - EGF and TNFalpha mediated signalling pathway", + "model_version": "0.1" + }, + "model": { + "vertices": [ + { + "id": "nik", + "name": "nik", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ikk", + "name": "ikk", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "mkk4", + "name": "mkk4", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "p38", + "name": "p38", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ask1", + "name": "ask1", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "map3k1", + "name": "map3k1", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "mkk7", + "name": "mkk7", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "map3k7", + "name": "map3k7", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "jnk", + "name": "jnk", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "tnfr", + "name": "tnfr", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "traf2", + "name": "traf2", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "egfr", + "name": "egfr", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "pi3k", + "name": "pi3k", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ex", + "name": "ex", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ikb", + "name": "ikb", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "mek", + "name": "mek", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "erk", + "name": "erk", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ras", + "name": "ras", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "raf1", + "name": "raf1", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "tnfa", + "name": "tnfa", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "akt", + "name": "akt", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "egf", + "name": "egf", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "nfkb", + "name": "nfkb", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "cjun", + "name": "cjun", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ap1", + "name": "ap1", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "ph", + "name": "ph", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "sos", + "name": "sos", + "grounding": { + "identifiers": {}, + "context": {} + }, + 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], - "time": { - "id": "t" - } - } - }, - "metadata": {} -} \ No newline at end of file diff --git a/scripts/covid19_diseasemaps/stockflow_amr/Coagulation-pathway.json b/scripts/covid19_diseasemaps/stockflow_amr/Coagulation-pathway.json deleted file mode 100644 index df2b56603..000000000 --- a/scripts/covid19_diseasemaps/stockflow_amr/Coagulation-pathway.json +++ /dev/null @@ -1,2524 +0,0 @@ -{ - "header": { - "name": "SIR Model", - "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/stockflow_v0.1/stockflow/stockflow_schema.json", - "description": "SIR Model", - "schema_name": "stockflow", - "model_version": "0.1" - }, - "properties": {}, - "model": { - "flows": [ - { - "id": "0", - "name": "tr_csa11", - "upstream_stock": null, - "downstream_stock": "csa11" - }, - { - "id": "1", - "name": "tr_csa13", - "upstream_stock": null, - "downstream_stock": "csa13" - }, - { - "id": "2", - "name": "tr_csa12", - "upstream_stock": null, - "downstream_stock": "csa12" - }, 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00:00:00 2001 From: nanglo123 Date: Tue, 23 Apr 2024 20:35:25 -0400 Subject: [PATCH 36/44] Revert format changes to regnet file --- mira/modeling/amr/regnet.py | 251 ++++++++++++++---------------------- 1 file changed, 95 insertions(+), 156 deletions(-) diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index 8482a687e..63cc86229 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -2,12 +2,8 @@ at https://github.com/DARPA-ASKEM/Model-Representations/tree/main/regnet. """ -__all__ = [ - "AMRRegNetModel", - "ModelSpecification", - "template_model_to_regnet_json", -] - +__all__ = ["AMRRegNetModel", "ModelSpecification", + "template_model_to_regnet_json"] import json import logging @@ -25,12 +21,10 @@ logger = logging.getLogger(__name__) -SCHEMA_VERSION = "0.2" -SCHEMA_URL = ( - "https://raw.githubusercontent.com/DARPA-ASKEM/" - "Model-Representations/regnet_v%s/regnet/" - "regnet_schema.json" -) % SCHEMA_VERSION +SCHEMA_VERSION = '0.2' +SCHEMA_URL = ('https://raw.githubusercontent.com/DARPA-ASKEM/' + 'Model-Representations/regnet_v%s/regnet/' + 'regnet_schema.json') % SCHEMA_VERSION class AMRRegNetModel: @@ -47,18 +41,12 @@ def __init__(self, model: Model): self.states = [] self.transitions = [] self.parameters = [] - self.model_name = ( - model.template_model.annotations.name - if model.template_model.annotations - and model.template_model.annotations.name - else "Model" - ) - self.model_description = ( - model.template_model.annotations.description - if model.template_model.annotations - and model.template_model.annotations.description - else self.model_name - ) + self.model_name = model.template_model.annotations.name if \ + model.template_model.annotations and \ + model.template_model.annotations.name else "Model" + self.model_description = model.template_model.annotations.description \ + if model.template_model.annotations and \ + model.template_model.annotations.description else self.model_name self.rates = [] self.observables = [] @@ -73,27 +61,25 @@ def __init__(self, model: Model): # on the key otherwise vmap[key] = name = var.concept.name or str(key) state_data = { - "id": name, - "name": name, - "grounding": { - "identifiers": { - k: v - for k, v in var.concept.identifiers.items() - if k != "biomodels.species" - }, - "context": var.concept.context, + 'id': name, + 'name': name, + 'grounding': { + 'identifiers': {k: v for k, v in + var.concept.identifiers.items() + if k != 'biomodels.species'}, + 'context': var.concept.context, }, } - initial = var.data.get("expression") + initial = var.data.get('expression') if initial is not None: # Here, initial is a SympyExprStr, and if its # value is a float, we export it as a float, # otherwise we export it as a string try: initial_float = float(initial.args[0]) - state_data["initial"] = initial_float + state_data['initial'] = initial_float except TypeError: - state_data["initial"] = str(initial) + state_data['initial'] = str(initial) self.states.append(state_data) self._states_by_id[name] = state_data @@ -115,16 +101,8 @@ def __init__(self, model: Model): # Natural degradation corresponds to an inherent negative # sign on the state so we have special handling for it - if ( - natdeg - or natrep - or ( - contprod - and ( - transition.control[0].key == transition.produced[0].key - ) - ) - ): + if natdeg or natrep or (contprod and (transition.control[0].key + == transition.produced[0].key)): if natdeg: var = vmap[transition.consumed[0].key] sign = False @@ -141,9 +119,9 @@ def __init__(self, model: Model): # We just choose an arbitrary one deterministically rate_const = sorted(pnames)[0] if pnames else None if state_for_var: - state_for_var["rate_constant"] = rate_const + state_for_var['rate_constant'] = rate_const if state_for_var: - state_for_var["sign"] = sign + state_for_var['sign'] = sign if transition.template.rate_law: rate_law = transition.template.rate_law.args[0] @@ -155,43 +133,25 @@ def __init__(self, model: Model): # - ControlledReplication / GroupedControlledProduction # - ControlledDegradation else: - # group controlled production, - # signs for each of the parent - # in a for loop, loop thorugh the parents and create a transition for each parent - - # single upstream controller and and downstream target in amr - # if isinstance( - # transition.template, GroupedControlledDegradation - # ): - # continue - # pass tid = f"t{idx + 1}" - transition_dict = {"id": tid} + transition_dict = {'id': tid} # If we have multiple controls then the thing that replicates # is both a control and a produced variable. if len(transition.control) > 1: - indep_ctrl = {c.key for c in transition.control} - { - transition.produced[0].key - } + indep_ctrl = {c.key for c in transition.control} - \ + {transition.produced[0].key} # There is one corner case where both controllers are also # the same as the produced variable, in which case. if not indep_ctrl: indep_ctrl = {transition.produced[0].key} - try: - transition_dict["source"] = vmap[sorted(indep_ctrl, key=lambda x: str( - x))[0]] - except TypeError: - pass + transition_dict['source'] = vmap[sorted(indep_ctrl, key=lambda x: str(x))[0]] else: - transition_dict["source"] = vmap[transition.control[0].key] - transition_dict["target"] = vmap[ - transition.consumed[0].key - if transition.consumed - else transition.produced[0].key - ] - transition_dict["sign"] = is_production( - transition.template - ) or is_replication(transition.template) + transition_dict['source'] = vmap[transition.control[0].key] + transition_dict['target'] = \ + vmap[transition.consumed[0].key if + transition.consumed else transition.produced[0].key] + transition_dict['sign'] = (is_production(transition.template) or + is_replication(transition.template)) # Include rate law if transition.template.rate_law: @@ -200,77 +160,64 @@ def __init__(self, model: Model): # We just choose an arbitrary one deterministically rate_const = sorted(pnames)[0] if pnames else None - transition_dict["properties"] = { - "name": tid, - "rate_constant": rate_const, + transition_dict['properties'] = { + 'name': tid, + 'rate_constant': rate_const, } - self.rates.append( - { - "target": tid, - "expression": str(rate_law), - "expression_mathml": expression_to_mathml(rate_law), - } - ) + self.rates.append({ + 'target': tid, + 'expression': str(rate_law), + 'expression_mathml': expression_to_mathml(rate_law) + }) self.transitions.append(transition_dict) idx += 1 for var, rates in intrinsic_by_var.items(): rate_law = sum(rates) - self.rates.append( - { - "target": var, - "expression": str(rate_law), - "expression_mathml": expression_to_mathml(rate_law), - } - ) + self.rates.append({ + 'target': var, + 'expression': str(rate_law), + 'expression_mathml': expression_to_mathml(rate_law) + }) for key, param in model.parameters.items(): if param.placeholder: continue - param_dict = {"id": str(key)} + param_dict = {'id': str(key)} if param.value is not None: - param_dict["value"] = param.value + param_dict['value'] = param.value if not param.distribution: pass elif param.distribution.type is None: - logger.warning( - "can not add distribution without type: %s", - param.distribution, - ) + logger.warning("can not add distribution without type: %s", param.distribution) else: - param_dict["distribution"] = { - "type": param.distribution.type, - "parameters": param.distribution.parameters, + param_dict['distribution'] = { + 'type': param.distribution.type, + 'parameters': param.distribution.parameters, } self.parameters.append(param_dict) for key, observable in model.observables.items(): - display_name = ( - observable.observable.display_name - if observable.observable.display_name + display_name = observable.observable.display_name \ + if observable.observable.display_name \ else observable.observable.name - ) obs_data = { - "id": observable.observable.name, - "name": display_name, - "expression": str(observable.observable.expression), - "expression_mathml": expression_to_mathml( - observable.observable.expression.args[0] - ), + 'id': observable.observable.name, + 'name': display_name, + 'expression': str(observable.observable.expression), + 'expression_mathml': expression_to_mathml( + observable.observable.expression.args[0]), } self.observables.append(obs_data) if model.template_model.time: - self.time = {"id": model.template_model.time.name} + self.time = {'id': model.template_model.time.name} if model.template_model.time.units: - self.time["units"] = { - "expression": str( - model.template_model.time.units.expression - ), - "expression_mathml": expression_to_mathml( - model.template_model.time.units.expression.args[0] - ), + self.time['units'] = { + 'expression': str(model.template_model.time.units.expression), + 'expression_mathml': expression_to_mathml( + model.template_model.time.units.expression.args[0]), } else: self.time = None @@ -280,7 +227,7 @@ def to_json( self, name: str = None, description: str = None, - model_version: str = None, + model_version: str = None ): """Return a JSON dict structure of the Petri net model. @@ -303,33 +250,31 @@ def to_json( A JSON representation of the Petri net model. """ return { - "header": { - "name": name or self.model_name, - "schema": SCHEMA_URL, - "schema_name": "regnet", - "description": description or self.model_description, - "model_version": model_version or "0.1", - }, - "model": { - "vertices": self.states, - "edges": self.transitions, - "parameters": self.parameters, + 'header': { + 'name': name or self.model_name, + 'schema': SCHEMA_URL, + 'schema_name': 'regnet', + 'description': description or self.model_description, + 'model_version': model_version or '0.1', }, - "semantics": { - "ode": { - "rates": self.rates, - "observables": self.observables, - "time": self.time if self.time else {"id": "t"}, - } + 'model': { + 'vertices': self.states, + 'edges': self.transitions, + 'parameters': self.parameters, }, - "metadata": self.metadata, + 'semantics': {'ode': { + 'rates': self.rates, + 'observables': self.observables, + 'time': self.time if self.time else {'id': 't'} + }}, + 'metadata': self.metadata, } def to_pydantic( self, name: str = None, description: str = None, - model_version: str = None, + model_version: str = None ) -> "ModelSpecification": """Return a Pydantic model specification of the Petri net model. @@ -355,9 +300,9 @@ def to_pydantic( header=Header( name=name or self.model_name, schema=SCHEMA_URL, - schema_name="regnet", + schema_name='regnet', description=description or self.model_description, - model_version=model_version or "0.1", + model_version=model_version or '0.1', ), model=RegNetModel( vertices=[State.parse_obj(s) for s in self.states], @@ -367,12 +312,8 @@ def to_pydantic( semantics=Ode( ode=OdeSemantics( rates=[Rate.parse_obj(r) for r in self.rates], - observables=[ - Observable.parse_obj(o) for o in self.observables - ], - time=Time.parse_obj(self.time) - if self.time - else Time(id="t"), + observables=[Observable.parse_obj(o) for o in self.observables], + time=Time.parse_obj(self.time) if self.time else Time(id='t') ) ), metadata=self.metadata, @@ -399,7 +340,7 @@ def to_json_file( name: str = None, description: str = None, model_version: str = None, - **kwargs, + **kwargs ): """Write the Petri net model to a JSON file. @@ -420,10 +361,9 @@ def to_json_file( **kwargs : Keyword arguments to be passed to json.dump """ - js = self.to_json( - name=name, description=description, model_version=model_version - ) - with open(fname, "w") as fh: + js = self.to_json(name=name, description=description, + model_version=model_version) + with open(fname, 'w') as fh: json.dump(js, fh, **kwargs) @@ -485,7 +425,7 @@ class Parameter(BaseModel): @classmethod def from_dict(cls, d): d = deepcopy(d) - d["id"] = str(d["id"]) + d['id'] = str(d['id']) return cls.parse_obj(d) @@ -498,7 +438,7 @@ class RegNetModel(BaseModel): class Header(BaseModel): name: str schema_name: str - schema_url: str = Field(..., alias="schema") + schema_url: str = Field(..., alias='schema') description: str model_version: str @@ -515,7 +455,6 @@ class Ode(BaseModel): class ModelSpecification(BaseModel): """A Pydantic model specification of the model.""" - header: Header properties: Optional[Dict] model: RegNetModel From 9314a41679d1248e85c4e8007aec05ab22558626 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Tue, 23 Apr 2024 23:39:21 -0400 Subject: [PATCH 37/44] Add support for GroupedControlledDegradation templates when exporting to regnet, add regnet amrs for sbml qual documents from the covid-19 diseasemap --- mira/modeling/amr/regnet.py | 29 +- .../process_covid19_diseasemaps_sbml.py | 44 +- .../regnet_amr_sbml/Apoptosis.json | 499 +++ .../regnet_amr_sbml/Coagulation-pathway.json | 2023 ++++++++++ .../regnet_amr_sbml/ER_Stress.json | 2609 +++++++++++++ .../regnet_amr_sbml/ETC.json | 1214 ++++++ .../regnet_amr_sbml/E_protein.json | 453 +++ .../regnet_amr_sbml/HMOX1_Pathway.json | 2307 ++++++++++++ .../regnet_amr_sbml/IFN-lambda.json | 614 ++++ .../regnet_amr_sbml/Interferon1.json | 1671 +++++++++ .../regnet_amr_sbml/JNK_pathway.json | 265 ++ .../regnet_amr_sbml/Kynurenine_pathway.json | 2119 +++++++++++ .../regnet_amr_sbml/NLRP3_Activation.json | 912 +++++ .../regnet_amr_sbml/Nsp14.json | 2267 ++++++++++++ .../regnet_amr_sbml/Nsp4_Nsp6.json | 974 +++++ .../regnet_amr_sbml/Nsp9_protein.json | 3248 +++++++++++++++++ .../regnet_amr_sbml/Orf10_Cul2_pathway.json | 882 +++++ .../regnet_amr_sbml/Orf3a.json | 623 ++++ .../regnet_amr_sbml/PAMP_signaling.json | 1044 ++++++ .../Pyrimidine_deprivation.json | 1334 +++++++ .../RTC-and-transcription.json | 518 +++ .../regnet_amr_sbml/Renin_angiotensin.json | 1115 ++++++ .../regnet_amr_sbml/TGFB_pathway.json | 259 ++ .../Virus_replication_cycle.json | 2929 +++++++++++++++ 24 files changed, 29933 insertions(+), 19 deletions(-) create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json create mode 100644 scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index 63cc86229..04f9b4f97 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -138,13 +138,28 @@ def __init__(self, model: Model): # If we have multiple controls then the thing that replicates # is both a control and a produced variable. if len(transition.control) > 1: - indep_ctrl = {c.key for c in transition.control} - \ - {transition.produced[0].key} - # There is one corner case where both controllers are also - # the same as the produced variable, in which case. - if not indep_ctrl: - indep_ctrl = {transition.produced[0].key} - transition_dict['source'] = vmap[sorted(indep_ctrl, key=lambda x: str(x))[0]] + if isinstance(transition.template, GroupedControlledDegradation): + indep_ctrl = {c.key for c in transition.control} - { + transition.consumed[0].key + } + if not indep_ctrl: + indep_ctrl = {transition.consumed[0].key} + + transition_dict["source"] = vmap[ + sorted(indep_ctrl, key=lambda x: str(x))[0] + ] + + else: + indep_ctrl = {c.key for c in transition.control} - { + transition.produced[0].key + } + # There is one corner case where both controllers are also + # the same as the produced variable, in which case. + if not indep_ctrl: + indep_ctrl = {transition.produced[0].key} + transition_dict["source"] = vmap[ + sorted(indep_ctrl, key=lambda x: str(x))[0] + ] else: transition_dict['source'] = vmap[transition.control[0].key] transition_dict['target'] = \ diff --git a/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py index e09bd9fc4..28edbf528 100644 --- a/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py +++ b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py @@ -2,27 +2,47 @@ import tqdm import requests -from mira.modeling.amr.stockflow import template_model_to_stockflow_json from mira.sources.sbml import template_model_from_sbml_qual_string +from mira.modeling.amr.regnet import template_model_to_regnet_json -models = ['Apoptosis', 'Coagulation-pathway', 'ER_Stress', 'ETC', 'E_protein', - 'HMOX1_Pathway', 'IFN-lambda', 'Interferon1', 'JNK_pathway', - 'Kynurenine_pathway', 'NLRP3_Activation', 'Nsp14', 'Nsp4_Nsp6', - 'Nsp9_protein', 'Orf10_Cul2_pathway', 'Orf3a', 'PAMP_signaling', - 'Pyrimidine_deprivation', 'RTC-and-transcription', - 'Renin_angiotensin', 'TGFB_pathway', 'Virus_replication_cycle'] +models = [ + "Apoptosis", + "Coagulation-pathway", + "ER_Stress", + "ETC", + "E_protein", + "HMOX1_Pathway", + "IFN-lambda", + "Interferon1", + "JNK_pathway", + "Kynurenine_pathway", + "NLRP3_Activation", + "Nsp14", + "Nsp4_Nsp6", + "Nsp9_protein", + "Orf10_Cul2_pathway", + "Orf3a", + "PAMP_signaling", + "Pyrimidine_deprivation", + "RTC-and-transcription", + "Renin_angiotensin", + "TGFB_pathway", + "Virus_replication_cycle", +] -SBML_URL_BASE = ('https://git-r3lab.uni.lu/covid/models/-/raw/master/' - 'Executable%20Modules/SBML_qual_build/sbml') +SBML_URL_BASE = ( + "https://git-r3lab.uni.lu/covid/models/-/raw/master/" + "Executable%20Modules/SBML_qual_build/sbml" +) if __name__ == "__main__": for model in tqdm.tqdm(models): - url = f'{SBML_URL_BASE}/{model}_stable.sbml' + url = f"{SBML_URL_BASE}/{model}_stable.sbml" model_text = requests.get(url).text tm = template_model_from_sbml_qual_string(model_text) - regnet = template_model_to_stockflow_json(tm) - with open(f'stockflow_amr/{model}.json', 'w') as fh: + regnet = template_model_to_regnet_json(tm) + with open(f"regnet_amr_sbml/{model}.json", "w") as fh: json.dump(regnet, fh, indent=1) diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json new file mode 100644 index 000000000..37a38b619 --- /dev/null +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json @@ -0,0 +1,499 @@ +{ + "header": { + "name": "Model", + "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/regnet_v0.2/regnet/regnet_schema.json", + "schema_name": "regnet", + "description": "Model", + "model_version": "0.1" + }, + "model": { + "vertices": [ + { + "id": "Orf7a", + "name": "Orf7a", + "grounding": { + "identifiers": { + "ncbigene": "1489674" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "E", + "name": "E", + "grounding": { + "identifiers": { + "pubmed": "32785274" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "BAD", + "name": "BAD", + "grounding": { + "identifiers": { + "uniprot": "Q92934" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "FASLG", + "name": "FASLG", + "grounding": { + "identifiers": { + "uniprot": "P48023" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "FAS/FASL_complex", + "name": "FAS/FASL_complex", + "grounding": { + "identifiers": { + "uniprot": "P25445" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "TNF", + "name": "TNF", + "grounding": { + "identifiers": { + "uniprot": "P01375" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "TNF/TNFRSF1A_complex", + "name": "TNF/TNFRSF1A_complex", + "grounding": { + "identifiers": { + "uniprot": "P01375" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "BCL2/MCL1/BCL2L1_complex", + "name": "BCL2/MCL1/BCL2L1_complex", + "grounding": { + "identifiers": { + "uniprot": "P10415" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "FADD", + "name": "FADD", + "grounding": { + "identifiers": { + "uniprot": "Q13158" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "TRADD", + "name": "TRADD", + "grounding": { + "identifiers": { + "uniprot": "Q15628" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "TRADD/FADD_complex", + "name": "TRADD/FADD_complex", + "grounding": { + "identifiers": { + "uniprot": "Q13158" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CYCS", + "name": "CYCS", + "grounding": { + "identifiers": { + "uniprot": "P99999" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "APAF1", + "name": "APAF1", + "grounding": { + "identifiers": { + "uniprot": "O14727" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CASP9_cell", + "name": "CASP9_cell", + "grounding": { + "identifiers": { + "uniprot": "P55211" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "AKT1", + "name": "AKT1", + "grounding": { + "identifiers": { + "uniprot": "P31749" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Apoptosome_complex", + "name": "Apoptosome_complex", + "grounding": { + "identifiers": { + "uniprot": "O14727" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "M", + "name": "M", + "grounding": { + "identifiers": { + "pubmed": "16845612" + }, + "context": { + "property": "ncbiprotein:APO40582" + } + }, + "initial": 3.0 + }, + { + "id": "BAD/BBC3/BCL2L11_complex", + "name": "BAD/BBC3/BCL2L11_complex", + "grounding": { + "identifiers": { + "uniprot": "O43521" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "BID", + "name": "BID", + "grounding": { + "identifiers": { + "uniprot": "P55957" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "BAX", + "name": "BAX", + "grounding": { + "identifiers": { + "uniprot": "Q07812" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Orf3a", + "name": "Orf3a", + "grounding": { + "identifiers": { + "pubmed": "32555321" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "MAPK14", + "name": "MAPK14", + "grounding": { + "identifiers": { + "uniprot": "Q16539" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CASP9_cell_active", + "name": "CASP9_cell_active", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CASP8", + "name": "CASP8", + "grounding": { + "identifiers": { + "uniprot": "Q14790" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CASP7", + "name": "CASP7", + "grounding": { + "identifiers": { + "uniprot": "P55210" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CASP3", + "name": "CASP3", + "grounding": { + "identifiers": { + "uniprot": "P42574" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Orf6", + "name": "Orf6", + "grounding": { + "identifiers": { + "ncbigene": "1489673" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "S", + "name": "S", + "grounding": { + "identifiers": { + "pubmed": "32075877" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Orf8a", + "name": "Orf8a", + "grounding": { + "identifiers": { + "ncbigene": "1489676" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "N", + "name": "N", + "grounding": { + "identifiers": { + "pubmed": "16112641" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Orf3b", + "name": "Orf3b", + "grounding": { + "identifiers": { + "ncbigene": "1489670" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Orf9b", + "name": "Orf9b", + "grounding": { + "identifiers": { + "ncbigene": "1489679" + }, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Apoptosis_phenotype", + "name": "Apoptosis_phenotype", + "grounding": { + "identifiers": { + "pubmed": "31226023" + }, + "context": {} + }, + "initial": 3.0 + } + ], + "edges": [ + { + "id": "t1", + "source": "BAD", + "target": "Orf7a", + "sign": false + }, + { + "id": "t2", + "source": "FASLG", + "target": "FAS/FASL_complex", + "sign": true + }, + { + "id": "t3", + "source": "TNF", + "target": "TNF/TNFRSF1A_complex", + "sign": true + }, + { + "id": "t4", + "source": "BCL2/MCL1/BCL2L1_complex", + "target": "BCL2/MCL1/BCL2L1_complex", + "sign": false + }, + { + "id": "t5", + "source": "FADD", + "target": "TRADD/FADD_complex", + "sign": true + }, + { + "id": "t6", + "source": "AKT1", + "target": "Apoptosome_complex", + "sign": true + }, + { + "id": "t7", + "source": "M", + "target": "M", + "sign": false + }, + { + "id": "t8", + "source": "FAS/FASL_complex", + "target": "FADD", + "sign": true + }, + { + "id": "t9", + "source": "AKT1", + "target": "AKT1", + "sign": false + }, + { + "id": "t10", + "source": "BAD/BBC3/BCL2L11_complex", + "target": "BAX", + "sign": true + }, + { + "id": "t11", + "source": "Orf3a", + "target": "MAPK14", + "sign": true + }, + { + "id": "t12", + "source": "BAX", + "target": "CYCS", + "sign": true + }, + { + "id": "t13", + "source": "CASP8", + "target": "CASP7", + "sign": true + }, + { + "id": "t14", + "source": "AKT1", + "target": "CASP9_cell_active", + "sign": true + }, + { + 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"target": "viral entry into host cell_phenotype", + "sign": false + }, + { + "id": "t107", + "source": "ACE2", + "target": "viral RNA genome replication_phenotype", + "sign": true + } + ], + "parameters": [] + }, + "semantics": { + "ode": { + "rates": [], + "observables": [], + "time": { + "id": "t" + } + } + }, + "metadata": { + "annotations": {} + } +} \ No newline at end of file diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json new file mode 100644 index 000000000..031fe12c1 --- /dev/null +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json @@ -0,0 +1,1214 @@ +{ + "header": { + "name": "Model", + "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/regnet_v0.2/regnet/regnet_schema.json", + "schema_name": "regnet", + "description": "Model", + "model_version": "0.1" + }, + "model": { + "vertices": [ + { + "id": "Nsp4_mitochondrion", + "name": "Nsp4_mitochondrion", + "grounding": { + 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"source": "CA12", + "target": "HFTcomp_complex", + "sign": true + }, + { + "id": "t64", + "source": "Benzthiazide_drug", + "target": "BZcomp_complex", + "sign": true + }, + { + "id": "t65", + "source": "AP2A2", + "target": "AP2A2comp_complex", + "sign": true + }, + { + "id": "t66", + "source": "Fibrillin_complex_human host", + "target": "Fibrillin_complex_human host", + "sign": true + }, + { + "id": "t67", + "source": "ELN", + "target": "RofecoxibComp_complex", + "sign": true + }, + { + "id": "t68", + "source": "Nsp8", + "target": "NspComp_complex", + "sign": true + }, + { + "id": "t69", + "source": "ENV", + "target": "NECENVComp_complex", + "sign": true + }, + { + "id": "t70", + "source": "CYB5R3", + "target": "NADHcomp_complex", + "sign": true + }, + { + "id": "t71", + "source": "CYB5R3", + "target": "CYB5R3comp_complex", + "sign": true + }, + { + "id": "t72", + "source": "CYB5R3", + "target": "FADcomp_complex", + "sign": true + }, + { + "id": "t73", + "source": "COMT", + "target": 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/dev/null +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json @@ -0,0 +1,882 @@ +{ + "header": { + "name": "Model", + "schema": "https://raw.githubusercontent.com/DARPA-ASKEM/Model-Representations/regnet_v0.2/regnet/regnet_schema.json", + "schema_name": "regnet", + "description": "Model", + "model_version": "0.1" + }, + "model": { + "vertices": [ + { + "id": "Cul2 ubiquitin ligase:substrate_complex_cell", + "name": "Cul2 ubiquitin ligase:substrate_complex_cell", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Cul2 ubiquitin ligase:Orf10_complex", + "name": "Cul2 ubiquitin ligase:Orf10_complex", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "Cul2 ubiquitin ligase:N8_complex", + "name": "Cul2 ubiquitin ligase:N8_complex", + "grounding": { + "identifiers": {}, + "context": {} + }, + "initial": 3.0 + }, + { + "id": "CSN5_complex", + "name": "CSN5_complex", + "grounding": { + 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}, + { + "id": "t9", + "source": "(+)ss gRNA_rna_epithelial_space_cell", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t10", + "source": "(+)ss gRNA_rna_epithelial_space_cell", + "target": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t11", + "source": "Nsp4:IDE_complex_epithelial_space_cell", + "target": "Nsp4_IDE_complex", + "sign": true + }, + { + "id": "t12", + "source": "IDE_epithelial_space_cell", + "target": "Nsp4:IDE_complex_epithelial_space_cell", + "sign": true + }, + { + "id": "t13", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "SIGMAR1: drug complex_complex", + "sign": true + }, + { + "id": "t14", + "source": "NUP210_endoplasmic reticulum", + "target": "Nsp4:NUP210_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t15", + "source": "V-ATPase_complex_endoplasmic reticulum", + "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t16", + "source": "ATP6AP1", + "target": "V-ATPase_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t17", + "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_nucleus", + "sign": true + }, + { + "id": "t18", + "source": "Nsp4:NUP210_complex_endoplasmic reticulum", + "target": "Nsp4:NUP210_complex_nucleus", + "sign": true + }, + { + "id": "t19", + "source": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "target": "V-ATPase:Nsp6_complex_endosome", + "sign": true + }, + { + "id": "t20", + "source": "V-ATPase_complex_endoplasmic reticulum", + "target": "V-ATPase_complex_endosome", + "sign": true + }, + { + "id": "t21", + "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_epithelial_space_cell", + "sign": true + }, + { + "id": "t22", + "source": "NUP210_endoplasmic reticulum", + "target": "NUP210:Selinexor_complex", + "sign": true + }, + { + "id": "t23", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t24", + "source": "ATP6AP1", + "target": "ATP6AP1:Bafilomycin_space_A1_complex", + "sign": true + }, + { + "id": "t25", + "source": "ALG11_endoplasmic reticulum", + "target": "Nsp4_ALG11_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t26", + "source": "ARL8B", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t27", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t28", + "source": "ds_space_gRNA_rna", + "target": "(-)ss_space_gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t29", + "source": "Nsp1", + "target": "Nsp1", + "sign": false + }, + { + "id": "t30", + "source": "S_rough_space_endoplasmic_space_reticulum", + "target": "S_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t31", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t32", + "source": "E_space_ds_space_sgmRNA_rna", + "target": "E_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t33", + "source": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf9b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t34", + "source": "M_space_ds_space_sgmRNA_rna", + "target": "M_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t35", + "source": "Orf9b_rough_space_endoplasmic_space_reticulum", + "target": "Orf9b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t36", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t37", + "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "target": "pp1ab_space_nsp6-16", + "sign": true + }, + { + "id": "t38", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "E_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t39", + "source": "Orf14_rough_space_endoplasmic_space_reticulum", + "target": "Orf14_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t40", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t41", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp13", + "sign": true + }, + { + "id": "t42", + "source": "(+)ss_space_gRNA_rna", + "target": "pp1a", + "sign": true + }, + { + "id": "t43", + "source": "pp1a", + "target": "Nsp1", + "sign": true + }, + { + "id": "t44", + "source": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf14_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t45", + "source": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "E_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t46", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t47", + "source": "Nsp15", + "target": "Nsp15", + "sign": false + }, + { + "id": "t48", + "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "target": "Nsp5_epithelial_space_cell", + "sign": true + }, + { + "id": "t49", + "source": "Nsp3-4", + "target": "Nsp3-4_glycosylated", + "sign": true + }, + { + "id": "t50", + "source": "Nsp3-4_glycosylated", + "target": "Nsp3", + "sign": true + }, + { + "id": "t51", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp7", + "sign": true + }, + { + "id": "t52", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp16", + "sign": true + }, + { + "id": "t53", + "source": "Orf8_space_ds_space_sgmRNA_rna", + "target": "Orf8_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t54", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp12", + "sign": true + }, + { + "id": "t55", + "source": "pp1a", + "target": "Nsp2", + "sign": true + }, + { + "id": "t56", + "source": "Nucleocapsid_complex_epithelial_space_cell", + "target": "(+)ss_space_gRNA_rna", + "sign": true + }, + { + "id": "t57", + "source": "Orf6_space_ds_space_sgmRNA_rna", + "target": "Orf6_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t58", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "ds_space_gRNA_rna", + "sign": true + }, + { + "id": "t59", + "source": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "M_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t60", + "source": "Camostat_space_mesylate_drug", + "target": "S2_epithelial_space_cell", + "sign": true + }, + { + "id": "t61", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp14", + "sign": true + }, + { + "id": "t62", + "source": "Camostat_space_mesylate_drug", + "target": "ACE2_epithelial_space_cell", + "sign": true + }, + { + "id": "t63", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp10", + "sign": true + }, + { + "id": "t64", + "source": "E_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t65", + "source": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf7b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t66", + "source": "N_space_space_(-)ss_space_sgmRNA_rna", + "target": "N_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t67", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp9", + "sign": true + }, + { + "id": "t68", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "N_space_space_(-)ss_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t69", + "source": "E_rough_space_endoplasmic_space_reticulum", + "target": "E_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t70", + "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", + "target": "Nsp3-4", + "sign": true + }, + { + "id": "t71", + "source": "Orf7b_rough_space_endoplasmic_space_reticulum", + "target": "Orf7b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t72", + "source": "(+)ss_space_gRNA_rna", + "target": "pp1ab", + "sign": true + }, + { + "id": "t73", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf3a_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t74", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf9b_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t75", + "source": "E_SARS-CoV-2_space_virion", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t76", + "source": "N_space_ds_space_sgmRNA_rna", + "target": "N_space_(-)ss_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t77", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf6_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t78", + "source": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf6_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t79", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf7a_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t80", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp8", + "sign": true + }, + { + "id": "t81", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t82", + "source": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf8_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t83", + "source": "Orf7a_space_ds_space_sgmRNA_rna", + "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t84", + "source": "M_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "M_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t85", + "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", + "target": "N_epithelial_space_cell", + "sign": true + }, + { + "id": "t86", + "source": "S_space_ds_space_sgmRNA_rna", + "target": "S_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t87", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t88", + "source": "Orf7a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "Orf7a_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t89", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf14_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t90", + "source": "Camostat_space_mesylate_drug", + "target": "ACE2_default_compartment", + "sign": true + }, + { + "id": "t91", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t92", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "S_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t93", + "source": "E_SARS-CoV-2_space_virion", + "target": "E_endosome", + "sign": true + }, + { + "id": "t94", + "source": "S_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "S_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t95", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t96", + "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", + "target": "S2_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t97", + "source": "E_SARS-CoV-2_space_virion", + "target": "M_endosome", + "sign": true + }, + { + "id": "t98", + "source": "Orf7b_space_ds_space_sgmRNA_rna", + "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t99", + "source": "Orf14_space_ds_space_sgmRNA_rna", + "target": "Orf14_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t100", + "source": "pp1ab", + "target": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "sign": true + }, + { + "id": "t101", + "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", + "target": "pp1a_space_Nsp6-11", + "sign": true + }, + { + "id": "t102", + "source": "Camostat_space_mesylate_drug", + "target": "S1_default_compartment", + "sign": true + }, + { + "id": "t103", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t104", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t105", + "source": "Orf8_rough_space_endoplasmic_space_reticulum", + "target": "Orf8_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t106", + "source": "Orf9b_space_ds_space_sgmRNA_rna", + "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t107", + "source": "E_SARS-CoV-2_space_virion", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t108", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf7b_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t109", + "source": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf7a_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t110", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp11", + "sign": true + }, + { + "id": "t111", + "source": "E_SARS-CoV-2_space_virion", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t112", + "source": "E_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "E_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t113", + "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", + "target": "S1_endosome", + "sign": true + }, + { + "id": "t114", + "source": "Orf6_rough_space_endoplasmic_space_reticulum", + "target": "Orf6_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t115", + "source": "Orf3a_space_ds_space_sgmRNA_rna", + "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t116", + "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", + "target": "Nsp5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t117", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t118", + "source": "Orf7a_rough_space_endoplasmic_space_reticulum", + "target": "Orf7a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t119", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "M_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t120", + "source": "Orf3a_rough_space_endoplasmic_space_reticulum", + "target": "Orf3a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t121", + "source": "Nsp3-4_glycosylated", + "target": "Nsp4_endoplasmic reticulum", + "sign": true + }, + { + "id": "t122", + "source": "pp1a", + "target": "pp1a_space_Nsp3-11_endoplasmic reticulum", + "sign": true + }, + { + "id": "t123", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf8_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t124", + "source": "(+)ss_space_gRNA_rna", + "target": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t125", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "S_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t126", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp15", + "sign": true + }, + { + "id": "t127", + "source": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf3a_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t128", + "source": "M_rough_space_endoplasmic_space_reticulum", + "target": "M_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t129", + "source": "IDE_epithelial_space_cell", + "target": "IDE_default_compartment", + "sign": true + }, + { + "id": "t130", + "source": "IDE_epithelial_space_cell", + "target": "IDE_epithelial_space_cell", + "sign": true + }, + { + "id": "t131", + "source": "V-type_space_proton_space_ATPase_complex", + "target": "H+_ion", + "sign": true + }, + { + "id": "t132", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "SIGMAR1_epithelial_space_cell", + "sign": true + }, + { + "id": "t133", + "source": "NUP210_endoplasmic reticulum", + "target": "NUP210_nucleus", + "sign": true + }, + { + "id": "t134", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "SIGMAR1_nucleus", + "sign": true + }, + { + "id": "t135", + "source": "Nsp3", + "target": "double membrane vesicle viral factory assembly_phenotype", + "sign": true + }, + { + "id": "t136", + "source": "bafilomycin_space_A1_drug", + "target": "SARS-CoV2 candidate drugs_complex", + "sign": false + }, + { + "id": "t137", + "source": "ds_space_gRNA_rna", + "target": "(+)ss gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t138", + "source": "N_space_ds_space_sgmRNA_rna", + "target": "N (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t139", + "source": "M_space_ds_space_sgmRNA_rna", + "target": "M (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t140", + "source": "S_space_ds_space_sgmRNA_rna", + "target": "S (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t141", + "source": "E_space_ds_space_sgmRNA_rna", + "target": "E (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t142", + "source": "Orf6_space_ds_space_sgmRNA_rna", + "target": "Orf6 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t143", + "source": "Orf7a_space_ds_space_sgmRNA_rna", + "target": "Orf7a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t144", + "source": "Orf3a_space_ds_space_sgmRNA_rna", + "target": "Orf3a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t145", + "source": "Orf8_space_ds_space_sgmRNA_rna", + "target": "Orf8 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t146", + "source": "DMV molecular pore_complex", + "target": "Orf7a (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t147", + "source": "DMV molecular pore_complex", + "target": "S (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t148", + "source": "DMV molecular pore_complex", + "target": "Orf6 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t149", + "source": "DMV molecular pore_complex", + "target": "E (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t150", + "source": "DMV molecular pore_complex", + "target": "Orf3a (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t151", + "source": "DMV molecular pore_complex", + "target": "M (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t152", + "source": "DMV molecular pore_complex", + "target": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t153", + "source": "DMV molecular pore_complex", + "target": "N (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t154", + "source": "(+)ss gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "(+)ss gRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t155", + "source": "DMV molecular pore_complex", + "target": "Orf9b (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t156", + "source": "DMV molecular pore_complex", + "target": "Orf14 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t157", + "source": "DMV molecular pore_complex", + "target": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t158", + "source": "Orf9b_space_ds_space_sgmRNA_rna", + "target": "Orf9b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t159", + "source": "Orf14_space_ds_space_sgmRNA_rna", + "target": "Orf14 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t160", + "source": "Orf7b_space_ds_space_sgmRNA_rna", + "target": "Orf7b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t161", + "source": "Orf3a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "Orf3a_lysosome", + "sign": true + } + ], + "parameters": [] + }, + "semantics": { + "ode": { + "rates": [], + "observables": [], + "time": { + "id": "t" + } + } + }, + "metadata": { + "annotations": {} + } +} \ No newline at end of file From 946dda6fd8c9e2c0391838afd8dfd22d7df1ee69 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 24 Apr 2024 16:45:17 -0400 Subject: [PATCH 38/44] Loop through each controller individually and create a transition dictionary for each controller, rerun script to generate new qual regnet amr for covid-19 disease map --- mira/modeling/amr/regnet.py | 123 +- .../regnet_amr_sbml/Apoptosis.json | 158 +- .../regnet_amr_sbml/Coagulation-pathway.json | 998 +++++- .../regnet_amr_sbml/ER_Stress.json | 1272 ++++++- .../regnet_amr_sbml/ETC.json | 844 ++++- .../regnet_amr_sbml/E_protein.json | 144 +- .../regnet_amr_sbml/HMOX1_Pathway.json | 1180 +++++- .../regnet_amr_sbml/IFN-lambda.json | 170 +- .../regnet_amr_sbml/Interferon1.json | 976 ++++- .../regnet_amr_sbml/JNK_pathway.json | 66 +- .../regnet_amr_sbml/Kynurenine_pathway.json | 1660 ++++++++- .../regnet_amr_sbml/NLRP3_Activation.json | 386 +- .../regnet_amr_sbml/Nsp14.json | 3168 ++++++++++++++++- .../regnet_amr_sbml/Nsp4_Nsp6.json | 204 +- .../regnet_amr_sbml/Nsp9_protein.json | 1202 ++++++- .../regnet_amr_sbml/Orf10_Cul2_pathway.json | 442 ++- .../regnet_amr_sbml/Orf3a.json | 174 +- .../regnet_amr_sbml/PAMP_signaling.json | 446 ++- .../Pyrimidine_deprivation.json | 576 ++- .../RTC-and-transcription.json | 102 +- .../regnet_amr_sbml/Renin_angiotensin.json | 606 +++- .../regnet_amr_sbml/TGFB_pathway.json | 114 +- .../Virus_replication_cycle.json | 1450 ++++++-- 23 files changed, 14556 insertions(+), 1905 deletions(-) diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index 04f9b4f97..021c694d8 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -83,7 +83,7 @@ def __init__(self, model: Model): self.states.append(state_data) self._states_by_id[name] = state_data - idx = 0 + edge_id = 1 # It's possible that something is naturally degraded/replicated # by multiple transitions so we need to collect and aggregate rates intrinsic_by_var = defaultdict(list) @@ -131,62 +131,65 @@ def __init__(self, model: Model): # a regular transition in the regnet framework # Possibilities are: # - ControlledReplication / GroupedControlledProduction - # - ControlledDegradation + # - ControlledDegradation / GroupedControlledDegradation else: - tid = f"t{idx + 1}" - transition_dict = {'id': tid} # If we have multiple controls then the thing that replicates # is both a control and a produced variable. if len(transition.control) > 1: - if isinstance(transition.template, GroupedControlledDegradation): + # GroupedControlledProduction + if is_production(transition.template) or is_replication( + transition.template + ): indep_ctrl = {c.key for c in transition.control} - { - transition.consumed[0].key + transition.produced[0].key } + # There is one corner case where both controllers are also + # the same as the produced variable, in which case. if not indep_ctrl: indep_ctrl = {transition.consumed[0].key} - transition_dict["source"] = vmap[ - sorted(indep_ctrl, key=lambda x: str(x))[0] - ] + for controller in indep_ctrl: + self.create_edge( + transition, + vmap[controller], + vmap[transition.produced[0].key], + edge_id, + ) + edge_id += 1 else: + # GroupedControlledDegradation indep_ctrl = {c.key for c in transition.control} - { - transition.produced[0].key + transition.consumed[0].key } # There is one corner case where both controllers are also # the same as the produced variable, in which case. if not indep_ctrl: - indep_ctrl = {transition.produced[0].key} - transition_dict["source"] = vmap[ - sorted(indep_ctrl, key=lambda x: str(x))[0] - ] - else: - transition_dict['source'] = vmap[transition.control[0].key] - transition_dict['target'] = \ - vmap[transition.consumed[0].key if - transition.consumed else transition.produced[0].key] - transition_dict['sign'] = (is_production(transition.template) or - is_replication(transition.template)) - - # Include rate law - if transition.template.rate_law: - rate_law = transition.template.rate_law.args[0] - pnames = transition.template.get_parameter_names() - # We just choose an arbitrary one deterministically - rate_const = sorted(pnames)[0] if pnames else None + indep_ctrl = {transition.consumed[0].key} - transition_dict['properties'] = { - 'name': tid, - 'rate_constant': rate_const, - } - self.rates.append({ - 'target': tid, - 'expression': str(rate_law), - 'expression_mathml': expression_to_mathml(rate_law) - }) + for controller in indep_ctrl: + self.create_edge( + transition, + vmap[controller], + vmap[transition.consumed[0].key], + edge_id, + ) - self.transitions.append(transition_dict) - idx += 1 + edge_id += 1 + else: + # ControlledDegradation + target = vmap[ + transition.consumed[0].key + if transition.consumed + else transition.produced[0].key + ] + self.create_edge( + transition, + vmap[transition.control[0].key], + target, + edge_id, + ) + edge_id += 1 for var, rates in intrinsic_by_var.items(): rate_law = sum(rates) @@ -238,6 +241,48 @@ def __init__(self, model: Model): self.time = None add_metadata_annotations(self.metadata, model) + def create_edge(self, transition, source, target, edge_id): + """Create and append a transition dictionary to the list of transitions + + Parameters + ---------- + transition : Transition + The Transition object + source : str + The name of the source of the transition + target : str + The name of the target of the transition + edge_id : int + The id to assign to the transition + """ + tid = f"t{edge_id}" + transition_dict = {"id": tid} + transition_dict["source"] = source + transition_dict["target"] = target + transition_dict["sign"] = is_production( + transition.template + ) or is_replication(transition.template) + + if transition.template.rate_law: + rate_law = transition.template.rate_law.args[0] + pnames = transition.template.get_parameter_names() + # We just choose an arbitrary one deterministically + rate_const = sorted(pnames)[0] if pnames else None + + transition_dict["properties"] = { + "name": tid, + "rate_constant": rate_const, + } + self.rates.append( + { + "target": tid, + "expression": str(rate_law), + "expression_mathml": expression_to_mathml(rate_law), + } + ) + + self.transitions.append(transition_dict) + def to_json( self, name: str = None, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json index 37a38b619..49e808ff4 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json @@ -381,102 +381,228 @@ }, { "id": "t2", + "source": "E", + "target": "Orf7a", + "sign": false + }, + { + "id": "t3", "source": "FASLG", "target": "FAS/FASL_complex", "sign": true }, { - "id": "t3", + "id": "t4", "source": "TNF", "target": "TNF/TNFRSF1A_complex", "sign": true }, { - "id": "t4", + "id": "t5", "source": "BCL2/MCL1/BCL2L1_complex", "target": "BCL2/MCL1/BCL2L1_complex", "sign": false }, { - "id": "t5", + "id": "t6", + "source": "TNF/TNFRSF1A_complex", + "target": "TRADD/FADD_complex", + "sign": true + }, + { + "id": "t7", + "source": "TRADD", + "target": "TRADD/FADD_complex", + "sign": true + }, + { + "id": "t8", "source": "FADD", "target": "TRADD/FADD_complex", "sign": true }, { - "id": "t6", + "id": "t9", + "source": "CYCS", + "target": "Apoptosome_complex", + "sign": true + }, + { + "id": "t10", "source": "AKT1", "target": "Apoptosome_complex", "sign": true }, { - "id": "t7", + "id": "t11", + "source": "APAF1", + "target": "Apoptosome_complex", + "sign": true + }, + { + "id": "t12", + "source": "CASP9_cell", + "target": "Apoptosome_complex", + "sign": true + }, + { + "id": "t13", "source": "M", "target": "M", "sign": false }, { - "id": "t8", + "id": "t14", "source": "FAS/FASL_complex", "target": "FADD", "sign": true }, { - "id": "t9", + "id": "t15", "source": "AKT1", "target": "AKT1", "sign": false }, { - "id": "t10", + "id": "t16", + "source": "BID", + "target": "BAX", + "sign": true + }, + { + "id": "t17", "source": "BAD/BBC3/BCL2L11_complex", "target": "BAX", "sign": true }, { - "id": "t11", + "id": "t18", + "source": "BCL2/MCL1/BCL2L1_complex", + "target": "BAX", + "sign": true + }, + { + "id": "t19", "source": "Orf3a", "target": "MAPK14", "sign": true }, { - "id": "t12", + "id": "t20", "source": "BAX", "target": "CYCS", "sign": true }, { - "id": "t13", + "id": "t21", + "source": "MAPK14", + "target": "CYCS", + "sign": true + }, + { + "id": "t22", + "source": "CASP9_cell_active", + "target": "CASP7", + "sign": true + }, + { + "id": "t23", "source": "CASP8", "target": "CASP7", "sign": true }, { - "id": "t14", + "id": "t24", + "source": "Apoptosome_complex", + "target": "CASP9_cell_active", + "sign": true + }, + { + "id": "t25", "source": "AKT1", "target": "CASP9_cell_active", "sign": true }, { - "id": "t15", + "id": "t26", + "source": "CASP9_cell_active", + "target": "CASP3", + "sign": true + }, + { + "id": "t27", "source": "CASP8", "target": "CASP3", "sign": true }, { - "id": "t16", + "id": "t28", + "source": "TRADD/FADD_complex", + "target": "CASP8", + "sign": true + }, + { + "id": "t29", + "source": "Orf3a", + "target": "CASP8", + "sign": true + }, + { + "id": "t30", "source": "FADD", "target": "CASP8", "sign": true }, { - "id": "t17", + "id": "t31", "source": "CASP3", "target": "Apoptosis_phenotype", "sign": true }, { - "id": "t18", + "id": "t32", + "source": "N", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t33", + "source": "Orf8a", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t34", + "source": "Orf9b", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t35", + "source": "Orf3b", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t36", + "source": "Orf6", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t37", + "source": "S", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t38", + "source": "CASP7", + "target": "Apoptosis_phenotype", + "sign": true + }, + { + "id": "t39", "source": "CASP8", "target": "BID", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json index 64bf0f67f..128593bc0 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json @@ -1467,543 +1467,1221 @@ }, { "id": "t2", - "source": "F10a", - "target": "F5a:F10a_complex", + "source": "KNG1", + "target": "KNG1:KLKB1_complex", "sign": true }, { "id": "t3", - "source": "F8a", - "target": "F8:F9_complex", + "source": "F10a", + "target": "F5a:F10a_complex", "sign": true }, { "id": "t4", - "source": "PLAT_blood", - "target": "PLAT:SERPINE1_complex", + "source": "F5a", + "target": "F5a:F10a_complex", "sign": true }, { "id": "t5", - "source": "SARS-CoV-2 infection_phenotype", - "target": "Fibrinogen_complex", + "source": "F8a", + "target": "F8:F9_complex", "sign": true }, { "id": "t6", - "source": "Antithrombin", - "target": "TAT complex_complex", + "source": "F9a", + "target": "F8:F9_complex", "sign": true }, { "id": "t7", - "source": "Thrombin_blood_active", - "target": "Thrombin:Thrombomodulin_complex", + "source": "SARS-CoV-2 infection_phenotype", + "target": "PLAT:SERPINE1_complex", "sign": true }, { "id": "t8", - "source": "C5b:C6:C7_complex", - "target": "C5b:C6:C7:C8A:C8B:C8G_complex", + "source": "PLAT_blood", + "target": "PLAT:SERPINE1_complex", "sign": true }, { "id": "t9", - "source": "C3b", - "target": "C3b:Bb:C3b_complex", + "source": "SERPINE1", + "target": "PLAT:SERPINE1_complex", "sign": true }, { "id": "t10", - "source": "C5b:C6_complex", - "target": "C5b:C6:C7_complex", + "source": "SARS-CoV-2 infection_phenotype", + "target": "Fibrinogen_complex", "sign": true }, { "id": "t11", - "source": "C5b:C6:C7:C8A:C8B:C8G_complex", - "target": "C5b-9_complex_endothelium, vascular", + "source": "SARS-CoV-2 infection_phenotype", + "target": "TAT complex_complex", "sign": true }, { "id": "t12", - "source": "C5b", - "target": "C5b:C6_complex", + "source": "Thrombin_blood_active", + "target": "TAT complex_complex", "sign": true }, { "id": "t13", - "source": "C2a", - "target": "C2a:C4b_complex", + "source": "Antithrombin", + "target": "TAT complex_complex", "sign": true }, { "id": "t14", - "source": "ACE2_blood", - "target": "ACE2:Spike_complex", + "source": "Thrombomodulin", + "target": "Thrombin:Thrombomodulin_complex", "sign": true }, { "id": "t15", - "source": "Plasmin", - "target": "SERPINF2:Plasmin_complex", + "source": "Thrombin_blood_active", + "target": "Thrombin:Thrombomodulin_complex", "sign": true }, { "id": "t16", - "source": "Fibrinogen_complex", - "target": "Fibrinogen:GP6_complex", + "source": "C8A:C8B:C8G_complex", + "target": "C5b:C6:C7:C8A:C8B:C8G_complex", "sign": true }, { "id": "t17", - "source": "GP6:alpha2:beta1_complex", - "target": "GP6:alpha2beta1:VWF_complex", + "source": "C5b:C6:C7_complex", + "target": "C5b:C6:C7:C8A:C8B:C8G_complex", "sign": true }, { "id": "t18", - "source": "GP6", - "target": "GP6:alpha2:beta1_complex", + "source": "C3b", + "target": "C3b:Bb:C3b_complex", "sign": true }, { "id": "t19", - "source": "S", - "target": "C5b-9_complex_endothelium, vascular", + "source": "C3b:Bb_complex", + "target": "C3b:Bb:C3b_complex", "sign": true }, { "id": "t20", - "source": "F12", - "target": "F12a", + "source": "C5b:C6_complex", + "target": "C5b:C6:C7_complex", "sign": true }, { "id": "t21", - "source": "ACE", - "target": "Small peptide", + "source": "C7", + "target": "C5b:C6:C7_complex", "sign": true }, { "id": "t22", - "source": "F12a", - "target": "F11", + "source": "C9", + "target": "C5b-9_complex_endothelium, vascular", "sign": true }, { "id": "t23", - "source": "F12a", - "target": "F11a", + "source": "SARS-CoV-2 infection_phenotype", + "target": "C5b-9_complex_endothelium, vascular", "sign": true }, { "id": "t24", - "source": "F11a", - "target": "F9a", + "source": "C5b:C6:C7:C8A:C8B:C8G_complex", + "target": "C5b-9_complex_endothelium, vascular", "sign": true }, { "id": "t25", - "source": "Antithrombin", - "target": "F10a", + "source": "C6", + "target": "C5b:C6_complex", "sign": true }, { "id": "t26", - "source": "SARS-CoV-2 infection_phenotype", - "target": "F8", + "source": "C5b", + "target": "C5b:C6_complex", "sign": true }, { "id": "t27", - "source": "F8", - "target": "F8a", + "source": "C4b", + "target": "C2a:C4b_complex", "sign": true }, { "id": "t28", - "source": "Antithrombin", - "target": "Thrombin_blood_active", + "source": "C2a", + "target": "C2a:C4b_complex", "sign": true }, { "id": "t29", - "source": "ACE", - "target": "angiotensin II_simple_molecule", + "source": "S", + "target": "ACE2:Spike_complex", "sign": true }, { "id": "t30", - "source": "AGT", - "target": "angiotensin I_simple_molecule", + "source": "ACE2_blood", + "target": "ACE2:Spike_complex", "sign": true }, { "id": "t31", - "source": "Kallikrein", - "target": "REN", + "source": "SARS-CoV-2 infection_phenotype", + "target": "SERPINF2:Plasmin_complex", "sign": true }, { "id": "t32", - "source": "aldosterone_simple_molecule_blood", - "target": "ACE", + "source": "Plasmin", + "target": "SERPINF2:Plasmin_complex", "sign": true }, { "id": "t33", - "source": "F5", - "target": "F5a", + "source": "SERPINF2", + "target": "SERPINF2:Plasmin_complex", "sign": true }, { "id": "t34", - "source": "SARS-CoV-2 infection_phenotype", - "target": "SARS-CoV-2 infection_phenotype", - "sign": false + "source": "GP6", + "target": "Fibrinogen:GP6_complex", + "sign": true }, { "id": "t35", - "source": "F5a:F10a_complex", - "target": "Thrombin_blood", + "source": "Fibrinogen_complex", + "target": "Fibrinogen:GP6_complex", "sign": true }, { "id": "t36", - "source": "SARS-CoV-2 infection_phenotype", - "target": "PROC", + "source": "VWF", + "target": "GP6:alpha2beta1:VWF_complex", "sign": true }, { "id": "t37", - "source": "Fibrin polymer", - "target": "D-dimer", + "source": "GP6:alpha2:beta1_complex", + "target": "GP6:alpha2beta1:VWF_complex", "sign": true }, { "id": "t38", - "source": "C5b-9_complex_endothelium, vascular", - "target": "Plasminogen", + "source": "GP6", + "target": "GP6:alpha2:beta1_complex", "sign": true }, { "id": "t39", - "source": "F11a", - "target": "Plasmin", + "source": "ITGA2:ITGAB1_complex", + "target": "GP6:alpha2:beta1_complex", "sign": true }, { "id": "t40", - "source": "Bradykinin", - "target": "PLAT_blood_active", + "source": "S", + "target": "C5b-9_complex_endothelium, vascular", "sign": true }, { "id": "t41", - "source": "AGTR1_blood", - "target": "SERPINE1", + "source": "F12", + "target": "F12a", "sign": true }, { "id": "t42", - "source": "Thrombin_blood_active", - "target": "TAFI", + "source": "KLKB1", + "target": "F12a", "sign": true }, { "id": "t43", - "source": "SERPINE1", - "target": "SERPINE1", - "sign": false + "source": "F8", + "target": "Small peptide", + "sign": true }, { "id": "t44", - "source": "SARS-CoV-2 infection_phenotype", - "target": "TNF", + "source": "ACE", + "target": "Small peptide", "sign": true }, { "id": "t45", - "source": "SARS-CoV-2 infection_phenotype", - "target": "IL6", + "source": "Antithrombin", + "target": "Small peptide", "sign": true }, { "id": "t46", - "source": "SARS-CoV-2 infection_phenotype", - "target": "IL1B", + "source": "PROC", + "target": "Small peptide", "sign": true }, { "id": "t47", - "source": "KNG1:KLKB1_complex", - "target": "Kininogen", + "source": "F10", + "target": "Small peptide", "sign": true }, { "id": "t48", - "source": "F12a", - "target": "Kallikrein", + "source": "F12", + "target": "Small peptide", "sign": true }, { "id": "t49", - "source": "C2a:C4b_complex", - "target": "C5a", + "source": "KLKB1", + "target": "Small peptide", "sign": true }, { "id": "t50", - "source": "C4d", - "target": "Thrombosis_phenotype_blood", + "source": "F9a", + "target": "Small peptide", "sign": true }, { "id": "t51", - "source": "SARS-CoV-2 infection_phenotype", - "target": "Thrombomodulin", + "source": "Thrombin_blood_active", + "target": "Small peptide", "sign": true }, { "id": "t52", - "source": "SARS-CoV-2 infection_phenotype", - "target": "IL8", + "source": "Bradykinin", + "target": "Small peptide", "sign": true }, { "id": "t53", - "source": "SARS-CoV-2 infection_phenotype", - "target": "IL2RA", + "source": "Thrombin_blood_active", + "target": "F11", "sign": true }, { "id": "t54", - "source": "C2a:C4b_complex", - "target": "C3a", + "source": "F12a", + "target": "F11", "sign": true }, { "id": "t55", - "source": "C2a:C4b_complex", - "target": "C3b", + "source": "Thrombin_blood_active", + "target": "F11a", "sign": true }, { "id": "t56", - "source": "C2a:C4b_complex", - "target": "C5b", + "source": "F12a", + "target": "F11a", "sign": true }, { "id": "t57", - "source": "MBL2", - "target": "MASP1", + "source": "F11a", + "target": "F9a", "sign": true }, { "id": "t58", - "source": "C4", - "target": "C4a", + "source": "F9", + "target": "F9a", "sign": true }, { "id": "t59", - "source": "C4", - "target": "C4b", + "source": "F9a", + "target": "F10a", "sign": true }, { "id": "t60", - "source": "C2", - "target": "C2a", + "source": "F10", + "target": "F10a", "sign": true }, { "id": "t61", - "source": "C2", - "target": "C2b", + "source": "Antithrombin", + "target": "F10a", "sign": true }, { "id": "t62", - "source": "C4b", - "target": "C4d", + "source": "SARS-CoV-2 infection_phenotype", + "target": "F8", "sign": true }, { "id": "t63", - "source": "C4d", - "target": "C4d deposition_phenotype", + "source": "F8", + "target": "F8a", "sign": true }, { "id": "t64", - "source": "C4d deposition_phenotype", - "target": "septal capillary necrosis_phenotype", + "source": "Thrombin_blood_active", + "target": "F8a", "sign": true }, { "id": "t65", - "source": "C5b-9_complex_endothelium, vascular", - "target": "C5b-9 deposition_phenotype", + "source": "PROC", + "target": "F8a", "sign": true }, { "id": "t66", - "source": "ACE2_blood", - "target": "ACE2_endothelium, vascular", + "source": "Thrombin_blood", + "target": "Thrombin_blood_active", "sign": true }, { "id": "t67", - "source": "Fibrinogen_complex", - "target": "Fibrin monomer", + "source": "Heparin_simple_molecule", + "target": "Thrombin_blood_active", "sign": true }, { "id": "t68", - "source": "ACE2_endothelium, vascular", - "target": "angiotensin I-7_simple_molecule", + "source": "Antithrombin", + "target": "Thrombin_blood_active", "sign": true }, { "id": "t69", - "source": "KNG1:KLKB1_complex", - "target": "Bradykinin", + "source": "SARS-CoV-2 infection_phenotype", + "target": "angiotensin II_simple_molecule", "sign": true }, { "id": "t70", "source": "ACE", - "target": "Bradykinin(1-5)", + "target": "angiotensin II_simple_molecule", + "sign": true + }, + { + "id": "t71", + "source": "angiotensin I_simple_molecule", + "target": "angiotensin II_simple_molecule", + "sign": true + }, + { + "id": "t72", + "source": "AGT", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t73", + "source": "REN", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t74", + "source": "Prorenin", + "target": "REN", + "sign": true + }, + { + "id": "t75", + "source": "Kallikrein", + "target": "REN", + "sign": true + }, + { + "id": "t76", + "source": "aldosterone_simple_molecule_blood", + "target": "ACE", + "sign": true + }, + { + "id": "t77", + "source": "F5", + "target": "F5a", + "sign": true + }, + { + "id": "t78", + "source": "Thrombin:Thrombomodulin_complex", + "target": "F5a", + "sign": true + }, + { + "id": "t79", + "source": "PROC", + "target": "F5a", + "sign": true + }, + { + "id": "t80", + "source": "SARS-CoV-2 infection_phenotype", + "target": "SARS-CoV-2 infection_phenotype", + "sign": false + }, + { + "id": "t81", + "source": "F5a:F10a_complex", + "target": "Thrombin_blood", + "sign": true + }, + { + "id": "t82", + "source": "Prothrombin", + "target": "Thrombin_blood", + "sign": true + }, + { + "id": "t83", + "source": "SARS-CoV-2 infection_phenotype", + "target": "PROC", + "sign": true + }, + { + "id": "t84", + "source": "SARS-CoV-2 infection_phenotype", + "target": "D-dimer", + "sign": true + }, + { + "id": "t85", + "source": "Fibrin polymer", + "target": "D-dimer", + "sign": true + }, + { + "id": "t86", + "source": "Plasmin", + "target": "D-dimer", + "sign": true + }, + { + "id": "t87", + "source": "TAFI", + "target": "D-dimer", + "sign": true + }, + { + "id": "t88", + "source": "C5b-9_complex_endothelium, vascular", + "target": "Plasminogen", + "sign": true + }, + { + "id": "t89", + "source": "PLAU", + "target": "Plasmin", + "sign": true + }, + { + "id": "t90", + "source": "F11a", + "target": "Plasmin", + "sign": true + }, + { + "id": "t91", + "source": "Plasminogen", + "target": "Plasmin", + "sign": true + }, + { + "id": "t92", + "source": "KLKB1", + "target": "Plasmin", + "sign": true + }, + { + "id": "t93", + "source": "PLAT_blood_active", + "target": "Plasmin", + "sign": true + }, + { + "id": "t94", + "source": "PROC", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t95", + "source": "angiotensin I-7_simple_molecule", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t96", + "source": "angiotensin II_simple_molecule", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t97", + "source": "PLAT_blood", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t98", + "source": "SERPINE1", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t99", + "source": "Bradykinin", + "target": "PLAT_blood_active", + "sign": true + }, + { + "id": "t100", + "source": "AGTR1_blood", + "target": "SERPINE1", + "sign": true + }, + { + "id": "t101", + "source": "angiotensin I-7_simple_molecule", + "target": "SERPINE1", + "sign": true + }, + { + "id": "t102", + "source": "angiotensin II_simple_molecule", + "target": "SERPINE1", + "sign": true + }, + { + "id": "t103", + "source": "aldosterone_simple_molecule_blood", + "target": "SERPINE1", + "sign": true + }, + { + "id": "t104", + "source": "IL6", + "target": "SERPINE1", + "sign": true + }, + { + "id": "t105", + "source": "Thrombin_blood_active", + "target": "TAFI", + "sign": true + }, + { + "id": "t106", + "source": "SERPINE1", + "target": "SERPINE1", + "sign": false + }, + { + "id": "t107", + "source": "SARS-CoV-2 infection_phenotype", + "target": "TNF", + "sign": true + }, + { + "id": "t108", + "source": "cytokine storm_phenotype", + "target": "TNF", + "sign": true + }, + { + "id": "t109", + "source": "SARS-CoV-2 infection_phenotype", + "target": "IL6", + "sign": true + }, + { + "id": "t110", + "source": "cytokine storm_phenotype", + "target": "IL6", + "sign": true + }, + { + "id": "t111", + "source": "SARS-CoV-2 infection_phenotype", + "target": "IL1B", + "sign": true + }, + { + "id": "t112", + "source": "cytokine storm_phenotype", + "target": "IL1B", + "sign": true + }, + { + "id": "t113", + "source": "KNG1:KLKB1_complex", + "target": "Kininogen", + "sign": true + }, + { + "id": "t114", + "source": "KLKB1", + "target": "Kallikrein", + "sign": true + }, + { + "id": "t115", + "source": "F12a", + "target": "Kallikrein", + "sign": true + }, + { + "id": "t116", + "source": "KNG1:KLKB1_complex", + "target": "Kallikrein", + "sign": true + }, + { + "id": "t117", + "source": "C3b:Bb:C3b_complex", + "target": "C5a", + "sign": true + }, + { + "id": "t118", + "source": "C2a:C4b_complex", + "target": "C5a", + "sign": true + }, + { + "id": "t119", + "source": "SARS-CoV-2 infection_phenotype", + "target": "C5a", + "sign": true + }, + { + "id": "t120", + "source": "C5", + "target": "C5a", + "sign": true + }, + { + "id": "t121", + "source": "Plasmin", + "target": "C5a", + "sign": true + }, + { + "id": "t122", + "source": "VWF", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t123", + "source": "TNF", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t124", + "source": "angiotensin II_simple_molecule", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t125", + "source": "CRP", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t126", + "source": "C5b-9_complex_endothelium, vascular", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t127", + "source": "IL6", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t128", + "source": "IL2RA", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t129", + "source": "C4d", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t130", + "source": "IL1B", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t131", + "source": "IL8", + "target": "Thrombosis_phenotype_blood", + "sign": true + }, + { + "id": "t132", + "source": "SARS-CoV-2 infection_phenotype", + "target": "Thrombomodulin", + "sign": true + }, + { + "id": "t133", + "source": "SARS-CoV-2 infection_phenotype", + "target": "IL8", "sign": true }, { - "id": "t71", + "id": "t134", + "source": "cytokine storm_phenotype", + "target": "IL8", + "sign": true + }, + { + "id": "t135", + "source": "SARS-CoV-2 infection_phenotype", + "target": "IL2RA", + "sign": true + }, + { + "id": "t136", + "source": "cytokine storm_phenotype", + "target": "IL2RA", + "sign": true + }, + { + "id": "t137", + "source": "C3", + "target": "C3a", + "sign": true + }, + { + "id": "t138", + "source": "C2a:C4b_complex", + "target": "C3a", + "sign": true + }, + { + "id": "t139", + "source": "C3b:Bb_complex", + "target": "C3a", + "sign": true + }, + { + "id": "t140", + "source": "C3", + "target": "C3b", + "sign": true + }, + { + "id": "t141", + "source": "C2a:C4b_complex", + "target": "C3b", + "sign": true + }, + { + "id": "t142", + "source": "C3b:Bb_complex", + "target": "C3b", + "sign": true + }, + { + "id": "t143", + "source": "C2a:C4b_complex", + "target": "C5b", + "sign": true + }, + { + "id": "t144", + "source": "C5", + "target": "C5b", + "sign": true + }, + { + "id": "t145", + "source": "C3b:Bb:C3b_complex", + "target": "C5b", + "sign": true + }, + { + "id": "t146", + "source": "MBL2", + "target": "MASP1", + "sign": true + }, + { + "id": "t147", + "source": "MASP2", + "target": "C4a", + "sign": true + }, + { + "id": "t148", + "source": "C4", + "target": "C4a", + "sign": true + }, + { + "id": "t149", + "source": "MASP2", + "target": "C4b", + "sign": true + }, + { + "id": "t150", + "source": "C4", + "target": "C4b", + "sign": true + }, + { + "id": "t151", + "source": "C2", + "target": "C2a", + "sign": true + }, + { + "id": "t152", + "source": "MASP1", + "target": "C2a", + "sign": true + }, + { + "id": "t153", + "source": "C2", + "target": "C2b", + "sign": true + }, + { + "id": "t154", + "source": "MASP1", + "target": "C2b", + "sign": true + }, + { + "id": "t155", + "source": "CFI", + "target": "C4d", + "sign": true + }, + { + "id": "t156", + "source": "SARS-CoV-2 infection_phenotype", + "target": "C4d", + "sign": true + }, + { + "id": "t157", + "source": "C4b", + "target": "C4d", + "sign": true + }, + { + "id": "t158", + "source": "S", + "target": "C4d", + "sign": true + }, + { + "id": "t159", + "source": "C4d", + "target": "C4d deposition_phenotype", + "sign": true + }, + { + "id": "t160", + "source": "C4d deposition_phenotype", + "target": "septal capillary necrosis_phenotype", + "sign": true + }, + { + "id": "t161", + "source": "C5b-9_complex_endothelium, vascular", + "target": "C5b-9 deposition_phenotype", + "sign": true + }, + { + "id": "t162", + "source": "SARS-CoV-2 infection_phenotype", + "target": "ACE2_endothelium, vascular", + "sign": true + }, + { + "id": "t163", + "source": "ACE2_blood", + "target": "ACE2_endothelium, vascular", + "sign": true + }, + { + "id": "t164", + "source": "SARS-CoV-2 infection_phenotype", + "target": "Fibrin monomer", + "sign": true + }, + { + "id": "t165", + "source": "Thrombin_blood", + "target": "Fibrin monomer", + "sign": true + }, + { + "id": "t166", + "source": "Fibrinogen_complex", + "target": "Fibrin monomer", + "sign": true + }, + { + "id": "t167", + "source": "Thrombin:Thrombomodulin_complex", + "target": "Fibrin monomer", + "sign": true + }, + { + "id": "t168", + "source": "ACE2_endothelium, vascular", + "target": "angiotensin I-7_simple_molecule", + "sign": true + }, + { + "id": "t169", + "source": "angiotensin II_simple_molecule", + "target": "angiotensin I-7_simple_molecule", + "sign": true + }, + { + "id": "t170", + "source": "KNG1:KLKB1_complex", + "target": "Bradykinin", + "sign": true + }, + { + "id": "t171", + "source": "ACE", + "target": "Bradykinin(1-5)", + "sign": true + }, + { + "id": "t172", + "source": "Bradykinin", + "target": "Bradykinin(1-5)", + "sign": true + }, + { + "id": "t173", "source": "C5b-9 deposition_phenotype", "target": "apoptosis_phenotype", "sign": true }, { - "id": "t72", + "id": "t174", "source": "C5b-9 deposition_phenotype", "target": "platelet aggregation_phenotype", "sign": true }, { - "id": "t73", + "id": "t175", "source": "SARS-CoV-2 infection_phenotype", "target": "CRP", "sign": true }, { - "id": "t74", + "id": "t176", "source": "SARS-CoV-2 infection_phenotype", "target": "VWF", "sign": true }, { - "id": "t75", + "id": "t177", "source": "MASP2", "target": "MASP2 deposition_phenotype", "sign": true }, { - "id": "t76", + "id": "t178", "source": "F13a", "target": "Fibrin polymer", "sign": true }, { - "id": "t77", + "id": "t179", + "source": "Fibrin monomer", + "target": "Fibrin polymer", + "sign": true + }, + { + "id": "t180", + "source": "GP6:alpha2beta1:VWF_complex", + "target": "platelet activation_phenotype", + "sign": true + }, + { + "id": "t181", "source": "Fibrinogen:GP6_complex", "target": "platelet activation_phenotype", "sign": true }, { - "id": "t78", + "id": "t182", + "source": "MAS1", + "target": "thrombus formation_phenotype", + "sign": true + }, + { + "id": "t183", + "source": "platelet activation_phenotype", + "target": "thrombus formation_phenotype", + "sign": true + }, + { + "id": "t184", "source": "AGTR1_platelet", "target": "thrombus formation_phenotype", "sign": true }, { - "id": "t79", + "id": "t185", "source": "SARS-CoV-2 infection_phenotype", "target": "MASP2", "sign": true }, { - "id": "t80", + "id": "t186", "source": "angiotensin I-7_simple_molecule", "target": "MAS1", "sign": true }, { - "id": "t81", + "id": "t187", "source": "angiotensin II_simple_molecule", "target": "AGTR1_platelet", "sign": true }, { - "id": "t82", + "id": "t188", "source": "ACE2:Spike_complex", "target": "SARS-CoV-2 viral entry_phenotype", "sign": true }, { - "id": "t83", + "id": "t189", + "source": "AGTR1_blood", + "target": "aldosterone_simple_molecule_blood", + "sign": true + }, + { + "id": "t190", + "source": "K+_ion", + "target": "aldosterone_simple_molecule_blood", + "sign": true + }, + { + "id": "t191", + "source": "angiotensin II_simple_molecule", + "target": "aldosterone_simple_molecule_blood", + "sign": true + }, + { + "id": "t192", + "source": "SARS-CoV-2 infection_phenotype", + "target": "aldosterone_simple_molecule_blood", + "sign": true + }, + { + "id": "t193", "source": "ACTH_simple_molecule", "target": "aldosterone_simple_molecule_blood", "sign": true }, { - "id": "t84", + "id": "t194", "source": "aldosterone_simple_molecule_blood", "target": "aldosterone_simple_molecule_endothelium, vascular", "sign": true }, { - "id": "t85", + "id": "t195", + "source": "aldosterone_simple_molecule_endothelium, vascular", + "target": "NR3C2", + "sign": true + }, + { + "id": "t196", "source": "AGTR1_blood", "target": "NR3C2", "sign": true }, { - "id": "t86", + "id": "t197", "source": "aldosterone_simple_molecule_endothelium, vascular", "target": "vascular remodeling_phenotype", "sign": true }, { - "id": "t87", + "id": "t198", "source": "angiotensin II_simple_molecule", "target": "AGTR1_blood", "sign": true }, { - "id": "t88", + "id": "t199", "source": "Hypokalemia_phenotype", "target": "Hypokalemia_phenotype", "sign": false }, { - "id": "t89", + "id": "t200", + "source": "NR3C2", + "target": "Thrombosis_phenotype_human host", + "sign": true + }, + { + "id": "t201", "source": "AGTR1_blood", "target": "Thrombosis_phenotype_human host", "sign": true }, { - "id": "t90", + "id": "t202", "source": "aldosterone_simple_molecule_endothelium, vascular", "target": "vascular inflammation_phenotype", "sign": true }, { - "id": "t91", + "id": "t203", "source": "SARS-CoV-2 infection_phenotype", "target": "Hypokalemia_phenotype", "sign": true + }, + { + "id": "t204", + "source": "aldosterone_simple_molecule_blood", + "target": "Hypokalemia_phenotype", + "sign": true } ], "parameters": [] diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json index 21211a244..2f5c20eff 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json @@ -1951,642 +1951,1554 @@ "edges": [ { "id": "t1", - "source": "EIF2S1_phosphorylated", + "source": "EIF2S3:GDP_complex", "target": "EIF2-P:GDP_complex", "sign": true }, { "id": "t2", - "source": "BAK1", - "target": "TRAF2:ERN1_complex", + "source": "EIF2S1_phosphorylated", + "target": "EIF2-P:GDP_complex", "sign": true }, { "id": "t3", - "source": "Ca2+space_ER_space_depletion_phenotype", - "target": "SIGMAR1:ITPR3_complex", + "source": "EIF2S2", + "target": "EIF2-P:GDP_complex", "sign": true }, { "id": "t4", - "source": "Met-tRNA_rna", - "target": "EIF2:GDP:Met-tRNA_complex", + "source": "BAX_endoplasmic reticulum", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t5", - "source": "ATG5", - "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", + "source": "BAX:ERN1_complex", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t6", - "source": "ERN1_endoplasmic reticulum", - "target": "ERN1:Unfolded_space_protein_complex", + "source": "BCL2L1", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t7", - "source": "HSPA5_endoplasmic reticulum", - "target": "SIGMAR1:HSPA5_complex", + "source": "ERN1:Unfolded_space_protein_complex", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t8", - "source": "RMDN3", - "target": "VAPB:RMDN3_complex", + "source": "BCL2", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t9", - "source": "EIF2:GDP:Met-tRNA_complex", - "target": "Ternary_space_Complex_complex", + "source": "TRAF2", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t10", - "source": "ADAM17_early_space_endosome", - "target": "PACS2-ADAM17_space_interaction_complex", + "source": "BAK1", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t11", - "source": "BCAP31", - "target": "FIS1:BCAP31_complex", + "source": "BAK1:ERN1_complex", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t12", - "source": "MFN2_endoplasmic reticulum", - "target": "MFN2:MFN2_complex", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t13", - "source": "BBC3", - "target": "ERN1:BBC3_complex", + "source": "Ca2+space_ER_space_depletion_phenotype", + "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t14", - "source": "EIF2S1", - "target": "EIF2:GDP_complex", + "source": "ITPR3", + "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t15", - "source": "MFN1", - "target": "MFN1:MFN2_complex", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t16", - "source": "MCU", - "target": "MCU:MICU1:MICU2:SMDT1_complex", + "source": "ER_space_stress_phenotype", + "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t17", - "source": "BCL2L11_endoplasmic reticulum", - "target": "ERN1:BCL2L11_complex", + "source": "Met-tRNA_rna", + "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t18", - "source": "CAPN1", - "target": "CAPN1:Ca2+_complex", + "source": "Ternary_space_Complex_complex", + "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t19", - "source": "EIF2AK3", - "target": "EIF2AK3:EIF2AK3_complex", + "source": "GDP_simple_molecule", + "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t20", - "source": "MCU:MICU1:MICU2:SMDT1_complex", - "target": "Mitochondrial_space_calcium_space_uniporter_space_complex_complex", + "source": "EIF2:GDP_complex", + "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t21", - "source": "ACE2", - "target": "ACE2:Spike_complex", + "source": "SQSTM1_space_", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t22", - "source": "HSPA5_default_compartment", - "target": "HSPA5-Spike interaction_complex", + "source": "MAP1LC3A", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t23", - "source": "ACE2,_space_membrane-bound", - "target": "ACE2-SARS-CoV interaction_complex", + "source": "ATG5", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t24", - "source": "ATF4", - "target": "PPP1R15A_rna", + "source": "CASP8:CASP8-ubq:FADD_complex", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t25", - "source": "BAX_phosphorylated", - "target": "release_space_of_space_ER_space_Ca2+_phenotype", + "source": "TRIM13", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t26", - "source": "ATF6_endoplasmic reticulum", - "target": "ATF6_Golgi apparatus", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t27", - "source": "DDIT3", - "target": "DDIT3_phosphorylated", + "source": "ERN1_endoplasmic reticulum", + "target": "ERN1:Unfolded_space_protein_complex", "sign": true }, { "id": "t28", - "source": "TRAF2:ERN1_complex", - "target": "TRAF2", + "source": "Unfolded_space_protein", + "target": "ERN1:Unfolded_space_protein_complex", "sign": true }, { "id": "t29", - "source": "MFN2_endoplasmic reticulum", - "target": "endoplasmic_space_reticulum_space_organization_phenotype", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "SIGMAR1:HSPA5_complex", "sign": true }, { "id": "t30", - "source": "ACE2", - "target": "HSPA5_endoplasmic reticulum", + "source": "HSPA5_endoplasmic reticulum", + "target": "SIGMAR1:HSPA5_complex", "sign": true }, { "id": "t31", - "source": "ERO1A_endoplasmic reticulum", - "target": "ITPR", + "source": "RMDN3", + "target": "VAPB:RMDN3_complex", "sign": true }, { "id": "t32", - "source": "GDP_simple_molecule", - "target": "GTP_simple_molecule", + "source": "VAPB", + "target": "VAPB:RMDN3_complex", "sign": true }, { "id": "t33", - "source": "ACE2", - "target": "HSPA5_rna", + "source": "EIF2B_complex", + "target": "Ternary_space_Complex_complex", "sign": true }, { "id": "t34", - "source": "ATF6_Golgi apparatus", - "target": "UPR_phenotype", + "source": "GTP_simple_molecule", + "target": "Ternary_space_Complex_complex", "sign": true }, { "id": "t35", - "source": "FIS1", - "target": "Ca2+space_mitochondrial_space_concentration_phenotype", + "source": "EIF2:GDP:Met-tRNA_complex", + "target": "Ternary_space_Complex_complex", "sign": true }, { "id": "t36", - "source": "PACS2_endoplasmic reticulum", - "target": "PACS2_endoplasmic reticulum", - "sign": false + "source": "PACS2_early_space_endosome", + "target": "PACS2-ADAM17_space_interaction_complex", + "sign": true }, { "id": "t37", - "source": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", - "target": "ER_space_Stress_phenotype", + "source": "ADAM17_early_space_endosome", + "target": "PACS2-ADAM17_space_interaction_complex", "sign": true }, { "id": "t38", - "source": "ATF6:HSPA5_complex", - "target": "ATF6_endoplasmic reticulum", + "source": "BCAP31", + "target": "FIS1:BCAP31_complex", "sign": true }, { "id": "t39", - "source": "DNAJC3_rna", - "target": "DNAJC3", + "source": "FIS1", + "target": "FIS1:BCAP31_complex", "sign": true }, { "id": "t40", - "source": "ATF4", - "target": "DDIT3_rna", + "source": "MFN2_endoplasmic reticulum", + "target": "MFN2:MFN2_complex", "sign": true }, { "id": "t41", - "source": "ATF4_gene", - "target": "ATF4_rna", + "source": "MFN2_mitochondrion", + "target": "MFN2:MFN2_complex", "sign": true }, { "id": "t42", - "source": "BCL2L11_phosphorylated", - "target": "BCL2L11_cell", + "source": "BBC3", + "target": "ERN1:BBC3_complex", "sign": true }, { "id": "t43", - "source": "DDIT3", - "target": "TRIB3_rna", + "source": "ERN1_endoplasmic reticulum", + "target": "ERN1:BBC3_complex", "sign": true }, { "id": "t44", - "source": "ITPR3:HSPA9:VDAC1_complex", - "target": "Ca2+_ion_mitochondrion", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "target": "ERN1:BBC3_complex", "sign": true }, { "id": "t45", - "source": "ERO1A_cell", - "target": "ERO1A_endoplasmic reticulum", + "source": "EIF2S3:GDP_complex", + "target": "EIF2:GDP_complex", "sign": true }, { "id": "t46", - "source": "EIF2AK1", - "target": "EIF2S1", + "source": "EIF2S2", + "target": "EIF2:GDP_complex", "sign": true }, { "id": "t47", - "source": "CASP9", - "target": "cleaved~CASP9", + "source": "EIF2S1", + "target": "EIF2:GDP_complex", "sign": true }, { "id": "t48", - "source": "ITPR3", - "target": "RMDN3", - "sign": false + "source": "MFN2_endoplasmic reticulum", + "target": "MFN1:MFN2_complex", + "sign": true }, { "id": "t49", - "source": "PPP1R15A_rna", - "target": "PPP1R15A", + "source": "MFN1", + "target": "MFN1:MFN2_complex", "sign": true }, { "id": "t50", - "source": "mitochondrial_space_fission_phenotype", - "target": "mitochondria_space_fragmentation_phenotype", + "source": "MCU2", + "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t51", - "source": "FIS1", - "target": "mitochondrial_space_outer_space_membrane_space_depolarization_phenotype", + "source": "SMDT1", + "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t52", - "source": "Ca2+space_ER_space_depletion_phenotype", - "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "source": "MCU1", + "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t53", - "source": "ATF6_nucleus", - "target": "XBP1_rna", + "source": "MCU", + "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t54", - "source": "ERAD_phenotype", - "target": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "source": "BCL2L11_endoplasmic reticulum", + "target": "ERN1:BCL2L11_complex", "sign": true }, { "id": "t55", - "source": "DDIT3_phosphorylated", - "target": "BCL2_rna", + "source": "ERN1_endoplasmic reticulum", + "target": "ERN1:BCL2L11_complex", "sign": true }, { "id": "t56", - "source": "ERO1A_endoplasmic reticulum", - "target": "hyperoxidation_phenotype", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "target": "ERN1:BCL2L11_complex", "sign": true }, { "id": "t57", - "source": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", - "target": "protein_space_ubiquitination_space_and_space_destruction_phenotype", + "source": "CAPN1", + "target": "CAPN1:Ca2+_complex", "sign": true }, { "id": "t58", - "source": "ER_space_Stress_phenotype", - "target": "CDK5", + "source": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", + "target": "CAPN1:Ca2+_complex", "sign": true }, { "id": "t59", - "source": "MAP3K5_phosphorylated", - "target": "MAPK14_phosphorylated", + "source": "Ca2+_ion_cell", + "target": "CAPN1:Ca2+_complex", "sign": true }, { "id": "t60", - "source": "ERO1A_rna", - "target": "ERO1A_cell", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, { "id": "t61", - "source": "Apoptosis_phenotype_cell", - "target": "Cell_space_survival_phenotype", + "source": "Unfolded_space_protein", + "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, { "id": "t62", - "source": "ER_space_stress_phenotype", - "target": "unfolded_space_protein_space_response_space_(UPR)_phenotype", + "source": "EIF2AK3", + "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, { "id": "t63", - "source": "DNAJC3", - "target": "EIF2AK2", + "source": "MCU:MICU1:MICU2:SMDT1_complex", + "target": "Mitochondrial_space_calcium_space_uniporter_space_complex_complex", "sign": true }, { "id": "t64", - "source": "Mitochondrial_space_calcium_space_uniporter_space_complex_complex", - "target": "Ca2+_ion_mitochondrial matrix", + "source": "ACE2", + "target": "ACE2:Spike_complex", "sign": true }, { "id": "t65", - "source": "BAX_cell", - "target": "BAX_phosphorylated", + "source": "S", + "target": "ACE2:Spike_complex", "sign": true }, { "id": "t66", - "source": "ATF6_endoplasmic reticulum", - "target": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "source": "HSPA5_default_compartment", + "target": "HSPA5-Spike interaction_complex", "sign": true }, { "id": "t67", - "source": "MAP3K4_phosphorylated", - "target": "MAPK8_phosphorylated", + "source": "S", + "target": "HSPA5-Spike interaction_complex", "sign": true }, { "id": "t68", - "source": "XBP1_rna", - "target": "XBP1", + "source": "ACE2,_space_soluble", + "target": "ACE2-SARS-CoV interaction_complex", "sign": true }, { "id": "t69", - "source": "Ternary_space_Complex_complex", - "target": "Translation_space_initiation_phenotype", + "source": "ACE2,_space_membrane-bound", + "target": "ACE2-SARS-CoV interaction_complex", "sign": true }, { "id": "t70", - "source": "BID", - "target": "BID_phosphorylated", + "source": "S", + "target": "ACE2-SARS-CoV interaction_complex", "sign": true }, { "id": "t71", - "source": "TRIB3_rna", - "target": "TRIB3", + "source": "ATF4", + "target": "PPP1R15A_rna", "sign": true }, { "id": "t72", - "source": "CASP4", - "target": "cleaved~CASP4", + "source": "DDIT3", + "target": "PPP1R15A_rna", "sign": true }, { "id": "t73", - "source": "ACE2", - "target": "ER_space_stress_phenotype", + "source": "PPP1R15A_gene", + "target": "PPP1R15A_rna", "sign": true }, { "id": "t74", + "source": "BAX_phosphorylated", + "target": "release_space_of_space_ER_space_Ca2+_phenotype", + "sign": true + }, + { + "id": "t75", + "source": "MBTPS1", + "target": "ATF6_Golgi apparatus", + "sign": true + }, + { + "id": "t76", + "source": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "target": "ATF6_Golgi apparatus", + "sign": true + }, + { + "id": "t77", + "source": "ER_space_Stress_phenotype", + "target": "ATF6_Golgi apparatus", + "sign": true + }, + { + "id": "t78", + "source": "MBTPS2", + "target": "ATF6_Golgi apparatus", + "sign": true + }, + { + "id": "t79", + "source": "ATF6_endoplasmic reticulum", + "target": "ATF6_Golgi apparatus", + "sign": true + }, + { + "id": "t80", + "source": "DDIT3", + "target": "DDIT3_phosphorylated", + "sign": true + }, + { + "id": "t81", + "source": "MAPK14_phosphorylated", + "target": "DDIT3_phosphorylated", + "sign": true + }, + { + "id": "t82", + "source": "TRAF2:ERN1_complex", + "target": "TRAF2", + "sign": true + }, + { + "id": "t83", + "source": "MFN2_endoplasmic reticulum", + "target": "endoplasmic_space_reticulum_space_organization_phenotype", + "sign": true + }, + { + "id": "t84", + "source": "ER_space_stress_phenotype", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t85", + "source": "SIGMAR1:HSPA5_complex", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t86", + "source": "ACE2", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t87", + "source": "Ca2+space_ER_space_depletion_phenotype", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t88", + "source": "Unfolded_space_protein", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t89", + "source": "ATF6:HSPA5_complex", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t90", + "source": "HSPA5_rna", + "target": "HSPA5_endoplasmic reticulum", + "sign": true + }, + { + "id": "t91", + "source": "TMBIM6", + "target": "ITPR", + "sign": true + }, + { + "id": "t92", + "source": "ERO1A_endoplasmic reticulum", + "target": "ITPR", + "sign": true + }, + { + "id": "t93", + "source": "Ternary_space_Complex_complex", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t94", + "source": "GDP_simple_molecule", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t95", + "source": "HSPA5_gene", + "target": "HSPA5_rna", + "sign": true + }, + { + "id": "t96", + "source": "ACE2", + "target": "HSPA5_rna", + "sign": true + }, + { + "id": "t97", + "source": "S", + "target": "HSPA5_rna", + "sign": true + }, + { + "id": "t98", + "source": "ATF6_Golgi apparatus", + "target": "UPR_phenotype", + "sign": true + }, + { + "id": "t99", + "source": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "target": "UPR_phenotype", + "sign": true + }, + { + "id": "t100", + "source": "XBP1", + "target": "UPR_phenotype", + "sign": true + }, + { + "id": "t101", + "source": "EIF2AK3:EIF2AK3_complex", + "target": "UPR_phenotype", + "sign": true + }, + { + "id": "t102", + "source": "TRAF2:ERN1_complex", + "target": "UPR_phenotype", + "sign": true + }, + { + "id": "t103", + "source": "RMDN3", + "target": "Ca2+space_mitochondrial_space_concentration_phenotype", + "sign": true + }, + { + "id": "t104", + "source": "FIS1", + "target": "Ca2+space_mitochondrial_space_concentration_phenotype", + "sign": true + }, + { + "id": "t105", + "source": "VAPB", + "target": "Ca2+space_mitochondrial_space_concentration_phenotype", + "sign": true + }, + { + "id": "t106", + "source": "PACS2_endoplasmic reticulum", + "target": "PACS2_endoplasmic reticulum", + "sign": false + }, + { + "id": "t107", + "source": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "target": "ER_space_Stress_phenotype", + "sign": true + }, + { + "id": "t108", + "source": "ATF6:HSPA5_complex", + "target": "ATF6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t109", + "source": "Unfolded_space_protein", + "target": "ATF6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t110", + "source": "DNAJC3_rna", + "target": "DNAJC3", + "sign": true + }, + { + "id": "t111", + "source": "ATF4", + "target": "DDIT3_rna", + "sign": true + }, + { + "id": "t112", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "target": "DDIT3_rna", + "sign": true + }, + { + "id": "t113", + "source": "XBP1", + "target": "DDIT3_rna", + "sign": true + }, + { + "id": "t114", + "source": "ATF6_nucleus", + "target": "DDIT3_rna", + "sign": true + }, + { + "id": "t115", + "source": "DDIT3_gene", + "target": "DDIT3_rna", + "sign": true + }, + { + "id": "t116", + "source": "ATF4_gene", + "target": "ATF4_rna", + "sign": true + }, + { + "id": "t117", + "source": "EIF2-P:GDP_complex", + "target": "ATF4_rna", + "sign": true + }, + { + "id": "t118", + "source": "PPP2CA", + "target": "BCL2L11_cell", + "sign": true + }, + { + "id": "t119", + "source": "BCL2L11_phosphorylated", + "target": "BCL2L11_cell", + "sign": true + }, + { + "id": "t120", + "source": "DDIT3", + "target": "TRIB3_rna", + "sign": true + }, + { + "id": "t121", + "source": "TRIB3_gene", + "target": "TRIB3_rna", + "sign": true + }, + { + "id": "t122", + "source": "ITPR3:HSPA9:VDAC1_complex", + "target": "Ca2+_ion_mitochondrion", + "sign": true + }, + { + "id": "t123", + "source": "Ca2+_ion_endoplasmic reticulum", + "target": "Ca2+_ion_mitochondrion", + "sign": true + }, + { + "id": "t124", + "source": "SIGMAR1:ITPR3_complex", + "target": "Ca2+_ion_mitochondrion", + "sign": true + }, + { + "id": "t125", + "source": "ERO1A_cell", + "target": "ERO1A_endoplasmic reticulum", + "sign": true + }, + { + "id": "t126", + "source": "PPP1R15A", + "target": "EIF2S1", + "sign": true + }, + { + "id": "t127", + "source": "EIF2S1_phosphorylated", + "target": "EIF2S1", + "sign": true + }, + { + "id": "t128", + "source": "EIF2AK1", + "target": "EIF2S1", + "sign": true + }, + { + "id": "t129", + "source": "cleaved~CASP4", + "target": "cleaved~CASP9", + "sign": true + }, + { + "id": "t130", + "source": "CASP9", + "target": "cleaved~CASP9", + "sign": true + }, + { + "id": "t131", + "source": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "target": "RMDN3", + "sign": false + }, + { + "id": "t132", + "source": "ITPR3", + "target": "RMDN3", + "sign": false + }, + { + "id": "t133", + "source": "VAPB", + "target": "RMDN3", + "sign": false + }, + { + "id": "t134", + "source": "PPP1R15A_rna", + "target": "PPP1R15A", + "sign": true + }, + { + "id": "t135", + "source": "mitochondrial_space_fission_phenotype", + "target": "mitochondria_space_fragmentation_phenotype", + "sign": true + }, + { + "id": "t136", + "source": "FIS1", + "target": "mitochondrial_space_outer_space_membrane_space_depolarization_phenotype", + "sign": true + }, + { + "id": "t137", + "source": "Ca2+space_ER_space_depletion_phenotype", + "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "sign": true + }, + { + "id": "t138", + "source": "ER_space_stress_phenotype", + "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "sign": true + }, + { + "id": "t139", + "source": "SIGMAR1:HSPA5_complex", + "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "sign": true + }, + { + "id": "t140", + "source": "ERN1:BCL2L11_complex", + "target": "XBP1_rna", + "sign": true + }, + { + "id": "t141", + "source": "ERN1:BBC3_complex", + "target": "XBP1_rna", + "sign": true + }, + { + "id": "t142", + "source": "ATF6_nucleus", + "target": "XBP1_rna", + "sign": true + }, + { + "id": "t143", + "source": "TRAF2:ERN1_complex", + "target": "XBP1_rna", + "sign": true + }, + { + "id": "t144", + "source": "XBP1_gene", + "target": "XBP1_rna", + "sign": true + }, + { + "id": "t145", + "source": "Unfolded_space_protein", + "target": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "sign": true + }, + { + "id": "t146", + "source": "ERAD_phenotype", + "target": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "sign": true + }, + { + "id": "t147", + "source": "BCL2_gene", + "target": "BCL2_rna", + "sign": true + }, + { + "id": "t148", + "source": "DDIT3_phosphorylated", + "target": "BCL2_rna", + "sign": true + }, + { + "id": "t149", + "source": "ERO1A_endoplasmic reticulum", + "target": "hyperoxidation_phenotype", + "sign": true + }, + { + "id": "t150", + "source": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "target": "protein_space_ubiquitination_space_and_space_destruction_phenotype", + "sign": true + }, + { + "id": "t151", + "source": "ER_space_Stress_phenotype", + "target": "CDK5", + "sign": true + }, + { + "id": "t152", + "source": "MAPK14", + "target": "MAPK14_phosphorylated", + "sign": true + }, + { + "id": "t153", + "source": "MAP3K5_phosphorylated", + "target": "MAPK14_phosphorylated", + "sign": true + }, + { + "id": "t154", + "source": "ERO1A_rna", + "target": "ERO1A_cell", + "sign": true + }, + { + "id": "t155", + "source": "Apoptosis_phenotype_cell", + "target": "Cell_space_survival_phenotype", + "sign": true + }, + { + "id": "t156", + "source": "MFN2_endoplasmic reticulum", + "target": "unfolded_space_protein_space_response_space_(UPR)_phenotype", + "sign": true + }, + { + "id": "t157", + "source": "ER_space_stress_phenotype", + "target": "unfolded_space_protein_space_response_space_(UPR)_phenotype", + "sign": true + }, + { + "id": "t158", + "source": "p20", + "target": "unfolded_space_protein_space_response_space_(UPR)_phenotype", + "sign": true + }, + { + "id": "t159", + "source": "presence_space_of_space_dsRNA_phenotype", + "target": "EIF2AK2", + "sign": true + }, + { + "id": "t160", + "source": "DNAJC3", + "target": "EIF2AK2", + "sign": true + }, + { + "id": "t161", + "source": "Ca2+_ion_mitochondrion", + "target": "Ca2+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t162", + "source": "Mitochondrial_space_calcium_space_uniporter_space_complex_complex", + "target": "Ca2+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t163", + "source": "BAX_cell", + "target": "BAX_phosphorylated", + "sign": true + }, + { + "id": "t164", + "source": "MAPK8_phosphorylated", + "target": "BAX_phosphorylated", + "sign": true + }, + { + "id": "t165", + "source": "MAPK14_phosphorylated", + "target": "BAX_phosphorylated", + "sign": true + }, + { + "id": "t166", + "source": "EIF2AK3:EIF2AK3_complex", + "target": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "sign": true + }, + { + "id": "t167", + "source": "ATF6_endoplasmic reticulum", + "target": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "sign": true + }, + { + "id": "t168", + "source": "MAP3K4_phosphorylated", + "target": "MAPK8_phosphorylated", + "sign": true + }, + { + "id": "t169", + "source": "MAPK8", + "target": "MAPK8_phosphorylated", + "sign": true + }, + { + "id": "t170", + "source": "MAP3K5_phosphorylated", + "target": "MAPK8_phosphorylated", + "sign": true + }, + { + "id": "t171", + "source": "XBP1_rna", + "target": "XBP1", + "sign": true + }, + { + "id": "t172", + "source": "Ternary_space_Complex_complex", + "target": "Translation_space_initiation_phenotype", + "sign": true + }, + { + "id": "t173", + "source": "BID", + "target": "BID_phosphorylated", + "sign": true + }, + { + "id": "t174", + "source": "MAPK8_phosphorylated", + "target": "BID_phosphorylated", + "sign": true + }, + { + "id": "t175", + "source": "TRIB3_rna", + "target": "TRIB3", + "sign": true + }, + { + "id": "t176", + "source": "CASP4", + "target": "cleaved~CASP4", + "sign": true + }, + { + "id": "t177", + "source": "CAPN1:Ca2+_complex", + "target": "cleaved~CASP4", + "sign": true + }, + { + "id": "t178", + "source": "ACE2", + "target": "ER_space_stress_phenotype", + "sign": true + }, + { + "id": "t179", + "source": "MFN2_endoplasmic reticulum", + "target": "ER_space_stress_phenotype", + "sign": true + }, + { + "id": "t180", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "target": "ER_space_stress_phenotype", + "sign": true + }, + { + "id": "t181", "source": "HYOU1_rna", "target": "HYOU1", "sign": true }, { - "id": "t75", + "id": "t182", + "source": "cleaved~CASP4", + "target": "cleaved~CASP3", + "sign": true + }, + { + "id": "t183", "source": "CASP3", "target": "cleaved~CASP3", "sign": true }, { - "id": "t76", + "id": "t184", + "source": "EIF2S1", + "target": "EIF2S1_phosphorylated", + "sign": true + }, + { + "id": "t185", + "source": "GCN2:ATP_complex", + "target": "EIF2S1_phosphorylated", + "sign": true + }, + { + "id": "t186", + "source": "EIF2AK2", + "target": "EIF2S1_phosphorylated", + "sign": true + }, + { + "id": "t187", "source": "DNAJC3", "target": "EIF2S1_phosphorylated", "sign": true }, { - "id": "t77", + "id": "t188", + "source": "EIF2AK3:EIF2AK3_complex", + "target": "EIF2S1_phosphorylated", + "sign": true + }, + { + "id": "t189", + "source": "PACS2_endoplasmic reticulum", + "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "sign": true + }, + { + "id": "t190", + "source": "MFN1:MFN2_complex", + "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "sign": true + }, + { + "id": "t191", "source": "FIS1:BCAP31_complex", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { - "id": "t78", + "id": "t192", + "source": "MFN2:MFN2_complex", + "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "sign": true + }, + { + "id": "t193", + "source": "VAPB:RMDN3_complex", + "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "sign": true + }, + { + "id": "t194", + "source": "DDIT3", + "target": "AP-1_phosphorylated_phosphorylated", + "sign": true + }, + { + "id": "t195", + "source": "MAPK8_phosphorylated", + "target": "AP-1_phosphorylated_phosphorylated", + "sign": true + }, + { + "id": "t196", "source": "AP-1", "target": "AP-1_phosphorylated_phosphorylated", "sign": true }, { - "id": "t79", + "id": "t197", + "source": "EIF2B_complex", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t198", + "source": "GTP_simple_molecule", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t199", "source": "EIF2:GDP:Met-tRNA_complex", "target": "GDP_simple_molecule", "sign": true }, { - "id": "t80", + "id": "t200", + "source": "TMBIM6", + "target": "Ca2+_ion_cell", + "sign": true + }, + { + "id": "t201", "source": "ITPR", "target": "Ca2+_ion_cell", "sign": true }, { - "id": "t81", + "id": "t202", + "source": "Ca2+_ion_endoplasmic reticulum", + "target": "Ca2+_ion_cell", + "sign": true + }, + { + "id": "t203", + "source": "RYR1", + "target": "Ca2+_ion_cell", + "sign": true + }, + { + "id": "t204", + "source": "BCAP31", + "target": "p20", + "sign": true + }, + { + "id": "t205", + "source": "PACS2_endoplasmic reticulum", + "target": "p20", + "sign": true + }, + { + "id": "t206", "source": "Apoptosis_phenotype_endoplasmic reticulum", "target": "p20", "sign": true }, { - "id": "t82", + "id": "t207", "source": "ATF4_rna", "target": "ATF4", "sign": true }, { - "id": "t83", + "id": "t208", + "source": "TRAF2:ERN1_complex", + "target": "MAP3K5_phosphorylated", + "sign": true + }, + { + "id": "t209", "source": "MAP3K5", "target": "MAP3K5_phosphorylated", "sign": true }, { - "id": "t84", + "id": "t210", + "source": "TRAF2", + "target": "MAP3K5_phosphorylated", + "sign": true + }, + { + "id": "t211", + "source": "MFN2_endoplasmic reticulum", + "target": "Apoptosis_phenotype_endoplasmic reticulum", + "sign": true + }, + { + "id": "t212", "source": "ER_space_stress_phenotype", "target": "Apoptosis_phenotype_endoplasmic reticulum", "sign": true }, { - "id": "t85", + "id": "t213", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "target": "Apoptosis_phenotype_endoplasmic reticulum", + "sign": true + }, + { + "id": "t214", + "source": "DNAJC3_gene", + "target": "DNAJC3_rna", + "sign": true + }, + { + "id": "t215", "source": "ATF6_nucleus", "target": "DNAJC3_rna", "sign": true }, { - "id": "t86", + "id": "t216", "source": "DDIT3_rna", "target": "DDIT3", "sign": true }, { - "id": "t87", + "id": "t217", + "source": "MFN2_rna", + "target": "MFN2_endoplasmic reticulum", + "sign": true + }, + { + "id": "t218", "source": "ER_space_stress_phenotype", "target": "MFN2_endoplasmic reticulum", "sign": true }, { - "id": "t88", + "id": "t219", "source": "PACS2-ADAM17_space_interaction_complex", "target": "ADAM17_cell", "sign": true }, { - "id": "t89", + "id": "t220", "source": "XBP1", "target": "ERAD_phenotype", "sign": true }, { - "id": "t90", + "id": "t221", "source": "MFN2_gene", "target": "MFN2_rna", "sign": true }, { - "id": "t91", + "id": "t222", + "source": "DDIT3_phosphorylated", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t223", + "source": "cleaved~CASP9", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t224", + "source": "MAPK14_phosphorylated", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t225", "source": "BAX_phosphorylated", "target": "Apoptosis_phenotype_cell", "sign": true }, { - "id": "t92", + "id": "t226", + "source": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t227", + "source": "cleaved~CASP3", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t228", + "source": "BID_phosphorylated", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t229", + "source": "TRIB3", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t230", + "source": "BCL2L11_phosphorylated", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t231", + "source": "Cell_space_survival_phenotype", + "target": "Apoptosis_phenotype_cell", + "sign": true + }, + { + "id": "t232", "source": "Mitochondrial_space_calcium_space_uniporter_space_complex_complex", "target": "mitochondrial_space_calcium_space_ion_space_transmembrane_space_transport_phenotype", "sign": true }, { - "id": "t93", + "id": "t233", + "source": "ADAM17_cell", + "target": "ACE2,_space_soluble", + "sign": true + }, + { + "id": "t234", "source": "ACE2", "target": "ACE2,_space_soluble", "sign": true }, { - "id": "t94", + "id": "t235", "source": "ER_space_Stress_phenotype", "target": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", "sign": true }, { - "id": "t95", + "id": "t236", "source": "Ca2+_ion_cell", "target": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", "sign": true }, { - "id": "t96", + "id": "t237", + "source": "release_space_of_space_ER_space_Ca2+_phenotype", + "target": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", + "sign": true + }, + { + "id": "t238", "source": "ATF6_Golgi apparatus", "target": "ATF6_nucleus", "sign": true }, { - "id": "t97", + "id": "t239", + "source": "MFN2_endoplasmic reticulum", + "target": "endoplasmic_space_reticulum_space_calcium_space_ion_space_homeostasis_phenotype", + "sign": true + }, + { + "id": "t240", "source": "HSPA5_endoplasmic reticulum", "target": "endoplasmic_space_reticulum_space_calcium_space_ion_space_homeostasis_phenotype", "sign": true }, { - "id": "t98", + "id": "t241", + "source": "MAP3K4", + "target": "MAP3K4_phosphorylated", + "sign": true + }, + { + "id": "t242", "source": "CDK5", "target": "MAP3K4_phosphorylated", "sign": true }, { - "id": "t99", + "id": "t243", "source": "RMDN3", "target": "VAPB", "sign": false }, { - "id": "t100", + "id": "t244", + "source": "HYOU1_gene", + "target": "HYOU1_rna", + "sign": true + }, + { + "id": "t245", "source": "ATF6_nucleus", "target": "HYOU1_rna", "sign": true }, { - "id": "t101", + "id": "t246", "source": "BCL2L11_cell", "target": "BCL2L11_phosphorylated", "sign": true }, { - "id": "t102", + "id": "t247", + "source": "MAPK8_phosphorylated", + "target": "BCL2L11_phosphorylated", + "sign": true + }, + { + "id": "t248", + "source": "ERO1A_gene", + "target": "ERO1A_rna", + "sign": true + }, + { + "id": "t249", + "source": "DDIT3", + "target": "ERO1A_rna", + "sign": true + }, + { + "id": "t250", "source": "ATF6_nucleus", "target": "ERO1A_rna", "sign": true }, { - "id": "t103", + "id": "t251", + "source": "ADAM17_cell", + "target": "ACE2,_space_membrane-bound", + "sign": true + }, + { + "id": "t252", "source": "ACE2", "target": "ACE2,_space_membrane-bound", "sign": true }, { - "id": "t104", + "id": "t253", "source": "ACE2", "target": "ACE2", "sign": false }, { - "id": "t105", + "id": "t254", + "source": "HSPA5-Spike interaction_complex", + "target": "viral entry into host cell_phenotype", + "sign": true + }, + { + "id": "t255", "source": "ACE2,_space_soluble", "target": "viral entry into host cell_phenotype", "sign": true }, { - "id": "t106", + "id": "t256", + "source": "ACE2-SARS-CoV interaction_complex", + "target": "viral entry into host cell_phenotype", + "sign": true + }, + { + "id": "t257", + "source": "SARS-CoV infection_phenotype", + "target": "viral entry into host cell_phenotype", + "sign": true + }, + { + "id": "t258", "source": "viral entry into host cell_phenotype", "target": "viral entry into host cell_phenotype", "sign": false }, { - "id": "t107", + "id": "t259", "source": "ACE2", "target": "viral RNA genome replication_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json index 031fe12c1..6811ee491 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json @@ -910,289 +910,931 @@ }, { "id": "t2", - "source": "F-ATPase_complex_mitochondrial matrix", - "target": "ATP_space_Synthase_complex", + "source": "Nsp4_mitochondrion", + "target": "TIM_space_complex:Nsp4_complex", "sign": true }, { "id": "t3", - "source": "Mt_space_ribosomal_space_proteins_complex", - "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", + "source": "Nsp6", + "target": "ATP_space_Synthase_complex", "sign": true }, { "id": "t4", - "source": "NDUFA1", - "target": "Complex_space_1_complex", + "source": "F-ATPase_complex_mitochondrial matrix", + "target": "ATP_space_Synthase_complex", "sign": true }, { "id": "t5", - "source": "ATP5MG", - "target": "F-ATPase_complex_mitochondrial matrix", + "source": "H+_ion_mitochondrion", + "target": "ATP_space_Synthase_complex", "sign": true }, { "id": "t6", - "source": "ACAD9", - "target": "OXPHOS_space_factors_complex", + "source": "Mt_space_ribosomal_space_proteins_complex", + "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t7", - "source": "Complex_space_1_complex", - "target": "complex_space_2_complex_mitochondrial matrix", + "source": "Mt_space_translation_complex", + "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t8", - "source": "Complex_space_1_complex", - "target": "complex_space_3_complex", + "source": "Nsp8-affected Mt ribosomal proteins_complex", + "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t9", - "source": "TCA_phenotype", - "target": "complex_space_2_complex_mitochondrial matrix", + "source": "mt_space_mRNA_rna", + "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t10", - "source": "Mt-tRNA_space_synthetase_complex", - "target": "MT_space_tRNAs_complex", + "source": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", + "target": "Complex_space_1_complex", "sign": true }, { "id": "t11", - "source": "Nsp8", - "target": "Nsp8", - "sign": false + "source": "NDUFB9", + "target": "Complex_space_1_complex", + "sign": true }, { "id": "t12", - "source": "O2_simple_molecule", - "target": "paraquat_space_dication_complex", + "source": "NDUFA1", + "target": "Complex_space_1_complex", "sign": true }, { "id": "t13", - "source": "OXPHOS_space_factors_complex", - "target": "complex_space_4_complex", + "source": "NADH_simple_molecule", + "target": "Complex_space_1_complex", "sign": true }, { "id": "t14", - "source": "DNAJC11", - "target": "Nsp4:DNAJC11_complex", + "source": "OXPHOS_space_factors_complex", + "target": "Complex_space_1_complex", "sign": true }, { "id": "t15", "source": "ATP5MG", - "target": "F-ATPase:Nsp6_complex", + "target": "F-ATPase_complex_mitochondrial matrix", "sign": true }, { "id": "t16", - "source": "Fe2+_ion", - "target": "Fe3+_ion", + "source": "F-ATPase_complex_mitochondrial matrix", + "target": "F-ATPase_complex_mitochondrial matrix", "sign": true }, { "id": "t17", - "source": "Complex_space_1_complex", - "target": "paraquat_simple_molecule", + "source": "ACAD9", + "target": "OXPHOS_space_factors_complex", "sign": true }, { "id": "t18", - "source": "MT_space_transcription_complex", - "target": "mt_space_mRNA_rna", + "source": "NDUFAF7", + "target": "OXPHOS_space_factors_complex", "sign": true }, { "id": "t19", - "source": "Orf9c", - "target": "Orf9c", - "sign": false + "source": "ECSIT", + "target": "OXPHOS_space_factors_complex", + "sign": true }, { "id": "t20", - "source": "SOD1", - "target": "H2O2_simple_molecule", + "source": "Complex_space_1_complex", + "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t21", - "source": "ATP_space_Synthase_complex", - "target": "H+_ion_mitochondrial matrix", + "source": "Q_simple_molecule_mitochondrial matrix", + "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t22", - "source": "Mt-DNA_space_repair_complex", - "target": "mt_space_DNA_gene", + "source": "SIRT3", + "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t23", - "source": "Fe3+_ion", - "target": "Fe2+_ion", + "source": "OXPHOS_space_factors_complex", + "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t24", - "source": "CAT", - "target": "H2O_simple_molecule", + "source": "Complex_space_1_complex", + "target": "complex_space_3_complex", "sign": true }, { "id": "t25", - "source": "O2_simple_molecule", - "target": "Q_simple_molecule_mitochondrial matrix", + "source": "Q_simple_molecule_mitochondrial matrix", + "target": "complex_space_3_complex", "sign": true }, { "id": "t26", - "source": "hydroxide_simple_molecule", - "target": "ROS_simple_molecule", + "source": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", + "target": "complex_space_3_complex", "sign": true }, { "id": "t27", - "source": "PRDX_complex", - "target": "TXN2", + "source": "OXPHOS_space_factors_complex", + "target": "complex_space_3_complex", "sign": true }, { "id": "t28", - "source": "GSR", - "target": "NADP(+)_simple_molecule", + "source": "TCA_phenotype", + "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t29", - "source": "Fe2+_ion", - "target": "HO_simple_molecule", + "source": "Mt-tRNA_space_synthetase_complex", + "target": "MT_space_tRNAs_complex", "sign": true }, { "id": "t30", - "source": "Fe3+_ion", - "target": "O2_simple_molecule", + "source": "mt_space_DNA_gene", + "target": "MT_space_tRNAs_complex", "sign": true }, { "id": "t31", - "source": "Complex_space_1_complex", - "target": "H+_ion_mitochondrion", + "source": "TRMT1", + "target": "MT_space_tRNAs_complex", "sign": true }, { "id": "t32", - "source": "O2_simple_molecule", - "target": "superoxide_simple_molecule", - "sign": true + "source": "Nsp8", + "target": "Nsp8", + "sign": false }, { "id": "t33", - "source": "Orf9c", - "target": "Orf9c", - "sign": false + "source": "O2_simple_molecule", + "target": "paraquat_space_dication_complex", + "sign": true }, { "id": "t34", - "source": "mt_space_DNA_gene", - "target": "damaged_space_mt_space_DNA_gene", + "source": "paraquat_simple_molecule", + "target": "paraquat_space_dication_complex", "sign": true }, { "id": "t35", - "source": "Fe2+_ion", - "target": "hydroxide_simple_molecule", + "source": "complex_space_3_complex", + "target": "complex_space_4_complex", "sign": true }, { "id": "t36", - "source": "ATP_space_Synthase_complex", - "target": "ATP_simple_molecule", + "source": "CYCS_mitochondrial matrix", + "target": "complex_space_4_complex", "sign": true }, { "id": "t37", - "source": "Complex_space_1_complex", - "target": "ubiquinol_simple_molecule_mitochondrial matrix", + "source": "OXPHOS_space_factors_complex", + "target": "complex_space_4_complex", "sign": true }, { "id": "t38", - "source": "Mt-dNTP_space_pool_complex", - "target": "mt_space_DNA_space_replication_phenotype", + "source": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", + "target": "complex_space_4_complex", "sign": true }, { "id": "t39", - "source": "GSR", - "target": "glutathione_simple_molecule", + "source": "Nsp4_cell", + "target": "Nsp4:DNAJC11_complex", "sign": true }, { "id": "t40", - "source": "Orf9c", - "target": "Orf9c", - "sign": false + "source": "DNAJC11", + "target": "Nsp4:DNAJC11_complex", + "sign": true }, { "id": "t41", - "source": "GPX1", - "target": "glutathione_space_disulfide_simple_molecule", + "source": "Nsp6", + "target": "F-ATPase:Nsp6_complex", "sign": true }, { "id": "t42", - "source": "Orf9b", - "target": "precursor_space_protein_space_N-terminus_space_binding", + "source": "ATP5MG", + "target": "F-ATPase:Nsp6_complex", "sign": true }, { "id": "t43", - "source": "Orf9c", - "target": "Orf9c", - "sign": false + "source": "H2O2_simple_molecule", + "target": "Fe3+_ion", + "sign": true }, { "id": "t44", - "source": "SIRT3", - "target": "SOD2", + "source": "Fe2+_ion", + "target": "Fe3+_ion", "sign": true }, { "id": "t45", - "source": "Complex_space_1_complex", - "target": "NAD+_simple_molecule", + "source": "hydroxide_simple_molecule", + "target": "Fe3+_ion", "sign": true }, { "id": "t46", - "source": "O2_simple_molecule", - "target": "O2-_simple_molecule", + "source": "paraquat_space_dication_complex", + "target": "paraquat_simple_molecule", "sign": true }, { "id": "t47", - "source": "Nsp7", - "target": "Nsp7", - "sign": false + "source": "Complex_space_1_complex", + "target": "paraquat_simple_molecule", + "sign": true }, { "id": "t48", - "source": "TOM_space_complex_complex_mitochondrion", - "target": "Nsp4_mitochondrion", + "source": "superoxide_simple_molecule", + "target": "paraquat_simple_molecule", "sign": true }, { "id": "t49", - "source": "O2_simple_molecule", + "source": "MT_space_transcription_complex", + "target": "mt_space_mRNA_rna", + "sign": true + }, + { + "id": "t50", + "source": "TFAM", + "target": "mt_space_mRNA_rna", + "sign": true + }, + { + "id": "t51", + "source": "damaged_space_mt_space_DNA_gene", + "target": "mt_space_mRNA_rna", + "sign": true + }, + { + "id": "t52", + "source": "mt_space_DNA_gene", + "target": "mt_space_mRNA_rna", + "sign": true + }, + { + "id": "t53", + "source": "Orf9c", + "target": "Orf9c", + "sign": false + }, + { + "id": "t54", + "source": "H+_ion_mitochondrial matrix", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t55", + "source": "superoxide_simple_molecule", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t56", + "source": "SOD1", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t57", + "source": "SOD2", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t58", + "source": "Fe3+_ion", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t59", + "source": "H2O2_simple_molecule", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t60", + "source": "ATP_space_Synthase_complex", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t61", + "source": "hydroxide_simple_molecule", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t62", + "source": "superoxide_simple_molecule", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t63", + "source": "Complex_space_1_complex", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t64", + "source": "NADH_simple_molecule", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t65", + "source": "Mt-dNTP_space_pool_complex", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t66", + "source": "TFAM", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t67", + "source": "Mt-DNA_space_repair_complex", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t68", + "source": "mt_space_DNA_space_damage_phenotype", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t69", + "source": "damaged_space_mt_space_DNA_gene", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t70", + "source": "mt_space_DNA_space_replication_phenotype", + "target": "mt_space_DNA_gene", + "sign": true + }, + { + "id": "t71", + "source": "Fe3+_ion", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t72", + "source": "superoxide_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t73", + "source": "GPX1", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t74", + "source": "GPX4", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t75", + "source": "H2O2_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t76", + "source": "CAT", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t77", + "source": "TXN2", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t78", + "source": "hydroxide_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t79", + "source": "glutathione_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "PRDX_complex", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t81", + "source": "O2_simple_molecule", + "target": "Q_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t82", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "target": "Q_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t83", + "source": "H+_ion_mitochondrial matrix", + "target": "Q_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t84", + "source": "complex_space_3_complex", + "target": "Q_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t85", + "source": "CYCS_mitochondrial matrix", + "target": "Q_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t86", + "source": "H2O2_simple_molecule", + "target": "ROS_simple_molecule", + "sign": true + }, + { + "id": "t87", + "source": "hydroxide_simple_molecule", + "target": "ROS_simple_molecule", + "sign": true + }, + { + "id": "t88", + "source": "superoxide_simple_molecule", + "target": "ROS_simple_molecule", + "sign": true + }, + { + "id": "t89", + "source": "NADPH_simple_molecule", + "target": "TXN2", + "sign": true + }, + { + "id": "t90", + "source": "H2O2_simple_molecule", + "target": "TXN2", + "sign": true + }, + { + "id": "t91", + "source": "TXNRD2", + "target": "TXN2", + "sign": true + }, + { + "id": "t92", + "source": "PRDX_complex", + "target": "TXN2", + "sign": true + }, + { + "id": "t93", + "source": "GSR", + "target": "NADP(+)_simple_molecule", + "sign": true + }, + { + "id": "t94", + "source": "TXNRD2", + "target": "NADP(+)_simple_molecule", + "sign": true + }, + { + "id": "t95", + "source": "TXN2", + "target": "NADP(+)_simple_molecule", + "sign": true + }, + { + "id": "t96", + "source": "NADPH_simple_molecule", + "target": "NADP(+)_simple_molecule", + "sign": true + }, + { + "id": "t97", + "source": "glutathione_space_disulfide_simple_molecule", + "target": "NADP(+)_simple_molecule", + "sign": true + }, + { + "id": "t98", + "source": "H2O2_simple_molecule", + "target": "HO_simple_molecule", + "sign": true + }, + { + "id": "t99", + "source": "Fe2+_ion", + "target": "HO_simple_molecule", + "sign": true + }, + { + "id": "t100", + "source": "hydroxide_simple_molecule", + "target": "HO_simple_molecule", + "sign": true + }, + { + "id": "t101", + "source": "Fe3+_ion", + "target": "O2_simple_molecule", + "sign": true + }, + { + "id": "t102", + "source": "superoxide_simple_molecule", + "target": "O2_simple_molecule", + "sign": true + }, + { + "id": "t103", + "source": "O2_simple_molecule", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t104", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t105", + "source": "H+_ion_mitochondrial matrix", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t106", + "source": "complex_space_3_complex", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t107", + "source": "Complex_space_1_complex", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t108", + "source": "CYCS_mitochondrial matrix", + "target": "H+_ion_mitochondrion", + "sign": true + }, + { + "id": "t109", + "source": "O2_simple_molecule", + "target": "superoxide_simple_molecule", + "sign": true + }, + { + "id": "t110", + "source": "H2O2_simple_molecule", + "target": "superoxide_simple_molecule", + "sign": true + }, + { + "id": "t111", + "source": "hydroxide_simple_molecule", + "target": "superoxide_simple_molecule", + "sign": true + }, + { + "id": "t112", + "source": "paraquat_simple_molecule", + "target": "superoxide_simple_molecule", + "sign": true + }, + { + "id": "t113", + "source": "Orf9c", + "target": "Orf9c", + "sign": false + }, + { + "id": "t114", + "source": "mt_space_DNA_gene", + "target": "damaged_space_mt_space_DNA_gene", + "sign": true + }, + { + "id": "t115", + "source": "mt_space_DNA_space_damage_phenotype", + "target": "damaged_space_mt_space_DNA_gene", + "sign": true + }, + { + "id": "t116", + "source": "H2O2_simple_molecule", + "target": "hydroxide_simple_molecule", + "sign": true + }, + { + "id": "t117", + "source": "Fe2+_ion", + "target": "hydroxide_simple_molecule", + "sign": true + }, + { + "id": "t118", + "source": "ATP_space_Synthase_complex", + "target": "ATP_simple_molecule", + "sign": true + }, + { + "id": "t119", + "source": "ADP_simple_molecule", + "target": "ATP_simple_molecule", + "sign": true + }, + { + "id": "t120", + "source": "Pi_simple_molecule", + "target": "ATP_simple_molecule", + "sign": true + }, + { + "id": "t121", + "source": "H+_ion_mitochondrial matrix", + "target": "ATP_simple_molecule", + "sign": true + }, + { + "id": "t122", + "source": "complex_space_2_complex_mitochondrial matrix", + "target": "ubiquinol_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t123", + "source": "Q_simple_molecule_mitochondrial matrix", + "target": "ubiquinol_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t124", + "source": "Complex_space_1_complex", + "target": "ubiquinol_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t125", + "source": "Mt-dNTP_space_pool_complex", + "target": "mt_space_DNA_space_replication_phenotype", + "sign": true + }, + { + "id": "t126", + "source": "TFAM", + "target": "mt_space_DNA_space_replication_phenotype", + "sign": true + }, + { + "id": "t127", + "source": "Mt_space_replication_complex", + "target": "mt_space_DNA_space_replication_phenotype", + "sign": true + }, + { + "id": "t128", + "source": "NADPH_simple_molecule", + "target": "glutathione_simple_molecule", + "sign": true + }, + { + "id": "t129", + "source": "glutathione_space_disulfide_simple_molecule", + "target": "glutathione_simple_molecule", + "sign": true + }, + { + "id": "t130", + "source": "GSR", + "target": "glutathione_simple_molecule", + "sign": true + }, + { + "id": "t131", + "source": "Orf9c", + "target": "Orf9c", + "sign": false + }, + { + "id": "t132", + "source": "GPX1", + "target": "glutathione_space_disulfide_simple_molecule", + "sign": true + }, + { + "id": "t133", + "source": "H2O2_simple_molecule", + "target": "glutathione_space_disulfide_simple_molecule", + "sign": true + }, + { + "id": "t134", + "source": "glutathione_simple_molecule", + "target": "glutathione_space_disulfide_simple_molecule", + "sign": true + }, + { + "id": "t135", + "source": "GPX4", + "target": "glutathione_space_disulfide_simple_molecule", + "sign": true + }, + { + "id": "t136", + "source": "TIM_space_complex:Nsp4_complex", + "target": "precursor_space_protein_space_N-terminus_space_binding", + "sign": true + }, + { + "id": "t137", + "source": "TIM_space_complex_complex", + "target": "precursor_space_protein_space_N-terminus_space_binding", + "sign": true + }, + { + "id": "t138", + "source": "TOM_space_complex_complex_mitochondrion", + "target": "precursor_space_protein_space_N-terminus_space_binding", + "sign": true + }, + { + "id": "t139", + "source": "TIM23_space_complex_complex", + "target": "precursor_space_protein_space_N-terminus_space_binding", + "sign": true + }, + { + "id": "t140", + "source": "Orf9b", + "target": "precursor_space_protein_space_N-terminus_space_binding", + "sign": true + }, + { + "id": "t141", + "source": "Orf9c", + "target": "Orf9c", + "sign": false + }, + { + "id": "t142", + "source": "SIRT3", + "target": "SOD2", + "sign": true + }, + { + "id": "t143", + "source": "Complex_space_1_complex", + "target": "NAD+_simple_molecule", + "sign": true + }, + { + "id": "t144", + "source": "NADH_simple_molecule", + "target": "NAD+_simple_molecule", + "sign": true + }, + { + "id": "t145", + "source": "O2_simple_molecule", + "target": "O2-_simple_molecule", + "sign": true + }, + { + "id": "t146", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "target": "O2-_simple_molecule", + "sign": true + }, + { + "id": "t147", + "source": "H+_ion_mitochondrial matrix", + "target": "O2-_simple_molecule", + "sign": true + }, + { + "id": "t148", + "source": "complex_space_3_complex", + "target": "O2-_simple_molecule", + "sign": true + }, + { + "id": "t149", + "source": "CYCS_mitochondrial matrix", + "target": "O2-_simple_molecule", + "sign": true + }, + { + "id": "t150", + "source": "Nsp7", + "target": "Nsp7", + "sign": false + }, + { + "id": "t151", + "source": "Nsp4_cell", + "target": "Nsp4_mitochondrion", + "sign": true + }, + { + "id": "t152", + "source": "TOM_space_complex_complex_mitochondrion", + "target": "Nsp4_mitochondrion", + "sign": true + }, + { + "id": "t153", + "source": "O2_simple_molecule", + "target": "CYCS_mitochondrial matrix", + "sign": true + }, + { + "id": "t154", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "target": "CYCS_mitochondrial matrix", + "sign": true + }, + { + "id": "t155", + "source": "complex_space_3_complex", + "target": "CYCS_mitochondrial matrix", + "sign": true + }, + { + "id": "t156", + "source": "H+_ion_mitochondrial matrix", "target": "CYCS_mitochondrial matrix", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json index 68f520266..0cf6529d1 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json @@ -323,114 +323,222 @@ "edges": [ { "id": "t1", - "source": "BRD2", + "source": "BRD4", "target": "histone_complex_nucleus", "sign": true }, { "id": "t2", - "source": "H2A", + "source": "BRD2", "target": "histone_complex_nucleus", "sign": true }, { "id": "t3", + "source": "H2BC21", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t4", + "source": "H4C14", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t5", + "source": "H4C9", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t6", + "source": "H3C15", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t7", + "source": "H4-16", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t8", + "source": "H4C1", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t9", + "source": "H3C1", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t10", + "source": "H2A", + "target": "histone_complex_nucleus", + "sign": true + }, + { + "id": "t11", "source": "CRB3", "target": "CRB3:PALS1:PATJ complex_complex", "sign": true }, { - "id": "t4", + "id": "t12", + "source": "MPP5", + "target": "CRB3:PALS1:PATJ complex_complex", + "sign": true + }, + { + "id": "t13", + "source": "PATJ", + "target": "CRB3:PALS1:PATJ complex_complex", + "sign": true + }, + { + "id": "t14", "source": "E_cell", "target": "ASIC1 trimer:H+:STOML3_complex", "sign": true }, { - "id": "t5", + "id": "t15", + "source": "ASIC1", + "target": "ASIC1 trimer:H+:STOML3_complex", + "sign": true + }, + { + "id": "t16", + "source": "STOML3", + "target": "ASIC1 trimer:H+:STOML3_complex", + "sign": true + }, + { + "id": "t17", "source": "E_cell", "target": "E_cell", "sign": false }, { - "id": "t6", + "id": "t18", "source": "E_cell", "target": "E-PALS1_complex", "sign": true }, { - "id": "t7", + "id": "t19", + "source": "MPP5", + "target": "E-PALS1_complex", + "sign": true + }, + { + "id": "t20", + "source": "CDK9", + "target": "P-TEFb_complex", + "sign": true + }, + { + "id": "t21", "source": "CCNT1", "target": "P-TEFb_complex", "sign": true }, { - "id": "t8", + "id": "t22", "source": "BRD4", "target": "CDK9", "sign": true }, { - "id": "t9", + "id": "t23", "source": "BRD4", "target": "CCNT1", "sign": true }, { - "id": "t10", + "id": "t24", "source": "E_nucleus", "target": "BRD4", "sign": true }, { - "id": "t11", + "id": "t25", "source": "BRD2", "target": "TBP", "sign": true }, { - "id": "t12", + "id": "t26", + "source": "JQ-1_simple_molecule", + "target": "BRD2", + "sign": true + }, + { + "id": "t27", "source": "E_nucleus", "target": "BRD2", "sign": true }, { - "id": "t13", + "id": "t28", "source": "H+_ion", "target": "ASIC1", "sign": true }, { - "id": "t14", + "id": "t29", "source": "ATP1A:ATP1B:FXYDs_complex", "target": "K+_ion", "sign": true }, { - "id": "t15", + "id": "t30", "source": "ATP1A:ATP1B:FXYDs_complex", "target": "Na+_ion", "sign": true }, { - "id": "t16", + "id": "t31", + "source": "ATP1A:ATP1B:FXYDs_complex", + "target": "Activity of sodium channels_phenotype", + "sign": true + }, + { + "id": "t32", "source": "ASIC1 trimer:H+:STOML3_complex", "target": "Activity of sodium channels_phenotype", "sign": true }, { - "id": "t17", + "id": "t33", + "source": "STOML3", + "target": "Activity of sodium channels_phenotype", + "sign": true + }, + { + "id": "t34", "source": "CRB3:PALS1:PATJ complex_complex", "target": "Maintenance of tight junction_phenotype", "sign": true }, { - "id": "t18", + "id": "t35", + "source": "E-PALS1_complex", + "target": "Maintenance of tight junction_phenotype", + "sign": true + }, + { + "id": "t36", "source": "P-TEFb_complex", "target": "RNA Polymerase II-dependent Transcription _phenotype", "sign": true }, { - "id": "t19", + "id": "t37", "source": "histone_complex_nucleus", "target": "Chromatin organization_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json index 0c98a9b1f..3f4f7cb4c 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json @@ -1709,585 +1709,1425 @@ }, { "id": "t2", - "source": "BACH1", - "target": "BACH1/Maf_complex", + "source": "NRF2_phosphorylated_nucleus", + "target": "Nrf2/Maf_complex", "sign": true }, { "id": "t3", - "source": "E2_ubiquitinated", - "target": "Ubiquitin Ligase Complex_complex_cell", + "source": "MAF", + "target": "BACH1/Maf_complex", "sign": true }, { "id": "t4", - "source": "Ubiquitin Ligase Complex_complex_cell", - "target": "Ubiquitin Ligase Complex_complex_cell", + "source": "BACH1", + "target": "BACH1/Maf_complex", "sign": true }, { "id": "t5", - "source": "Dimethly fumarate_drug", - "target": "NRF2:KEAP1_complex", + "source": "Ubiquitin Ligase Complex_complex_cell", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t6", - "source": "CUL3:RBX1_complex", - "target": "Neddylated CUL3:RBX1_complex", + "source": "E2_ubiquitinated", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t7", - "source": "SLC40A1_rna", - "target": "SLC40A1:CP:Cu2+_complex", + "source": "Ubiquitin Ligase Complex_complex_cell", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t8", - "source": "CAND1", - "target": "Ubiquitin Ligase Complex_complex_cell", + "source": "NRF2_empty", + "target": "NRF2:KEAP1_complex", "sign": true }, { "id": "t9", - "source": "Fe3+_ion_default_compartment", - "target": "holoTF_complex", + "source": "KEAP1", + "target": "NRF2:KEAP1_complex", "sign": true }, { "id": "t10", - "source": "TFRC", - "target": "TFRC:holoTF_complex_cell", + "source": "Dimethly fumarate_drug", + "target": "NRF2:KEAP1_complex", "sign": true }, { "id": "t11", - "source": "TFRC:holoTF_complex_cell", - "target": "TFRC:holoTF_complex_endosome", + "source": "CUL3:RBX1_complex", + "target": "Neddylated CUL3:RBX1_complex", "sign": true }, { "id": "t12", - "source": "TFRC:holoTF_complex_endosome", - "target": "TFRC:TF_complex_endosome", + "source": "SLC40A1_rna", + "target": "SLC40A1:CP:Cu2+_complex", "sign": true }, { "id": "t13", - "source": "TFRC:TF_complex_endosome", - "target": "TFRC:TF_complex_cell", + "source": "Neddylated CUL3:RBX1_complex", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t14", - "source": "NLRP3_cell", - "target": "TXNIP:NLRP3_complex", + "source": "CAND1", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t15", - "source": "NLRP3_cell", - "target": "NLRP3:SUGT1:HSP90_complex", + "source": "NRF2:KEAP1_complex", + "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t16", - "source": "NLRP3:SUGT1:HSP90_complex", - "target": "SUGT1:HSP90AB1_complex", + "source": "Fe3+_ion_default_compartment", + "target": "holoTF_complex", "sign": true }, { "id": "t17", - "source": "BLVRA_rna", - "target": "BLVRA:Zn2+_complex", + "source": "Transferrin", + "target": "holoTF_complex", "sign": true }, { "id": "t18", - "source": "TXNIP", - "target": "Thioredoxin:TXNIP_complex", + "source": "TFRC", + "target": "TFRC:holoTF_complex_cell", "sign": true }, { "id": "t19", - "source": "PSTPIP1", - "target": "PSTPIP1 trimer:Pyrin trimer_complex", + "source": "holoTF_complex", + "target": "TFRC:holoTF_complex_cell", "sign": true }, { "id": "t20", - "source": "ASC", - "target": "NLRP3 oligomer:ASC_complex", + "source": "TFRC:holoTF_complex_cell", + "target": "TFRC:holoTF_complex_endosome", "sign": true }, { "id": "t21", - "source": "ASC", - "target": "Pyrin trimer:ASC_complex", + "source": "TFRC:holoTF_complex_endosome", + "target": "TFRC:TF_complex_endosome", "sign": true }, { "id": "t22", - "source": "CASP1_cell", - "target": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "TFRC:TF_complex_endosome", + "target": "TFRC:TF_complex_cell", "sign": true }, { "id": "t23", - "source": "FTH1_rna", - "target": "Ferritin_complex", + "source": "TXNIP", + "target": "TXNIP:NLRP3_complex", "sign": true }, { "id": "t24", - "source": "ALB", - "target": "ALB/BIL_complex", + "source": "NLRP3_cell", + "target": "TXNIP:NLRP3_complex", "sign": true }, { "id": "t25", - "source": "CASP1(120-197):CASP1(317-404)_complex", - "target": "Caspase-1 Tetramer_complex", + "source": "SUGT1:HSP90AB1_complex", + "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { "id": "t26", - "source": "CASP1_cell", - "target": "CASP1(120-197):CASP1(317-404)_complex", + "source": "NLRP3_cell", + "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { "id": "t27", - "source": "FLVCR1-2", - "target": "Heme_simple_molecule_cell", + "source": "NLRP3:SUGT1:HSP90_complex", + "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t28", - "source": "Heme_simple_molecule_cell", - "target": "Biliverdin_simple_molecule", + "source": "BLVRA_rna", + "target": "BLVRA:Zn2+_complex", "sign": true }, { "id": "t29", - "source": "FECH", - "target": "Heme_simple_molecule_mitochondrial matrix", + "source": "TXN_cell", + "target": "Thioredoxin:TXNIP_complex", "sign": true }, { "id": "t30", - "source": "ALAD:Zn2+_complex", - "target": "H2O_simple_molecule_cell", + "source": "TXNIP", + "target": "Thioredoxin:TXNIP_complex", "sign": true }, { "id": "t31", - "source": "BLVRA:Zn2+_complex", - "target": "NADP+_simple_molecule", + "source": "PSTPIP1", + "target": "PSTPIP1 trimer:Pyrin trimer_complex", "sign": true }, { "id": "t32", - "source": "Fe2+_ion_default_compartment", - "target": "Fe2+_ion_cell", + "source": "Pyrin trimer_complex", + "target": "PSTPIP1 trimer:Pyrin trimer_complex", "sign": true }, { "id": "t33", - "source": "HMOX1_rna", - "target": "HMOX1_cell", + "source": "CTSG", + "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t34", - "source": "Heme_simple_molecule_cell", - "target": "CO_simple_molecule", + "source": "NLRP3_cell_active", + "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t35", - "source": "BLVRA:Zn2+_complex", - "target": "Bilirubin_simple_molecule_cell", + "source": "ASC", + "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t36", - "source": "BLVRB_rna", - "target": "BLVRB", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t37", - "source": "ABCC1", - "target": "Bilirubin_simple_molecule_default_compartment", + "source": "ASC", + "target": "Pyrin trimer:ASC_complex", "sign": true }, { "id": "t38", - "source": "ORF9c", - "target": "ABCC1", + "source": "Pyrin trimer_complex", + "target": "Pyrin trimer:ASC_complex", "sign": true }, { "id": "t39", - "source": "NRF2_phosphorylated_cell", - "target": "NRF2_phosphorylated_nucleus", + "source": "NLRP3 oligomer:ASC_complex", + "target": "NLRP3 oligomer:ASC:Caspase1_complex", "sign": true }, { "id": "t40", - "source": "miRNA-155_rna", - "target": "miRNA-155_rna", - "sign": false + "source": "CASP1_cell", + "target": "NLRP3 oligomer:ASC:Caspase1_complex", + "sign": true }, { "id": "t41", - "source": "BACH1/Maf_complex", - "target": "HMOX1_rna", + "source": "FTH1_rna", + "target": "Ferritin_complex", "sign": true }, { "id": "t42", - "source": "FECH_rna", - "target": "FECH", + "source": "FTL_rna", + "target": "Ferritin_complex", "sign": true }, { "id": "t43", - "source": "PRIN9_simple_molecule_mitochondrion", - "target": "PRIN9_simple_molecule_mitochondrial matrix", + "source": "Bilirubin_simple_molecule_default_compartment", + "target": "ALB/BIL_complex", "sign": true }, { "id": "t44", - "source": "FECH", - "target": "H+_ion_mitochondrial matrix", + "source": "ALB", + "target": "ALB/BIL_complex", "sign": true }, { "id": "t45", - "source": "ALAS1:ALAS2_complex", - "target": "dALA_simple_molecule_mitochondrial matrix", + "source": "CASP1(120-197):CASP1(317-404)_complex", + "target": "Caspase-1 Tetramer_complex", "sign": true }, { "id": "t46", - "source": "ALAS1:ALAS2_complex", - "target": "CO2_simple_molecule_mitochondrial matrix", + "source": "CASP1_cell", + "target": "CASP1(120-197):CASP1(317-404)_complex", "sign": true }, { "id": "t47", - "source": "ALAS1:ALAS2_complex", - "target": "CoA-SH_simple_molecule", + "source": "Heme_simple_molecule_mitochondrial matrix", + "target": "Heme_simple_molecule_cell", "sign": true }, { "id": "t48", - "source": "dALA_simple_molecule_mitochondrial matrix", - "target": "dALA_simple_molecule_cell", + "source": "FLVCR1-2", + "target": "Heme_simple_molecule_cell", "sign": true }, { "id": "t49", - "source": "ALAD:Zn2+_complex", - "target": "PBG_simple_molecule", + "source": "Heme_simple_molecule_cell", + "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t50", - "source": "ALAD:Zn2+_complex", - "target": "H+_ion_cell", + "source": "HMOX1_cell_active", + "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t51", - "source": "H2O_simple_molecule_cell", - "target": "HMBL_simple_molecule", + "source": "O2_simple_molecule_cell", + "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t52", - "source": "H2O_simple_molecule_cell", - "target": "NH4+_ion", + "source": "NADPH_simple_molecule", + "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t53", - "source": "HMBL_simple_molecule", - "target": "URO3_simple_molecule", + "source": "Fe2+_ion_mitochondrial matrix", + "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t54", - "source": "URO3_simple_molecule", - "target": "COPRO3_simple_molecule_cell", + "source": "FECH", + "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t55", - "source": "COPRO3_simple_molecule_cell", - "target": "COPRO3_simple_molecule_mitochondrion", + "source": "PRIN9_simple_molecule_mitochondrial matrix", + "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t56", - "source": "COPRO3_simple_molecule_mitochondrion", - "target": "PPGEN9_simple_molecule", + "source": "Pb2+_ion", + "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t57", - "source": "O2_simple_molecule_mitochondrion", - "target": "PRIN9_simple_molecule_mitochondrion", + "source": "Heme_simple_molecule_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t58", - "source": "COPRO3_simple_molecule_mitochondrion", - "target": "CO2_simple_molecule_mitochondrion", + "source": "O2_simple_molecule_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t59", - "source": "COPRO3_simple_molecule_mitochondrion", - "target": "H2O2_simple_molecule", + "source": "NADPH_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t60", - "source": "Lipid Peroxide_simple_molecule", - "target": "Ferroptosis_phenotype", + "source": "HMOX1_cell_active", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t61", - "source": "Poly-unsaturated fatty acid_simple_molecule", - "target": "Lipid Peroxide_simple_molecule", + "source": "dALA_simple_molecule_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t62", - "source": "CYBRD1:Heme_complex", - "target": "Fe2+_ion_default_compartment", + "source": "ALAD:Zn2+_complex", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t63", - "source": "Fe2+_ion_default_compartment", - "target": "Fe3+_ion_default_compartment", + "source": "Heme_simple_molecule_cell", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t64", - "source": "NRF2_phosphorylated_nucleus", - "target": "SLC40A1_rna", + "source": "BLVRB", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t65", - "source": "NRF2_phosphorylated_nucleus", - "target": "FTH1_rna", + "source": "O2_simple_molecule_cell", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t66", - "source": "NRF2_phosphorylated_nucleus", - "target": "FTL_rna", + "source": "NADPH_simple_molecule", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t67", - "source": "NRF2_phosphorylated_nucleus", - "target": "FECH_rna", + "source": "HMOX1_cell_active", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t68", - "source": "NRF2_phosphorylated_nucleus", - "target": "BLVRA_rna", + "source": "BLVRA:Zn2+_complex", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t69", - "source": "NRF2_phosphorylated_nucleus", - "target": "BLVRB_rna", + "source": "Biliverdin_simple_molecule", + "target": "NADP+_simple_molecule", "sign": true }, { "id": "t70", - "source": "Fe2+_ion_cell", - "target": "Fe(3+)O(OH)_simple_molecule", + "source": "Heme_simple_molecule_cell", + "target": "Fe2+_ion_cell", "sign": true }, { "id": "t71", - "source": "Fe2+_ion_default_compartment", - "target": "H2O_simple_molecule_default_compartment", + "source": "O2_simple_molecule_cell", + "target": "Fe2+_ion_cell", "sign": true }, { "id": "t72", - "source": "CO_simple_molecule", - "target": "Reactive Oxygen Species_simple_molecule", + "source": "NADPH_simple_molecule", + "target": "Fe2+_ion_cell", "sign": true }, { "id": "t73", - "source": "GPX4", - "target": "Lipid alcohol_simple_molecule", + "source": "HMOX1_cell_active", + "target": "Fe2+_ion_cell", + "sign": true + }, + { + "id": "t74", + "source": "MCOLN1", + "target": "Fe2+_ion_cell", + "sign": true + }, + { + "id": "t75", + "source": "SLC11A2", + "target": "Fe2+_ion_cell", + "sign": true + }, + { + "id": "t76", + "source": "Fe2+_ion_default_compartment", + "target": "Fe2+_ion_cell", + "sign": true + }, + { + "id": "t77", + "source": "Fe2+_ion_endosome", + "target": "Fe2+_ion_cell", + "sign": true + }, + { + "id": "t78", + "source": "HMOX1_rna", + "target": "HMOX1_cell", + "sign": true + }, + { + "id": "t79", + "source": "Heme_simple_molecule_cell", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "HMOX1_cell_active", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t81", + "source": "O2_simple_molecule_cell", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t82", + "source": "NADPH_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t83", + "source": "NADPH_simple_molecule", + "target": "Bilirubin_simple_molecule_cell", + "sign": true + }, + { + "id": "t84", + "source": "Biliverdin_simple_molecule", + "target": "Bilirubin_simple_molecule_cell", + "sign": true + }, + { + "id": "t85", + "source": "BLVRA:Zn2+_complex", + "target": "Bilirubin_simple_molecule_cell", + "sign": true + }, + { + "id": "t86", + "source": "BLVRB", + "target": "Bilirubin_simple_molecule_cell", + "sign": true + }, + { + "id": "t87", + "source": "BLVRB_rna", + "target": "BLVRB", + "sign": true + }, + { + "id": "t88", + "source": "Bilirubin_simple_molecule_cell", + "target": "Bilirubin_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t89", + "source": "ABCC1", + "target": "Bilirubin_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t90", + "source": "ORF9c", + "target": "ABCC1", + "sign": true + }, + { + "id": "t91", + "source": "NRF2_phosphorylated_cell", + "target": "NRF2_phosphorylated_nucleus", + "sign": true + }, + { + "id": "t92", + "source": "miRNA-155_rna", + "target": "miRNA-155_rna", + "sign": false + }, + { + "id": "t93", + "source": "BACH1/Maf_complex", + "target": "HMOX1_rna", + "sign": true + }, + { + "id": "t94", + "source": "Nrf2/Maf_complex", + "target": "HMOX1_rna", + "sign": true + }, + { + "id": "t95", + "source": "FECH_rna", + "target": "FECH", + "sign": true + }, + { + "id": "t96", + "source": "PRIN9_simple_molecule_mitochondrion", + "target": "PRIN9_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t97", + "source": "Fe2+_ion_mitochondrial matrix", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t98", + "source": "FECH", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t99", + "source": "PRIN9_simple_molecule_mitochondrial matrix", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t100", + "source": "Pb2+_ion", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t101", + "source": "H+_ion_mitochondrial matrix", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t102", + "source": "Panhematin_drug", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t103", + "source": "Gly_simple_molecule", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t104", + "source": "ALAS1:ALAS2_complex", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t105", + "source": "Heme_simple_molecule_mitochondrial matrix", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t106", + "source": "SUCC-CoA_simple_molecule", + "target": "dALA_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t107", + "source": "H+_ion_mitochondrial matrix", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t108", + "source": "Panhematin_drug", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t109", + "source": "Gly_simple_molecule", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t110", + "source": "ALAS1:ALAS2_complex", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t111", + "source": "Heme_simple_molecule_mitochondrial matrix", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t112", + "source": "SUCC-CoA_simple_molecule", + "target": "CO2_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t113", + "source": "H+_ion_mitochondrial matrix", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t114", + "source": "Panhematin_drug", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t115", + "source": "Gly_simple_molecule", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t116", + "source": "ALAS1:ALAS2_complex", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t117", + "source": "Heme_simple_molecule_mitochondrial matrix", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t118", + "source": "SUCC-CoA_simple_molecule", + "target": "CoA-SH_simple_molecule", + "sign": true + }, + { + "id": "t119", + "source": "dALA_simple_molecule_mitochondrial matrix", + "target": "dALA_simple_molecule_cell", + "sign": true + }, + { + "id": "t120", + "source": "dALA_simple_molecule_cell", + "target": "PBG_simple_molecule", + "sign": true + }, + { + "id": "t121", + "source": "ALAD:Zn2+_complex", + "target": "PBG_simple_molecule", + "sign": true + }, + { + "id": "t122", + "source": "dALA_simple_molecule_cell", + "target": "H+_ion_cell", + "sign": true + }, + { + "id": "t123", + "source": "ALAD:Zn2+_complex", + "target": "H+_ion_cell", + "sign": true + }, + { + "id": "t124", + "source": "PBG_simple_molecule", + "target": "HMBL_simple_molecule", + "sign": true + }, + { + "id": "t125", + "source": "H2O_simple_molecule_cell", + "target": "HMBL_simple_molecule", + "sign": true + }, + { + "id": "t126", + "source": "HMBS:DIPY_complex", + "target": "HMBL_simple_molecule", + "sign": true + }, + { + "id": "t127", + "source": "PBG_simple_molecule", + "target": "NH4+_ion", + "sign": true + }, + { + "id": "t128", + "source": "H2O_simple_molecule_cell", + "target": "NH4+_ion", + "sign": true + }, + { + "id": "t129", + "source": "HMBS:DIPY_complex", + "target": "NH4+_ion", + "sign": true + }, + { + "id": "t130", + "source": "UROS", + "target": "URO3_simple_molecule", + "sign": true + }, + { + "id": "t131", + "source": "HMBL_simple_molecule", + "target": "URO3_simple_molecule", + "sign": true + }, + { + "id": "t132", + "source": "UROD", + "target": "COPRO3_simple_molecule_cell", + "sign": true + }, + { + "id": "t133", + "source": "URO3_simple_molecule", + "target": "COPRO3_simple_molecule_cell", + "sign": true + }, + { + "id": "t134", + "source": "COPRO3_simple_molecule_cell", + "target": "COPRO3_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t135", + "source": "O2_simple_molecule_mitochondrion", + "target": "PPGEN9_simple_molecule", + "sign": true + }, + { + "id": "t136", + "source": "CPOX", + "target": "PPGEN9_simple_molecule", + "sign": true + }, + { + "id": "t137", + "source": "COPRO3_simple_molecule_mitochondrion", + "target": "PPGEN9_simple_molecule", + "sign": true + }, + { + "id": "t138", + "source": "PPGEN9_simple_molecule", + "target": "PRIN9_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t139", + "source": "O2_simple_molecule_mitochondrion", + "target": "PRIN9_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t140", + "source": "PPO:FAD_complex", + "target": "PRIN9_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t141", + "source": "O2_simple_molecule_mitochondrion", + "target": "CO2_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t142", + "source": "CPOX", + "target": "CO2_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t143", + "source": "COPRO3_simple_molecule_mitochondrion", + "target": "CO2_simple_molecule_mitochondrion", + "sign": true + }, + { + "id": "t144", + "source": "PPGEN9_simple_molecule", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t145", + "source": "O2_simple_molecule_mitochondrion", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t146", + "source": "PPO:FAD_complex", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t147", + "source": "COPRO3_simple_molecule_mitochondrion", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t148", + "source": "CPOX", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t149", + "source": "Lipid Peroxide_simple_molecule", + "target": "Ferroptosis_phenotype", + "sign": true + }, + { + "id": "t150", + "source": "Reactive Oxygen Species_simple_molecule", + "target": "Lipid Peroxide_simple_molecule", + "sign": true + }, + { + "id": "t151", + "source": "Poly-unsaturated fatty acid_simple_molecule", + "target": "Lipid Peroxide_simple_molecule", + "sign": true + }, + { + "id": "t152", + "source": "e-_ion_default_compartment", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t153", + "source": "Fe3+_ion_default_compartment", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t154", + "source": "SLC40A1:HEPH:Cu2+_complex", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t155", + "source": "CYBRD1:Heme_complex", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t156", + "source": "Fe2+_ion_cell", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t157", + "source": "SLC40A1:CP:Cu2+_complex", + "target": "Fe2+_ion_default_compartment", + "sign": true + }, + { + "id": "t158", + "source": "H+_ion_default_compartment", + "target": "Fe3+_ion_default_compartment", + "sign": true + }, + { + "id": "t159", + "source": "SLC40A1:HEPH:Cu2+_complex", + "target": "Fe3+_ion_default_compartment", + "sign": true + }, + { + "id": "t160", + "source": "Fe2+_ion_default_compartment", + "target": "Fe3+_ion_default_compartment", + "sign": true + }, + { + "id": "t161", + "source": "O2_simple_molecule_default_compartment", + "target": "Fe3+_ion_default_compartment", "sign": true }, { - "id": "t74", + "id": "t162", + "source": "SLC40A1:CP:Cu2+_complex", + "target": "Fe3+_ion_default_compartment", + "sign": true + }, + { + "id": "t163", + "source": "NRF2_phosphorylated_nucleus", + "target": "SLC40A1_rna", + "sign": true + }, + { + "id": "t164", + "source": "NRF2_phosphorylated_nucleus", + "target": "FTH1_rna", + "sign": true + }, + { + "id": "t165", + "source": "NRF2_phosphorylated_nucleus", + "target": "FTL_rna", + "sign": true + }, + { + "id": "t166", + "source": "NRF2_phosphorylated_nucleus", + "target": "FECH_rna", + "sign": true + }, + { + "id": "t167", + "source": "NRF2_phosphorylated_nucleus", + "target": "BLVRA_rna", + "sign": true + }, + { + "id": "t168", + "source": "NRF2_phosphorylated_nucleus", + "target": "BLVRB_rna", + "sign": true + }, + { + "id": "t169", + "source": "Fe2+_ion_cell", + "target": "Fe(3+)O(OH)_simple_molecule", + "sign": true + }, + { + "id": "t170", + "source": "Ferritin_complex", + "target": "Fe(3+)O(OH)_simple_molecule", + "sign": true + }, + { + "id": "t171", + "source": "O2_simple_molecule_cell", + "target": "Fe(3+)O(OH)_simple_molecule", + "sign": true + }, + { + "id": "t172", + "source": "H+_ion_cell", + "target": "Fe(3+)O(OH)_simple_molecule", + "sign": true + }, + { + "id": "t173", + "source": "H+_ion_default_compartment", + "target": "H2O_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t174", + "source": "SLC40A1:HEPH:Cu2+_complex", + "target": "H2O_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t175", + "source": "Fe2+_ion_default_compartment", + "target": "H2O_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t176", + "source": "O2_simple_molecule_default_compartment", + "target": "H2O_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t177", + "source": "SLC40A1:CP:Cu2+_complex", + "target": "H2O_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t178", + "source": "Fe2+_ion_cell", + "target": "Reactive Oxygen Species_simple_molecule", + "sign": true + }, + { + "id": "t179", + "source": "CO_simple_molecule", + "target": "Reactive Oxygen Species_simple_molecule", + "sign": true + }, + { + "id": "t180", + "source": "Lipid Peroxide_simple_molecule", + "target": "Lipid alcohol_simple_molecule", + "sign": true + }, + { + "id": "t181", + "source": "GPX4", + "target": "Lipid alcohol_simple_molecule", + "sign": true + }, + { + "id": "t182", + "source": "ORF3a", + "target": "HMOX1_cell_active", + "sign": true + }, + { + "id": "t183", "source": "HMOX1_cell", "target": "HMOX1_cell_active", "sign": true }, { - "id": "t75", + "id": "t184", "source": "NRF2_empty", "target": "NRF2_phosphorylated_cell", "sign": true }, { - "id": "t76", + "id": "t185", + "source": "PKC", + "target": "NRF2_phosphorylated_cell", + "sign": true + }, + { + "id": "t186", + "source": "CK2", + "target": "NRF2_phosphorylated_cell", + "sign": true + }, + { + "id": "t187", + "source": "Heme_simple_molecule_cell", + "target": "Heme_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t188", + "source": "ATP_simple_molecule", + "target": "Heme_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t189", "source": "ABCG2", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { - "id": "t77", + "id": "t190", + "source": "H2O_simple_molecule_cell", + "target": "Heme_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t191", + "source": "FLVCR1-1", + "target": "Heme_simple_molecule_default_compartment", + "sign": true + }, + { + "id": "t192", + "source": "Heme_simple_molecule_cell", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t193", "source": "ABCG2", "target": "ADP_simple_molecule", "sign": true }, { - "id": "t78", + "id": "t194", + "source": "H2O_simple_molecule_cell", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t195", + "source": "ATP_simple_molecule", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t196", + "source": "Heme_simple_molecule_cell", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t197", "source": "ABCG2", "target": "Pi_simple_molecule", "sign": true }, { - "id": "t79", + "id": "t198", + "source": "H2O_simple_molecule_cell", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t199", + "source": "ATP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t200", "source": "TFRC:TF_complex_cell", "target": "Transferrin", "sign": true }, { - "id": "t80", + "id": "t201", "source": "TFRC:TF_complex_cell", "target": "TFRC", "sign": true }, { - "id": "t81", + "id": "t202", "source": "TFRC:holoTF_complex_endosome", "target": "Fe3+_ion_endosome", "sign": true }, { - "id": "t82", + "id": "t203", "source": "Fe3+_ion_endosome", "target": "Fe2+_ion_endosome", "sign": true }, { - "id": "t83", + "id": "t204", + "source": "e-_ion_endosome", + "target": "Fe2+_ion_endosome", + "sign": true + }, + { + "id": "t205", + "source": "STEAP3", + "target": "Fe2+_ion_endosome", + "sign": true + }, + { + "id": "t206", "source": "Ubiquitin Ligase Complex_complex_cell", "target": "NRF2_ubiquitinated", "sign": true }, { - "id": "t84", + "id": "t207", "source": "NLRP3:SUGT1:HSP90_complex", "target": "NLRP3_cell", "sign": true }, { - "id": "t85", + "id": "t208", + "source": "NLRP3_rna", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t209", + "source": "Thioredoxin:TXNIP_complex", + "target": "TXNIP", + "sign": true + }, + { + "id": "t210", "source": "Reactive Oxygen Species_simple_molecule", "target": "TXNIP", "sign": true }, { - "id": "t86", + "id": "t211", + "source": "Thioredoxin:TXNIP_complex", + "target": "TXN_cell", + "sign": true + }, + { + "id": "t212", "source": "Reactive Oxygen Species_simple_molecule", "target": "TXN_cell", "sign": true }, { - "id": "t87", + "id": "t213", "source": "Nf-KB Complex_complex", "target": "NLRP3_rna", "sign": true }, { - "id": "t88", + "id": "t214", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t89", + "id": "t215", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t216", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t90", + "id": "t217", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t218", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t91", + "id": "t219", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t220", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t92", + "id": "t221", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t222", "source": "Caspase-1 Tetramer_complex", "target": "proIL-1B_cell", "sign": true }, { - "id": "t93", + "id": "t223", "source": "Caspase-1 Tetramer_complex", "target": "proIL-18_cell", "sign": true }, { - "id": "t94", + "id": "t224", + "source": "proIL-1B_cell", + "target": "IL-1B_cell", + "sign": true + }, + { + "id": "t225", "source": "Caspase-1 Tetramer_complex", "target": "IL-1B_cell", "sign": true }, { - "id": "t95", + "id": "t226", + "source": "proIL-18_cell", + "target": "IL-18_cell", + "sign": true + }, + { + "id": "t227", "source": "Caspase-1 Tetramer_complex", "target": "IL-18_cell", "sign": true }, { - "id": "t96", + "id": "t228", "source": "IL-1B_cell", "target": "IL-1B_default_compartment", "sign": true }, { - "id": "t97", + "id": "t229", "source": "IL-18_cell", "target": "IL-18_default_compartment", "sign": true }, { - "id": "t98", + "id": "t230", + "source": "NLRP3 Elicitor Proteins", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t231", + "source": "SARS Orf3a", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t232", + "source": "NLRP3_cell", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t233", + "source": "SARS E", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t234", + "source": "PAMPs_phenotype", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t235", + "source": "Reactive Oxygen Species_simple_molecule", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t236", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "target": "NLRP3_cell_active", + "sign": true + }, + { + "id": "t237", "source": "DAMPs_phenotype", "target": "NLRP3_cell_active", "sign": true + }, + { + "id": "t238", + "source": "TXNIP:NLRP3_complex", + "target": "NLRP3_cell_active", + "sign": true } ], "parameters": [] diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json index 5680cdc85..f0e732dc7 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json @@ -424,174 +424,288 @@ }, { "id": "t2", - "source": "IRF9", + "source": "ISGF3 precursor_complex", "target": "ISGF3_complex", "sign": true }, { "id": "t3", + "source": "IRF9", + "target": "ISGF3_complex", + "sign": true + }, + { + "id": "t4", "source": "SOCS3", "target": "receptor complex_complex_cell", "sign": true }, { - "id": "t4", + "id": "t5", "source": "ISGF3 precursor_complex", "target": "Inhibited ISGF3 precursor_complex", "sign": true }, { - "id": "t5", + "id": "t6", + "source": "STAT3", + "target": "Inhibited ISGF3 precursor_complex", + "sign": true + }, + { + "id": "t7", "source": "IRF3_phosphorylated", "target": "p38-NFkB_complex", "sign": true }, { - "id": "t6", + "id": "t8", + "source": "ribosomal 40S subunit_complex", + "target": "inhibited ribosomal 40S SU_complex", + "sign": true + }, + { + "id": "t9", "source": "Nsp1", "target": "inhibited ribosomal 40S SU_complex", "sign": true }, { - "id": "t7", + "id": "t10", "source": "80S ribosome_complex", "target": "inhibited 80S ribosome_complex", "sign": true }, { - "id": "t8", + "id": "t11", + "source": "Nsp1", + "target": "inhibited 80S ribosome_complex", + "sign": true + }, + { + "id": "t12", + "source": "RIG-I-mitoMAVS_complex", + "target": "RIG-I-MAVS_complex_mitochondrion", + "sign": true + }, + { + "id": "t13", "source": "IKK-TBK1_complex", "target": "RIG-I-MAVS_complex_mitochondrion", "sign": true }, { - "id": "t9", + "id": "t14", + "source": "RIG-I:dsRNA_complex_mitochondrion", + "target": "RIG-I-mitoMAVS_complex", + "sign": true + }, + { + "id": "t15", "source": "MAVS", "target": "RIG-I-mitoMAVS_complex", "sign": true }, { - "id": "t10", + "id": "t16", + "source": "STAT2_phosphorylated", + "target": "ISGF3 precursor_complex", + "sign": true + }, + { + "id": "t17", "source": "STAT1_phosphorylated", "target": "ISGF3 precursor_complex", "sign": true }, { - "id": "t11", + "id": "t18", "source": "dsRNA_rna", "target": "RIG-I-MAVS_complex_peroxisome", "sign": true }, { - "id": "t12", + "id": "t19", "source": "ribosomal 40S subunit_complex", "target": "80S ribosome_complex", "sign": true }, { - "id": "t13", + "id": "t20", + "source": "ribosomal 60S subunit_complex", + "target": "80S ribosome_complex", + "sign": true + }, + { + "id": "t21", "source": "M", "target": "RIG-1 M-Protein_complex", "sign": true }, { - "id": "t14", + "id": "t22", + "source": "RIG-I", + "target": "RIG-1 M-Protein_complex", + "sign": true + }, + { + "id": "t23", + "source": "dsRNA_rna", + "target": "RIG-I:dsRNA_complex_mitochondrion", + "sign": true + }, + { + "id": "t24", + "source": "RIG-I", + "target": "RIG-I:dsRNA_complex_mitochondrion", + "sign": true + }, + { + "id": "t25", "source": "PLPro", "target": "RIG-I:dsRNA_complex_mitochondrion", "sign": true }, { - "id": "t15", + "id": "t26", "source": "Riplet:TRIM25_complex", "target": "RIG-I:dsRNA_complex_mitochondrion", "sign": true }, { - "id": "t16", + "id": "t27", "source": "80S ribosome_complex", "target": "IFNs_complex", "sign": true }, { - "id": "t17", + "id": "t28", + "source": "ISGs_rna", + "target": "IFNs_complex", + "sign": true + }, + { + "id": "t29", "source": "SOCS1", "target": "receptor complex_complex_cell", "sign": true }, { - "id": "t18", + "id": "t30", "source": "80S ribosome_complex", "target": "antiviral proteins_complex", "sign": true }, { - "id": "t19", + "id": "t31", + "source": "ISGs_rna", + "target": "antiviral proteins_complex", + "sign": true + }, + { + "id": "t32", "source": "IFN-III", "target": "Ifn lambda_complex", "sign": true }, { - "id": "t20", + "id": "t33", + "source": "receptor complex_complex_cell", + "target": "Ifn lambda_complex", + "sign": true + }, + { + "id": "t34", "source": "receptor complex_complex_cell", "target": "STAT1_phosphorylated", "sign": true }, { - "id": "t21", + "id": "t35", "source": "receptor complex_complex_cell", "target": "STAT2_phosphorylated", "sign": true }, { - "id": "t22", + "id": "t36", + "source": "ISGF3_complex", + "target": "ISGs_rna", + "sign": true + }, + { + "id": "t37", "source": "IFN-sensitive-response-element_gene", "target": "ISGs_rna", "sign": true }, { - "id": "t23", + "id": "t38", "source": "nsp14", "target": "viral RNA+N-methyl-Guanine_rna", "sign": true }, { - "id": "t24", + "id": "t39", + "source": "viral RNA_rna", + "target": "viral RNA+N-methyl-Guanine_rna", + "sign": true + }, + { + "id": "t40", + "source": "viral RNA+N-methyl-Guanine_rna", + "target": "5'cap-viral-RNA_rna", + "sign": true + }, + { + "id": "t41", "source": "nsp16", "target": "5'cap-viral-RNA_rna", "sign": true }, { - "id": "t25", + "id": "t42", + "source": "dsRNA_vesicle_rna", + "target": "dsRNA_rna", + "sign": true + }, + { + "id": "t43", "source": "RNA_rna", "target": "dsRNA_rna", "sign": true }, { - "id": "t26", + "id": "t44", "source": "RIG-I-MAVS_complex_mitochondrion", "target": "IRF3_phosphorylated", "sign": true }, { - "id": "t27", + "id": "t45", "source": "RIG-I-MAVS_complex_peroxisome", "target": "IRF1_phosphorylated", "sign": true }, { - "id": "t28", + "id": "t46", "source": "IRF1_phosphorylated", "target": "IFN-III_rna", "sign": true }, { - "id": "t29", + "id": "t47", + "source": "p38-NFkB_complex", + "target": "IFN-III_rna", + "sign": true + }, + { + "id": "t48", "source": "IFN-III_rna", "target": "IFN-III", "sign": true }, { - "id": "t30", + "id": "t49", "source": "dsRNA_rna", "target": "dsRNA_vesicle_rna", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json index 9f5b9900e..1d592bcd2 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json @@ -1253,402 +1253,1110 @@ }, { "id": "t2", - "source": "IRAK1/4", - "target": "TLR4_TRIF_TRAM_complex", + "source": "IFNAR_complex", + "target": "IFNA1_IFNAR_complex", "sign": true }, { "id": "t3", - "source": "IFNAR_complex", - "target": "IFNB1_IFNAR_complex", + "source": "IFNA1_extracellular space", + "target": "IFNA1_IFNAR_complex", "sign": true }, { "id": "t4", - "source": "IRF9", - "target": "STAT1/2_IRF9_complex", + "source": "TRIF", + "target": "TLR4_TRIF_TRAM_complex", "sign": true }, { "id": "t5", - "source": "Orf6", - "target": "ISRE_complex", + "source": "IRAK1/4", + "target": "TLR4_TRIF_TRAM_complex", "sign": true }, { "id": "t6", - "source": "IFNA1_IFNAR_complex", - "target": "JAK1_TYK2_complex", + "source": "IFNB1_extracellular space", + "target": "IFNB1_IFNAR_complex", "sign": true }, { "id": "t7", - "source": "E", - "target": "AP-1_complex_cell", + "source": "IFNAR_complex", + "target": "IFNB1_IFNAR_complex", "sign": true }, { "id": "t8", - "source": "IkB_p50_p65_complex_cell", - "target": "p50_p65_complex_cell", + "source": "IFNB1_extracellular space", + "target": "IFNB1_IFNAR_complex", "sign": true }, { "id": "t9", - "source": "EIF2AK", - "target": "OAS1_EIF2AK_complex", + "source": "JAK1_TYK2_complex", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t10", - "source": "IKBKE", - "target": "TBK1_IKBKE_complex", + "source": "TREML4", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t11", - "source": "MYD88", - "target": "MYD88_TRAM_complex", + "source": "STAT1_phosphorylated", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t12", - "source": "M", - "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", + "source": "IRF9", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t13", - "source": "TBK1_IKBKE_complex", - "target": "TRAF3_TBK1_IKBKE_complex_cell", + "source": "STAT2_phosphorylated", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t14", - "source": "STING1_ubiquitinated", - "target": "TRAF3_TBK1_IKBKE_complex_cell_active", + "source": "Nsp5", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t15", - "source": "DDX58_ubiquitinated", - "target": "RIG1_MDA5_complex", + "source": "Orf6", + "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t16", - "source": "E", - "target": "NLRP3_inflammasome_complex", + "source": "Orf6", + "target": "ISRE_complex", "sign": true }, { "id": "t17", - "source": "MAP3K7", - "target": "MAPK8/14_complex", + "source": "STAT1/2_IRF9_complex", + "target": "ISRE_complex", "sign": true }, { "id": "t18", - "source": "AP-1_complex_cell", - "target": "AP-1_complex_nucleus", + "source": "TYK2", + "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t19", - "source": "p50_p65_complex_cell", - "target": "p50_p65_complex_nucleus", + "source": "IFNB1_IFNAR_complex", + "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t20", - "source": "Viral dsRNA_rna_endosome", - "target": "TLR3_TRIF_complex", + "source": "IFNA1_IFNAR_complex", + "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t21", - "source": "RIP1", - "target": "TLR3_TRIF_RIPK1_complex", + "source": "JAK1", + "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t22", - "source": "TRAF6_ubiquitinated", - "target": "TAB1/2_TRAF6_TAK1_complex", + "source": "JUN", + "target": "AP-1_complex_cell", "sign": true }, { "id": "t23", - "source": "IKKa", - "target": "IKKa_IKKb_NEMO_complex", + "source": "FOS", + "target": "AP-1_complex_cell", "sign": true }, { "id": "t24", - "source": "IkB", - "target": "IkB_p50_p65_complex_cell", + "source": "E", + "target": "AP-1_complex_cell", "sign": true }, { "id": "t25", - "source": "IKKa_IKKb_NEMO_complex", - "target": "IkB_p50_p65_complex_cell", + "source": "MAPK8/14_complex", + "target": "AP-1_complex_cell", "sign": true }, { "id": "t26", - "source": "Orf6", - "target": "IRF3_homodimer_complex_nucleus", + "source": "IkB_p50_p65_complex_cell", + "target": "p50_p65_complex_cell", "sign": true }, { "id": "t27", - "source": "IRF3_phosphorylated", - "target": "IRF3_homodimer_complex_cell", + "source": "OAS1_cell_active", + "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t28", - "source": "IRF7_phosphorylated", - "target": "IRF7_homodimer_complex", + "source": "OAS2_cell_active", + "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t29", - "source": "GRL0617_drug", - "target": "ISG15_Nsp3_complex", + "source": "EIF2AK", + "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t30", - "source": "IFNB1_rna", - "target": "IFNB1_cell", + "source": "OAS3_cell_active", + "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t31", - "source": "IFNB1_cell", - "target": "IFNB1_extracellular space", + "source": "Azithromycin_drug", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t32", - "source": "IFNA1_rna", - "target": "IFNA1_cell", + "source": "Nsp3", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t33", - "source": "IFNA1_cell", - "target": "IFNA1_extracellular space", + "source": "TRAF3", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t34", - "source": "AP-1_complex_nucleus", - "target": "IFNB1_rna", + "source": "IKBKE", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t35", - "source": "AP-1_complex_nucleus", - "target": "IFNA1_rna", + "source": "NAP1", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t36", - "source": "ISRE_complex", - "target": "OAS1_rna", + "source": "TBK1", + "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t37", - "source": "ISRE_complex", - "target": "EIF2AK_rna", + "source": "TREML4", + "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t38", - "source": "Nsp15", - "target": "OAS1_cell_active", + "source": "TLR9", + "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t39", - "source": "EIF2AK_rna", - "target": "EIF2AK", + "source": "TLR7", + "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t40", - "source": "MYD88_TRAM_complex", - "target": "TRAF6_ubiquitinated", + "source": "MYD88", + "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t41", - "source": "IKBKE", - "target": "TBK1", + "source": "IRAK1/4", + "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t42", - "source": "M", - "target": "Nsp1", - "sign": false + "source": "Viral dsRNA_rna_endosome", + "target": "MYD88_TRAM_complex", + "sign": true }, { "id": "t43", - "source": "Nsp13", - "target": "Orf7a", - "sign": false + "source": "TANK", + "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", + "sign": true }, { "id": "t44", - "source": "ISRE_complex", - "target": "OAS2_rna", + "source": "MAVS", + "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t45", - "source": "Nsp15", - "target": "OAS2_cell_active", + "source": "M", + "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t46", - "source": "ISRE_complex", - "target": "OAS3_rna", + "source": "TLR3_TRIF_complex", + "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t47", - "source": "Nsp15", - "target": "OAS3_cell_active", + "source": "TRAF3_TBK1_IKBKE_complex_cell_active", + "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t48", - "source": "Nsp3", - "target": "ISG expression_antiviral response_phenotype", + "source": "TRAF3", + "target": "TRAF3_TBK1_IKBKE_complex_cell", "sign": true }, { "id": "t49", - "source": "MYD88_TRAM_complex", - "target": "TRAF3", + "source": "pp1ab", + "target": "TRAF3_TBK1_IKBKE_complex_cell", "sign": true }, { "id": "t50", - "source": "TRAF6_ubiquitinated", - "target": "MAP3K7", + "source": "TBK1_IKBKE_complex", + "target": "TRAF3_TBK1_IKBKE_complex_cell", "sign": true }, { "id": "t51", - "source": "Nsp3", - "target": "IKBKE", + "source": "TRAF3_TBK1_IKBKE_complex_cell", + "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t52", - "source": "MAVS", - "target": "IRF3_phosphorylated", + "source": "pp1ab", + "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t53", - "source": "Orf9b", - "target": "MAVS", + "source": "STING1_ubiquitinated", + "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t54", - "source": "Nsp15", - "target": "IFIH1", + "source": "Nsp10", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t55", - "source": "N", - "target": "DDX58_ubiquitinated", + "source": "Nsp15", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t56", - "source": "OAS3_rna", - "target": "OAS3_cell", + "source": "N", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t57", - "source": "OAS2_rna", - "target": "OAS2_cell", + "source": "Nsp14", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t58", - "source": "OAS1_rna", - "target": "OAS1_cell", + "source": "Nsp16", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t59", - "source": "MAVS", - "target": "STING1_ubiquitinated", + "source": "IFIH1", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t60", - "source": "IFNA1_extracellular space", - "target": "Viral dsRNA_rna_cell", + "source": "M", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t61", - "source": "NLRP3_inflammasome_complex", - "target": "Proinflammatory cytokine expression_Inflammation_phenotype", + "source": "DDX58_ubiquitinated", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t62", - "source": "Orf9b", - "target": "ITCH", + "source": "Viral dsRNA_rna_cell", + "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t63", - "source": "TRAF3_TANK_TBK1_IKKepsilon_complex", - "target": "IRF7_phosphorylated", + "source": "E", + "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t64", - "source": "IFNA1_extracellular space", - "target": "type I IFN response_phenotype", + "source": "MNS_drug", + "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t65", - "source": "IkB_p50_p65_complex_cell", - "target": "IkB_phosphorylated", + "source": "p50_p65_complex_nucleus", + "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t66", - "source": "TLR4_TRIF_TRAM_complex", - "target": "NAP1", + "source": "MAPK8", + "target": "MAPK8/14_complex", "sign": true }, { "id": "t67", - "source": "ISRE_complex", - "target": "ISG15_rna", + "source": "MAPK14", + "target": "MAPK8/14_complex", "sign": true }, { "id": "t68", + "source": "TBK1", + "target": "MAPK8/14_complex", + "sign": true + }, + { + "id": "t69", + "source": "MAP3K7", + "target": "MAPK8/14_complex", + "sign": true + }, + { + "id": "t70", + "source": "AP-1_complex_cell", + "target": "AP-1_complex_nucleus", + "sign": true + }, + { + "id": "t71", + "source": "p50_p65_complex_cell", + "target": "p50_p65_complex_nucleus", + "sign": true + }, + { + "id": "t72", + "source": "TRIF", + "target": "TLR3_TRIF_complex", + "sign": true + }, + { + "id": "t73", + "source": "Viral dsRNA_rna_endosome", + "target": "TLR3_TRIF_complex", + "sign": true + }, + { + "id": "t74", + "source": "Azithromycin_drug", + "target": "TLR3_TRIF_complex", + "sign": true + }, + { + "id": "t75", + "source": "TLR3_TRIF_complex", + "target": "TLR3_TRIF_RIPK1_complex", + "sign": true + }, + { + "id": "t76", + "source": "RIP1", + "target": "TLR3_TRIF_RIPK1_complex", + "sign": true + }, + { + "id": "t77", + "source": "TAB2", + "target": "TAB1/2_TRAF6_TAK1_complex", + "sign": true + }, + { + "id": "t78", + "source": "TRAF6_ubiquitinated", + "target": "TAB1/2_TRAF6_TAK1_complex", + "sign": true + }, + { + "id": "t79", + "source": "TLR3_TRIF_RIPK1_complex", + "target": "TAB1/2_TRAF6_TAK1_complex", + "sign": true + }, + { + "id": "t80", + "source": "TAB1", + "target": "TAB1/2_TRAF6_TAK1_complex", + "sign": true + }, + { + "id": "t81", + "source": "TAK1", + "target": "TAB1/2_TRAF6_TAK1_complex", + "sign": true + }, + { + "id": "t82", + "source": "NEMO", + "target": "IKKa_IKKb_NEMO_complex", + "sign": true + }, + { + "id": "t83", + "source": "IKKa", + "target": "IKKa_IKKb_NEMO_complex", + "sign": true + }, + { + "id": "t84", + "source": "IKKb", + "target": "IKKa_IKKb_NEMO_complex", + "sign": true + }, + { + "id": "t85", + "source": "TAB1/2_TRAF6_TAK1_complex", + "target": "IKKa_IKKb_NEMO_complex", + "sign": true + }, + { + "id": "t86", + "source": "NFKB1", + "target": "IkB_p50_p65_complex_cell", + "sign": true + }, + { + "id": "t87", + "source": "IkB", + "target": "IkB_p50_p65_complex_cell", + "sign": true + }, + { + "id": "t88", + "source": "RELA", + "target": "IkB_p50_p65_complex_cell", + "sign": true + }, + { + "id": "t89", + "source": "IKKa_IKKb_NEMO_complex", + "target": "IkB_p50_p65_complex_cell", + "sign": true + }, + { + "id": "t90", + "source": "IRF3_homodimer_complex_cell", + "target": "IRF3_homodimer_complex_nucleus", + "sign": true + }, + { + "id": "t91", + "source": "Orf6", + "target": "IRF3_homodimer_complex_nucleus", + "sign": true + }, + { + "id": "t92", + "source": "IRF3_phosphorylated", + "target": "IRF3_homodimer_complex_cell", + "sign": true + }, + { + "id": "t93", + "source": "IRF7_phosphorylated", + "target": "IRF7_homodimer_complex", + "sign": true + }, + { + "id": "t94", + "source": "ISG15", + "target": "ISG15_Nsp3_complex", + "sign": true + }, + { + "id": "t95", + "source": "GRL0617_drug", + "target": "ISG15_Nsp3_complex", + "sign": true + }, + { + "id": "t96", + "source": "Nsp3", + "target": "ISG15_Nsp3_complex", + "sign": true + }, + { + "id": "t97", + "source": "IFNB1_rna", + "target": "IFNB1_cell", + "sign": true + }, + { + "id": "t98", + "source": "IFNB1_cell", + "target": "IFNB1_extracellular space", + "sign": true + }, + { + "id": "t99", + "source": "IFNA1_rna", + "target": "IFNA1_cell", + "sign": true + }, + { + "id": "t100", + "source": "IFNA1_cell", + "target": "IFNA1_extracellular space", + "sign": true + }, + { + "id": "t101", + "source": "Azithromycin_drug", + "target": "IFNB1_rna", + "sign": true + }, + { + "id": "t102", + "source": "p50_p65_complex_nucleus", + "target": "IFNB1_rna", + "sign": true + }, + { + "id": "t103", + "source": "IRF7_homodimer_complex", + "target": "IFNB1_rna", + "sign": true + }, + { + "id": "t104", + "source": "IRF3_homodimer_complex_nucleus", + "target": "IFNB1_rna", + "sign": true + }, + { + "id": "t105", + "source": "AP-1_complex_nucleus", + "target": "IFNB1_rna", + "sign": true + }, + { + "id": "t106", + "source": "AP-1_complex_nucleus", + "target": "IFNA1_rna", + "sign": true + }, + { + "id": "t107", + "source": "IRF7_homodimer_complex", + "target": "IFNA1_rna", + "sign": true + }, + { + "id": "t108", + "source": "p50_p65_complex_nucleus", + "target": "IFNA1_rna", + "sign": true + }, + { + "id": "t109", + "source": "IRF3_homodimer_complex_nucleus", + "target": "OAS1_rna", + "sign": true + }, + { + "id": "t110", + "source": "ISRE_complex", + "target": "OAS1_rna", + "sign": true + }, + { + "id": "t111", + "source": "IRF3_homodimer_complex_nucleus", + "target": "EIF2AK_rna", + "sign": true + }, + { + "id": "t112", + "source": "ISRE_complex", + "target": "EIF2AK_rna", + "sign": true + }, + { + "id": "t113", + "source": "OAS1_cell", + "target": "OAS1_cell_active", + "sign": true + }, + { + "id": "t114", + "source": "Nsp15", + "target": "OAS1_cell_active", + "sign": true + }, + { + "id": "t115", + "source": "Nsp15", + "target": "EIF2AK", + "sign": true + }, + { + "id": "t116", + "source": "EIF2AK_rna", + "target": "EIF2AK", + "sign": true + }, + { + "id": "t117", + "source": "Nsp3", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t118", + "source": "ITCH", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t119", + "source": "MYD88_TRAM_complex", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t120", + "source": "STING1_ubiquitinated", + "target": "TBK1", + "sign": true + }, + { + "id": "t121", + "source": "MAVS", + "target": "TBK1", + "sign": true + }, + { + "id": "t122", + "source": "IKBKE", + "target": "TBK1", + "sign": true + }, + { + "id": "t123", + "source": "Nsp13", + "target": "TBK1", + "sign": true + }, + { + "id": "t124", + "source": "Nsp6", + "target": "Nsp1", + "sign": false + }, + { + "id": "t125", + "source": "Orf7b", + "target": "Nsp1", + "sign": false + }, + { + "id": "t126", + "source": "Nsp13", + "target": "Nsp1", + "sign": false + }, + { + "id": "t127", + "source": "M", + "target": "Nsp1", + "sign": false + }, + { + "id": "t128", + "source": "Orf3a", + "target": "Nsp1", + "sign": false + }, + { + "id": "t129", + "source": "Nsp6", + "target": "Orf7a", + "sign": false + }, + { + "id": "t130", + "source": "Orf7b", + "target": "Orf7a", + "sign": false + }, + { + "id": "t131", + "source": "Nsp13", + "target": "Orf7a", + "sign": false + }, + { + "id": "t132", + "source": "IRF3_homodimer_complex_nucleus", + "target": "OAS2_rna", + "sign": true + }, + { + "id": "t133", + "source": "ISRE_complex", + "target": "OAS2_rna", + "sign": true + }, + { + "id": "t134", + "source": "OAS2_cell", + "target": "OAS2_cell_active", + "sign": true + }, + { + "id": "t135", + "source": "Nsp15", + "target": "OAS2_cell_active", + "sign": true + }, + { + "id": "t136", + "source": "IRF3_homodimer_complex_nucleus", + "target": "OAS3_rna", + "sign": true + }, + { + "id": "t137", + "source": "ISRE_complex", + "target": "OAS3_rna", + "sign": true + }, + { + "id": "t138", + "source": "Nsp15", + "target": "OAS3_cell_active", + "sign": true + }, + { + "id": "t139", + "source": "OAS3_cell", + "target": "OAS3_cell_active", + "sign": true + }, + { + "id": "t140", + "source": "ISG15", + "target": "ISG expression_antiviral response_phenotype", + "sign": true + }, + { + "id": "t141", + "source": "Azithromycin_drug", + "target": "ISG expression_antiviral response_phenotype", + "sign": true + }, + { + "id": "t142", + "source": "Nsp3", + "target": "ISG expression_antiviral response_phenotype", + "sign": true + }, + { + "id": "t143", + "source": "p50_p65_complex_nucleus", + "target": "ISG expression_antiviral response_phenotype", + "sign": true + }, + { + "id": "t144", + "source": "OAS1_EIF2AK_complex", + "target": "ISG expression_antiviral response_phenotype", + "sign": true + }, + { + "id": "t145", + "source": "Nsp3", + "target": "TRAF3", + "sign": true + }, + { + "id": "t146", + "source": "MYD88_TRAM_complex", + "target": "TRAF3", + "sign": true + }, + { + "id": "t147", + "source": "TRAF6_ubiquitinated", + "target": "MAP3K7", + "sign": true + }, + { + "id": "t148", + "source": "Nsp3", + "target": "IKBKE", + "sign": true + }, + { + "id": "t149", + "source": "TBK1", + "target": "IKBKE", + "sign": true + }, + { + "id": "t150", + "source": "Nsp6", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t151", + "source": "TRAF3_TANK_TBK1_IKKepsilon_complex", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t152", + "source": "Nsp15", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t153", + "source": "N", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t154", + "source": "Nsp3", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t155", + "source": "Orf8_complex", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t156", + "source": "pp1ab", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t157", + "source": "Orf6", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t158", + "source": "MAVS", + "target": "IRF3_phosphorylated", + "sign": true + }, + { + "id": "t159", + "source": "RIG1_MDA5_complex", + "target": "MAVS", + "sign": true + }, + { + "id": "t160", + "source": "ITCH", + "target": "MAVS", + "sign": true + }, + { + "id": "t161", + "source": "Orf9b", + "target": "MAVS", + "sign": true + }, + { + "id": "t162", + "source": "Nsp15", + "target": "IFIH1", + "sign": true + }, + { + "id": "t163", + "source": "Azithromycin_drug", + "target": "IFIH1", + "sign": true + }, + { + "id": "t164", + "source": "N", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t165", + "source": "Azithromycin_drug", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t166", + "source": "TRIM25", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t167", + "source": "Nsp5", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t168", + "source": "RNF135", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t169", + "source": "OAS3_rna", + "target": "OAS3_cell", + "sign": true + }, + { + "id": "t170", + "source": "OAS2_rna", + "target": "OAS2_cell", + "sign": true + }, + { + "id": "t171", + "source": "OAS1_rna", + "target": "OAS1_cell", + "sign": true + }, + { + "id": "t172", + "source": "pp1ab", + "target": "STING1_ubiquitinated", + "sign": true + }, + { + "id": "t173", + "source": "MAVS", + "target": "STING1_ubiquitinated", + "sign": true + }, + { + "id": "t174", + "source": "IFNB1_extracellular space", + "target": "Viral dsRNA_rna_cell", + "sign": true + }, + { + "id": "t175", + "source": "Viral replication_phenotype", + "target": "Viral dsRNA_rna_cell", + "sign": true + }, + { + "id": "t176", + "source": "IFNA1_extracellular space", + "target": "Viral dsRNA_rna_cell", + "sign": true + }, + { + "id": "t177", + "source": "NLRP3_inflammasome_complex", + "target": "Proinflammatory cytokine expression_Inflammation_phenotype", + "sign": true + }, + { + "id": "t178", + "source": "p50_p65_complex_nucleus", + "target": "Proinflammatory cytokine expression_Inflammation_phenotype", + "sign": true + }, + { + "id": "t179", + "source": "Orf9b", + "target": "ITCH", + "sign": true + }, + { + "id": "t180", + "source": "TRAF3_TANK_TBK1_IKKepsilon_complex", + "target": "IRF7_phosphorylated", + "sign": true + }, + { + "id": "t181", + "source": "IFNB1_extracellular space", + "target": "type I IFN response_phenotype", + "sign": true + }, + { + "id": "t182", + "source": "IFNA1_extracellular space", + "target": "type I IFN response_phenotype", + "sign": true + }, + { + "id": "t183", + "source": "IkB_p50_p65_complex_cell", + "target": "IkB_phosphorylated", + "sign": true + }, + { + "id": "t184", + "source": "TLR4_TRIF_TRAM_complex", + "target": "NAP1", + "sign": true + }, + { + "id": "t185", + "source": "ISRE_complex", + "target": "ISG15_rna", + "sign": true + }, + { + "id": "t186", "source": "ISG15_rna", "target": "ISG15", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json index 13889e67c..c10ea6587 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json @@ -171,78 +171,120 @@ "edges": [ { "id": "t1", - "source": "3a", + "source": "7a", "target": "JNK_complex_cell", "sign": true }, { "id": "t2", + "source": "MAP2K7_phosphorylated", + "target": "JNK_complex_cell", + "sign": true + }, + { + "id": "t3", + "source": "S", + "target": "JNK_complex_cell", + "sign": true + }, + { + "id": "t4", + "source": "3a", + "target": "JNK_complex_cell", + "sign": true + }, + { + "id": "t5", + "source": "MAP2K4_phosphorylated", + "target": "JNK_complex_cell", + "sign": true + }, + { + "id": "t6", "source": "SARS-CoV-1 proteins_complex", "target": "MLK1/2/3_complex", "sign": true }, { - "id": "t3", + "id": "t7", "source": "3b", "target": "AP-1_complex", "sign": true }, { - "id": "t4", + "id": "t8", + "source": "JNK_complex_cell", + "target": "AP-1_complex", + "sign": true + }, + { + "id": "t9", "source": "SARS-CoV-1 proteins_complex", "target": "MEKK1/4_complex", "sign": true }, { - "id": "t5", + "id": "t10", + "source": "SARS-CoV-1 proteins_complex", + "target": "MAP2K4_phosphorylated", + "sign": true + }, + { + "id": "t11", "source": "MEKK1/4_complex", "target": "MAP2K4_phosphorylated", "sign": true }, { - "id": "t6", + "id": "t12", + "source": "SARS-CoV-1 proteins_complex", + "target": "MAP2K7_phosphorylated", + "sign": true + }, + { + "id": "t13", "source": "MLK1/2/3_complex", "target": "MAP2K7_phosphorylated", "sign": true }, { - "id": "t7", + "id": "t14", "source": "JNK_complex_cell", "target": "BCL2_phosphorylated", "sign": true }, { - "id": "t8", + "id": "t15", "source": "AP-1_complex", "target": "Innate Immunity_phenotype", "sign": true }, { - "id": "t9", + "id": "t16", "source": "BCL2_phosphorylated", "target": "BCL2_phosphorylated", "sign": false }, { - "id": "t10", + "id": "t17", "source": "BCL2_phosphorylated", "target": "Autophagy_phenotype", "sign": true }, { - "id": "t11", + "id": "t18", "source": "JNK_complex_cell", "target": "ATF2_phosphorylated", "sign": true }, { - "id": "t12", + "id": "t19", "source": "JNK_complex_cell", "target": "TP53_phosphorylated", "sign": true }, { - "id": "t13", + "id": "t20", "source": "TP53_phosphorylated", "target": "TP53 signalling_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json index 17c06d6e2..79e95b290 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json @@ -1635,469 +1635,1819 @@ "edges": [ { "id": "t1", - "source": "AHR", + "source": "L-Kynurenine_simple_molecule", "target": "AHR/L-KYN_complex", "sign": true }, { "id": "t2", - "source": "CO_simple_molecule", - "target": "CO_simple_molecule", - "sign": false + "source": "AHR", + "target": "AHR/L-KYN_complex", + "sign": true }, { "id": "t3", - "source": "Heme_simple_molecule", - "target": "IDO1_complex", - "sign": true + "source": "CO_simple_molecule", + "target": "CO_simple_molecule", + "sign": false }, { "id": "t4", - "source": "L-Tryptophan_simple_molecule_human host", - "target": "L-Tryptophan_simple_molecule_cell", + "source": "apo-IDO1", + "target": "IDO1_complex", "sign": true }, { "id": "t5", - "source": "IDO1_rna", - "target": "apo-IDO1", + "source": "Heme_simple_molecule", + "target": "IDO1_complex", "sign": true }, { "id": "t6", - "source": "ACS_simple_molecule", - "target": "H2O_simple_molecule_cell", + "source": "SLC36A4", + "target": "L-Tryptophan_simple_molecule_cell", "sign": true }, { "id": "t7", - "source": "IDO1_complex", - "target": "NFK_simple_molecule", + "source": "L-Tryptophan_simple_molecule_human host", + "target": "L-Tryptophan_simple_molecule_cell", "sign": true }, { "id": "t8", - "source": "I3LACT", - "target": "AP-DOBu_simple_molecule", + "source": "IDO1_rna", + "target": "apo-IDO1", "sign": true }, { "id": "t9", - "source": "AFMID", - "target": "HCOOH_simple_molecule", + "source": "KMO", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t10", - "source": "AFMID", - "target": "L-Kynurenine_simple_molecule", + "source": "QUIN_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t11", - "source": "ATP_simple_molecule_cell", - "target": "NADP+_simple_molecule_cell", + "source": "Heme_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t12", - "source": "2AMA_simple_molecule", - "target": "H+_ion_cell", + "source": "ACS_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t13", - "source": "AP-DOBu_simple_molecule", - "target": "KYNA_simple_molecule", + "source": "H+_ion_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t14", - "source": "3HKYN_simple_molecule", - "target": "L-Ala_simple_molecule", + "source": "O2_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t15", - "source": "3HKYN_simple_molecule", - "target": "3HAA_simple_molecule", + "source": "AP-DOBu_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t16", - "source": "H+_ion_cell", - "target": "3HKYN_simple_molecule", + "source": "HMOX1_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t17", - "source": "3HAA_simple_molecule", - "target": "Regulatory T-cell generation_phenotype", + "source": "PRPP_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t18", - "source": "3HAA_simple_molecule", - "target": "ACS_simple_molecule", + "source": "NADPH_simple_molecule_cell", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t19", - "source": "ACMSD", - "target": "CO2_simple_molecule", + "source": "L-Kynurenine_simple_molecule", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t20", - "source": "ACS_simple_molecule", - "target": "QUIN_simple_molecule", + "source": "QPRT", + "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t21", - "source": "2AMA_simple_molecule", - "target": "NADH_simple_molecule_cell", + "source": "O2_simple_molecule", + "target": "NFK_simple_molecule", "sign": true }, { "id": "t22", - "source": "ATP_simple_molecule_cell", - "target": "NAD+_simple_molecule_cell", + "source": "L-Tryptophan_simple_molecule_cell", + "target": "NFK_simple_molecule", "sign": true }, { "id": "t23", - "source": "ACMSD", - "target": "2AMA_simple_molecule", + "source": "IDO2", + "target": "NFK_simple_molecule", "sign": true }, { "id": "t24", - "source": "2AMA_simple_molecule", - "target": "2AM_simple_molecule", + "source": "Epacadostat_drug", + "target": "NFK_simple_molecule", "sign": true }, { "id": "t25", - "source": "CO_simple_molecule", - "target": "iNOS_rna", + "source": "IDO1_complex", + "target": "NFK_simple_molecule", "sign": true }, { "id": "t26", - "source": "iNOS_rna", - "target": "iNOS", + "source": "I3LACT", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t27", - "source": "L-Arginine_simple_molecule", - "target": "NO_simple_molecule", + "source": "I3PROPA", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t28", - "source": "IFN-G", - "target": "IDO1_rna", + "source": "L-Kynurenine_simple_molecule", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t29", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "PPi (3-)_simple_molecule", + "source": "L-Phe_simple_molecule", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t30", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "NAAD_simple_molecule_mitochondrial matrix", + "source": "PYR_simple_molecule", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t31", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "H+_ion_mitochondrial matrix", + "source": "PXLP-KYAT1_complex", + "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t32", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "ADP_simple_molecule_mitochondrial matrix", + "source": "NFK_simple_molecule", + "target": "HCOOH_simple_molecule", "sign": true }, { "id": "t33", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "NADPH_simple_molecule_mitochondrial matrix", + "source": "AFMID", + "target": "HCOOH_simple_molecule", "sign": true }, { "id": "t34", - "source": "APOA1BP", - "target": "S-NADPHX_simple_molecule", + "source": "H2O_simple_molecule_cell", + "target": "HCOOH_simple_molecule", "sign": true }, { "id": "t35", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "NADP+_simple_molecule_mitochondrial matrix", + "source": "NFK_simple_molecule", + "target": "L-Kynurenine_simple_molecule", "sign": true }, { "id": "t36", - "source": "ATP_simple_molecule_mitochondrial matrix", - "target": "Pi_simple_molecule", + "source": "AFMID", + "target": "L-Kynurenine_simple_molecule", "sign": true }, { "id": "t37", - "source": "SLC22A13", - "target": "NCA_simple_molecule", + "source": "H2O_simple_molecule_cell", + "target": "L-Kynurenine_simple_molecule", "sign": true }, { "id": "t38", - "source": "ATP_simple_molecule_cell", - "target": "PPi_simple_molecule", + "source": "KMO", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t39", "source": "ATP_simple_molecule_cell", - "target": "NAMN_simple_molecule_cell", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t40", - "source": "NAMN_simple_molecule_cell", - "target": "NAAD_simple_molecule_cell", + "source": "Heme_simple_molecule", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t41", - "source": "ATP_simple_molecule_cell", - "target": "PPi(3-)_simple_molecule_cell", + "source": "NAD+_simple_molecule_cell", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t42", - "source": "ATP_simple_molecule_cell", - "target": "L-Glu_simple_molecule", + "source": "H+_ion_cell", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t43", - "source": "ATP_simple_molecule_cell", - "target": "AMP_simple_molecule_cell", + "source": "O2_simple_molecule", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t44", - "source": "ATP_simple_molecule_cell", - "target": "ADP_simple_molecule_cell", + "source": "HMOX1_cell", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t45", - "source": "AdoMet_simple_molecule", - "target": "MNA_simple_molecule", + "source": "NADPH_simple_molecule_cell", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t46", - "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", - "target": "NAM_simple_molecule_cell", + "source": "L-Kynurenine_simple_molecule", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t47", - "source": "ATP_simple_molecule_cell", - "target": "NMN_simple_molecule_cell", + "source": "NADK:Zn2+ tetramer_complex", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t48", - "source": "AdoMet_simple_molecule", - "target": "AdoHcy_simple_molecule", + "source": "L-Arginine_simple_molecule", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t49", - "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", - "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", + "source": "iNOS", + "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t50", - "source": "BST1", - "target": "H+_ion_human host", + "source": "ATP_simple_molecule_cell", + "target": "H+_ion_cell", "sign": true }, { "id": "t51", - "source": "BST1", - "target": "NAM_simple_molecule_human host", + "source": "NAD+_simple_molecule_cell", + "target": "H+_ion_cell", "sign": true }, { "id": "t52", - "source": "H+_ion_human host", - "target": "H2O2_simple_molecule", + "source": "2AMA_simple_molecule", + "target": "H+_ion_cell", "sign": true }, { "id": "t53", - "source": "H+_ion_human host", - "target": "NAD+_simple_molecule_human host", + "source": "NAR_simple_molecule", + "target": "H+_ion_cell", "sign": true }, { "id": "t54", - "source": "BST1", - "target": "ADP-ribose_simple_molecule", + "source": "O2_simple_molecule", + "target": "H+_ion_cell", "sign": true }, { "id": "t55", - "source": "H2O_simple_molecule_human host", - "target": "Pi_ion", + "source": "H2O_simple_molecule_cell", + "target": "H+_ion_cell", "sign": true }, { "id": "t56", - "source": "H2O_simple_molecule_human host", - "target": "NMN_simple_molecule_human host", + "source": "NADPH_simple_molecule_cell", + "target": "H+_ion_cell", "sign": true }, { "id": "t57", - "source": "H2O_simple_molecule_human host", - "target": "NRNAM_simple_molecule", + "source": "NMRK1", + "target": "H+_ion_cell", "sign": true }, { "id": "t58", - "source": "AMP_simple_molecule_peroxisome", - "target": "NMNH_simple_molecule", + "source": "NR_simple_molecule", + "target": "H+_ion_cell", "sign": true }, { "id": "t59", - "source": "AMP_simple_molecule_peroxisome", - "target": "H+_ion_peroxisome", + "source": "L-Arginine_simple_molecule", + "target": "H+_ion_cell", "sign": true }, { "id": "t60", - "source": "ATP_simple_molecule_nucleus", - "target": "NAAD_simple_molecule_nucleus", + "source": "NMRK2", + "target": "H+_ion_cell", "sign": true }, { "id": "t61", - "source": "ATP_simple_molecule_nucleus", - "target": "PPi(3-)_simple_molecule_nucleus", + "source": "iNOS", + "target": "H+_ion_cell", "sign": true }, { "id": "t62", - "source": "PGH2_simple_molecule", - "target": "PGI2_simple_molecule", + "source": "AP-DOBu_simple_molecule", + "target": "KYNA_simple_molecule", "sign": true }, { "id": "t63", - "source": "H+_ion_endoplasmic reticulum", - "target": "PGH2_simple_molecule", + "source": "I3LACT", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t64", - "source": "H+_ion_endoplasmic reticulum", - "target": "H2O_simple_molecule_endoplasmic reticulum", + "source": "CCBL2", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t65", - "source": "Na+_ion_human host", - "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", + "source": "I3PROPA", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t66", - "source": "Na+_ion_human host", - "target": "Na+_ion_cell", + "source": "H2O_simple_molecule_cell", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t67", - "source": "3HAA_simple_molecule", - "target": "HMOX1_rna", + "source": "KYNU", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t68", - "source": "HMOX1_rna", - "target": "HMOX1_cell", + "source": "L-Kynurenine_simple_molecule", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t69", - "source": "Orf3a", - "target": "HMOX1_cell", + "source": "L-Phe_simple_molecule", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t70", - "source": "Heme_simple_molecule", - "target": "Fe2+_ion", + "source": "PYR_simple_molecule", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t71", - "source": "Heme_simple_molecule", - "target": "Biliverdin_simple_molecule", + "source": "PXLP-KYAT1_complex", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t72", - "source": "Heme_simple_molecule", - "target": "CO_simple_molecule", + "source": "3HKYN_simple_molecule", + "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t73", - "source": "L-Tryptophan_simple_molecule_human host", - "target": "L-Tryptophan_simple_molecule_human host", - "sign": false + "source": "H2O_simple_molecule_cell", + "target": "3HAA_simple_molecule", + "sign": true }, { "id": "t74", - "source": "3HAA_simple_molecule", - "target": "CA_simple_molecule", + "source": "KYNU", + "target": "3HAA_simple_molecule", "sign": true }, { "id": "t75", - "source": "3HAA_simple_molecule", + "source": "3HKYN_simple_molecule", "target": "3HAA_simple_molecule", - "sign": false + "sign": true }, { "id": "t76", - "source": "3HAA_simple_molecule", - "target": "T-cell apoptosis_phenotype", + "source": "KMO", + "target": "3HKYN_simple_molecule", "sign": true }, { "id": "t77", - "source": "3HAA_simple_molecule", - "target": "Dendritic cell maturation_phenotype", + "source": "H+_ion_cell", + "target": "3HKYN_simple_molecule", "sign": true }, { "id": "t78", + "source": "O2_simple_molecule", + "target": "3HKYN_simple_molecule", + "sign": true + }, + { + "id": "t79", + "source": "NADPH_simple_molecule_cell", + "target": "3HKYN_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "L-Kynurenine_simple_molecule", + "target": "3HKYN_simple_molecule", + "sign": true + }, + { + "id": "t81", + "source": "AHR/L-KYN_complex", + "target": "Regulatory T-cell generation_phenotype", + "sign": true + }, + { + "id": "t82", + "source": "3HAA_simple_molecule", + "target": "Regulatory T-cell generation_phenotype", + "sign": true + }, + { + "id": "t83", + "source": "O2_simple_molecule", + "target": "ACS_simple_molecule", + "sign": true + }, + { + "id": "t84", + "source": "HAAO", + "target": "ACS_simple_molecule", + "sign": true + }, + { + "id": "t85", + "source": "3HAA_simple_molecule", + "target": "ACS_simple_molecule", + "sign": true + }, + { + "id": "t86", + "source": "QUIN_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t87", + "source": "ACS_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t88", + "source": "H+_ion_cell", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t89", + "source": "PRPP_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t90", + "source": "ACMSD", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t91", + "source": "QPRT", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t92", + "source": "ACS_simple_molecule", + "target": "QUIN_simple_molecule", + "sign": true + }, + { + "id": "t93", + "source": "2AMA_simple_molecule", + "target": "NADH_simple_molecule_cell", + "sign": true + }, + { + "id": "t94", + "source": "H2O_simple_molecule_cell", + "target": "NADH_simple_molecule_cell", + "sign": true + }, + { + "id": "t95", + "source": "NAD+_simple_molecule_cell", + "target": "NADH_simple_molecule_cell", + "sign": true + }, + { + "id": "t96", + "source": "ATP_simple_molecule_cell", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t97", + "source": "L-Gln_simple_molecule", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t98", + "source": "NAAD_simple_molecule_cell", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t99", + "source": "NMNAT2:Mg2+_complex", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t100", + "source": "NADSYN1 hexamer", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t101", + "source": "NMN_simple_molecule_cell", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t102", + "source": "H2O_simple_molecule_cell", + "target": "NAD+_simple_molecule_cell", + "sign": true + }, + { + "id": "t103", + "source": "ACMSD", + "target": "2AMA_simple_molecule", + "sign": true + }, + { + "id": "t104", + "source": "ACS_simple_molecule", + "target": "2AMA_simple_molecule", + "sign": true + }, + { + "id": "t105", + "source": "2AMA_simple_molecule", + "target": "2AM_simple_molecule", + "sign": true + }, + { + "id": "t106", + "source": "H2O_simple_molecule_cell", + "target": "2AM_simple_molecule", + "sign": true + }, + { + "id": "t107", + "source": "NAD+_simple_molecule_cell", + "target": "2AM_simple_molecule", + "sign": true + }, + { + "id": "t108", + "source": "IFN-G", + "target": "iNOS_rna", + "sign": true + }, + { + "id": "t109", + "source": "CO_simple_molecule", + "target": "iNOS_rna", + "sign": true + }, + { + "id": "t110", + "source": "Nf-KB Complex_complex", + "target": "iNOS_rna", + "sign": true + }, + { + "id": "t111", + "source": "iNOS_rna", + "target": "iNOS", + "sign": true + }, + { + "id": "t112", + "source": "O2_simple_molecule", + "target": "NO_simple_molecule", + "sign": true + }, + { + "id": "t113", "source": "L-Arginine_simple_molecule", + "target": "NO_simple_molecule", + "sign": true + }, + { + "id": "t114", + "source": "NADPH_simple_molecule_cell", + "target": "NO_simple_molecule", + "sign": true + }, + { + "id": "t115", + "source": "iNOS", + "target": "NO_simple_molecule", + "sign": true + }, + { + "id": "t116", + "source": "IFN-G", + "target": "IDO1_rna", + "sign": true + }, + { + "id": "t117", + "source": "NO_simple_molecule", + "target": "IDO1_rna", + "sign": true + }, + { + "id": "t118", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "PPi (3-)_simple_molecule", + "sign": true + }, + { + "id": "t119", + "source": "NMNAT3:Mg2+_complex", + "target": "PPi (3-)_simple_molecule", + "sign": true + }, + { + "id": "t120", + "source": "NAMN_simple_molecule_mitochondrial matrix", + "target": "PPi (3-)_simple_molecule", + "sign": true + }, + { + "id": "t121", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "NAAD_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t122", + "source": "NMNAT3:Mg2+_complex", + "target": "NAAD_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t123", + "source": "NAMN_simple_molecule_mitochondrial matrix", + "target": "NAAD_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t124", + "source": "NAD+_simple_molecule_mitochondrial matrix", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t125", + "source": "S-NADPHX_simple_molecule", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t126", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t127", + "source": "NADK2", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t128", + "source": "CARKD", + "target": "H+_ion_mitochondrial matrix", + "sign": true + }, + { + "id": "t129", + "source": "NAD+_simple_molecule_mitochondrial matrix", + "target": "ADP_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t130", + "source": "S-NADPHX_simple_molecule", + "target": "ADP_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t131", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "ADP_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t132", + "source": "NADK2", + "target": "ADP_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t133", + "source": "CARKD", + "target": "ADP_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t134", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "NADPH_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t135", + "source": "S-NADPHX_simple_molecule", + "target": "NADPH_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t136", + "source": "CARKD", + "target": "NADPH_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t137", + "source": "R-NADPHX_simple_molecule", + "target": "S-NADPHX_simple_molecule", + "sign": true + }, + { + "id": "t138", + "source": "APOA1BP", + "target": "S-NADPHX_simple_molecule", + "sign": true + }, + { + "id": "t139", + "source": "NAD+_simple_molecule_mitochondrial matrix", + "target": "NADP+_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t140", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "NADP+_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t141", + "source": "NADK2", + "target": "NADP+_simple_molecule_mitochondrial matrix", + "sign": true + }, + { + "id": "t142", + "source": "ATP_simple_molecule_mitochondrial matrix", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t143", + "source": "S-NADPHX_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t144", + "source": "CARKD", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t145", + "source": "SLC22A13", + "target": "NCA_simple_molecule", + "sign": true + }, + { + "id": "t146", + "source": "ATP_simple_molecule_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t147", + "source": "L-Gln_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t148", + "source": "H+_ion_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t149", + "source": "NAM_simple_molecule_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t150", + "source": "NAAD_simple_molecule_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t151", + "source": "Mg2+_ion", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t152", + "source": "NADSYN1 hexamer", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t153", + "source": "NAPRT1", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t154", + "source": "PRPP_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t155", + "source": "H2O_simple_molecule_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t156", + "source": "NCA_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t157", + "source": "NAMPT", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t158", + "source": "ATP_simple_molecule_cell", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t159", + "source": "QUIN_simple_molecule", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t160", + "source": "H+_ion_cell", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t161", + "source": "NAM_simple_molecule_cell", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t162", + "source": "NAR_simple_molecule", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t163", + "source": "Mg2+_ion", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t164", + "source": "NAPRT1", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t165", + "source": "PRPP_simple_molecule", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t166", + "source": "NMRK1", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t167", + "source": "NCA_simple_molecule", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t168", + "source": "QPRT", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t169", + "source": "NAMPT", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t170", + "source": "NMRK2", + "target": "NAMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t171", + "source": "NMNAT2:Mg2+_complex", + "target": "NAAD_simple_molecule_cell", + "sign": true + }, + { + "id": "t172", + "source": "NAMN_simple_molecule_cell", + "target": "NAAD_simple_molecule_cell", + "sign": true + }, + { + "id": "t173", + "source": "ATP_simple_molecule_cell", + "target": "PPi(3-)_simple_molecule_cell", + "sign": true + }, + { + "id": "t174", + "source": "NMN_simple_molecule_cell", + "target": "PPi(3-)_simple_molecule_cell", + "sign": true + }, + { + "id": "t175", + "source": "NMNAT2:Mg2+_complex", + "target": "PPi(3-)_simple_molecule_cell", + "sign": true + }, + { + "id": "t176", + "source": "NAMN_simple_molecule_cell", + "target": "PPi(3-)_simple_molecule_cell", + "sign": true + }, + { + "id": "t177", + "source": "ATP_simple_molecule_cell", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t178", + "source": "L-Gln_simple_molecule", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t179", + "source": "NAAD_simple_molecule_cell", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t180", + "source": "NADSYN1 hexamer", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t181", + "source": "H2O_simple_molecule_cell", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t182", + "source": "ATP_simple_molecule_cell", + "target": "AMP_simple_molecule_cell", + "sign": true + }, + { + "id": "t183", + "source": "L-Gln_simple_molecule", + "target": "AMP_simple_molecule_cell", + "sign": true + }, + { + "id": "t184", + "source": "NAAD_simple_molecule_cell", + "target": "AMP_simple_molecule_cell", + "sign": true + }, + { + "id": "t185", + "source": "NADSYN1 hexamer", + "target": "AMP_simple_molecule_cell", + "sign": true + }, + { + "id": "t186", + "source": "H2O_simple_molecule_cell", + "target": "AMP_simple_molecule_cell", + "sign": true + }, + { + "id": "t187", + "source": "ATP_simple_molecule_cell", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t188", + "source": "NAD+_simple_molecule_cell", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t189", + "source": "NAR_simple_molecule", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t190", + "source": "NMRK1", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t191", + "source": "NR_simple_molecule", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t192", + "source": "NMRK2", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t193", + "source": "NADK:Zn2+ tetramer_complex", + "target": "ADP_simple_molecule_cell", + "sign": true + }, + { + "id": "t194", + "source": "NNMT", + "target": "MNA_simple_molecule", + "sign": true + }, + { + "id": "t195", + "source": "AdoMet_simple_molecule", + "target": "MNA_simple_molecule", + "sign": true + }, + { + "id": "t196", + "source": "NAM_simple_molecule_cell", + "target": "MNA_simple_molecule", + "sign": true + }, + { + "id": "t197", + "source": "PARPs", + "target": "NAM_simple_molecule_cell", + "sign": true + }, + { + "id": "t198", + "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", + "target": "NAM_simple_molecule_cell", + "sign": true + }, + { + "id": "t199", + "source": "NAD+_simple_molecule_cell", + "target": "NAM_simple_molecule_cell", + "sign": true + }, + { + "id": "t200", + "source": "NR_simple_molecule", + "target": "NMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t201", + "source": "ATP_simple_molecule_cell", + "target": "NMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t202", + "source": "NMRK2", + "target": "NMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t203", + "source": "NMRK1", + "target": "NMN_simple_molecule_cell", + "sign": true + }, + { + "id": "t204", + "source": "NNMT", + "target": "AdoHcy_simple_molecule", + "sign": true + }, + { + "id": "t205", + "source": "AdoMet_simple_molecule", + "target": "AdoHcy_simple_molecule", + "sign": true + }, + { + "id": "t206", + "source": "NAM_simple_molecule_cell", + "target": "AdoHcy_simple_molecule", + "sign": true + }, + { + "id": "t207", + "source": "PARPs", + "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", + "sign": true + }, + { + "id": "t208", + "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", + "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", + "sign": true + }, + { + "id": "t209", + "source": "NAD+_simple_molecule_cell", + "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", + "sign": true + }, + { + "id": "t210", + "source": "CD38", + "target": "H+_ion_human host", + "sign": true + }, + { + "id": "t211", + "source": "NAD+_simple_molecule_human host", + "target": "H+_ion_human host", + "sign": true + }, + { + "id": "t212", + "source": "BST1", + "target": "H+_ion_human host", + "sign": true + }, + { + "id": "t213", + "source": "H2O_simple_molecule_human host", + "target": "H+_ion_human host", + "sign": true + }, + { + "id": "t214", + "source": "CD38", + "target": "NAM_simple_molecule_human host", + "sign": true + }, + { + "id": "t215", + "source": "NAD+_simple_molecule_human host", + "target": "NAM_simple_molecule_human host", + "sign": true + }, + { + "id": "t216", + "source": "BST1", + "target": "NAM_simple_molecule_human host", + "sign": true + }, + { + "id": "t217", + "source": "H2O_simple_molecule_human host", + "target": "NAM_simple_molecule_human host", + "sign": true + }, + { + "id": "t218", + "source": "H+_ion_human host", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t219", + "source": "O2_ion", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t220", + "source": "dh-beta-NAD_simple_molecule", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t221", + "source": "RNLS:FAD_complex", + "target": "H2O2_simple_molecule", + "sign": true + }, + { + "id": "t222", + "source": "H+_ion_human host", + "target": "NAD+_simple_molecule_human host", + "sign": true + }, + { + "id": "t223", + "source": "O2_ion", + "target": "NAD+_simple_molecule_human host", + "sign": true + }, + { + "id": "t224", + "source": "dh-beta-NAD_simple_molecule", + "target": "NAD+_simple_molecule_human host", + "sign": true + }, + { + "id": "t225", + "source": "RNLS:FAD_complex", + "target": "NAD+_simple_molecule_human host", + "sign": true + }, + { + "id": "t226", + "source": "CD38", + "target": "ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t227", + "source": "NAD+_simple_molecule_human host", + "target": "ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t228", + "source": "BST1", + "target": "ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t229", + "source": "H2O_simple_molecule_human host", + "target": "ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t230", + "source": "NMN_simple_molecule_human host", + "target": "Pi_ion", + "sign": true + }, + { + "id": "t231", + "source": "NAD+_simple_molecule_human host", + "target": "Pi_ion", + "sign": true + }, + { + "id": "t232", + "source": "NT5E:Zn2+_complex", + "target": "Pi_ion", + "sign": true + }, + { + "id": "t233", + "source": "H2O_simple_molecule_human host", + "target": "Pi_ion", + "sign": true + }, + { + "id": "t234", + "source": "NAD+_simple_molecule_human host", + "target": "NMN_simple_molecule_human host", + "sign": true + }, + { + "id": "t235", + "source": "NT5E:Zn2+_complex", + "target": "NMN_simple_molecule_human host", + "sign": true + }, + { + "id": "t236", + "source": "H2O_simple_molecule_human host", + "target": "NMN_simple_molecule_human host", + "sign": true + }, + { + "id": "t237", + "source": "NMN_simple_molecule_human host", + "target": "NRNAM_simple_molecule", + "sign": true + }, + { + "id": "t238", + "source": "NT5E:Zn2+_complex", + "target": "NRNAM_simple_molecule", + "sign": true + }, + { + "id": "t239", + "source": "H2O_simple_molecule_human host", + "target": "NRNAM_simple_molecule", + "sign": true + }, + { + "id": "t240", + "source": "AMP_simple_molecule_peroxisome", + "target": "NMNH_simple_molecule", + "sign": true + }, + { + "id": "t241", + "source": "H2O_simple_molecule_peroxisome", + "target": "NMNH_simple_molecule", + "sign": true + }, + { + "id": "t242", + "source": "NADH_simple_molecule_peroxisome", + "target": "NMNH_simple_molecule", + "sign": true + }, + { + "id": "t243", + "source": "NUDT12", + "target": "NMNH_simple_molecule", + "sign": true + }, + { + "id": "t244", + "source": "AMP_simple_molecule_peroxisome", + "target": "H+_ion_peroxisome", + "sign": true + }, + { + "id": "t245", + "source": "H2O_simple_molecule_peroxisome", + "target": "H+_ion_peroxisome", + "sign": true + }, + { + "id": "t246", + "source": "NADH_simple_molecule_peroxisome", + "target": "H+_ion_peroxisome", + "sign": true + }, + { + "id": "t247", + "source": "NUDT12", + "target": "H+_ion_peroxisome", + "sign": true + }, + { + "id": "t248", + "source": "NAMN_simple_molecule_nucleus", + "target": "NAAD_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t249", + "source": "NMNAT1:Zn2+_complex", + "target": "NAAD_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t250", + "source": "ATP_simple_molecule_nucleus", + "target": "NAAD_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t251", + "source": "NAMN_simple_molecule_nucleus", + "target": "PPi(3-)_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t252", + "source": "NMNAT1:Zn2+_complex", + "target": "PPi(3-)_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t253", + "source": "ATP_simple_molecule_nucleus", + "target": "PPi(3-)_simple_molecule_nucleus", + "sign": true + }, + { + "id": "t254", + "source": "PTGIS", + "target": "PGI2_simple_molecule", + "sign": true + }, + { + "id": "t255", + "source": "PGH2_simple_molecule", + "target": "PGI2_simple_molecule", + "sign": true + }, + { + "id": "t256", + "source": "H+_ion_endoplasmic reticulum", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t257", + "source": "PGG2_simple_molecule", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t258", + "source": "e-_ion", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t259", + "source": "PTGS2", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t260", + "source": "PTCS2:celecoxib_complex", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t261", + "source": "MNA_simple_molecule", + "target": "PGH2_simple_molecule", + "sign": true + }, + { + "id": "t262", + "source": "H+_ion_endoplasmic reticulum", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t263", + "source": "PGG2_simple_molecule", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t264", + "source": "e-_ion", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t265", + "source": "PTGS2", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t266", + "source": "PTCS2:celecoxib_complex", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t267", + "source": "MNA_simple_molecule", + "target": "H2O_simple_molecule_endoplasmic reticulum", + "sign": true + }, + { + "id": "t268", + "source": "monocarboxylates transported by SLC5A8_simple_molecule_human host", + "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", + "sign": true + }, + { + "id": "t269", + "source": "SLC5A8", + "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", + "sign": true + }, + { + "id": "t270", + "source": "Na+_ion_human host", + "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", + "sign": true + }, + { + "id": "t271", + "source": "monocarboxylates transported by SLC5A8_simple_molecule_human host", + "target": "Na+_ion_cell", + "sign": true + }, + { + "id": "t272", + "source": "SLC5A8", + "target": "Na+_ion_cell", + "sign": true + }, + { + "id": "t273", + "source": "Na+_ion_human host", + "target": "Na+_ion_cell", + "sign": true + }, + { + "id": "t274", + "source": "IFN-G", + "target": "HMOX1_rna", + "sign": true + }, + { + "id": "t275", + "source": "NO_simple_molecule", + "target": "HMOX1_rna", + "sign": true + }, + { + "id": "t276", + "source": "3HAA_simple_molecule", + "target": "HMOX1_rna", + "sign": true + }, + { + "id": "t277", + "source": "HMOX1_rna", + "target": "HMOX1_cell", + "sign": true + }, + { + "id": "t278", + "source": "Orf3a", + "target": "HMOX1_cell", + "sign": true + }, + { + "id": "t279", + "source": "O2_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t280", + "source": "HMOX1_cell", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t281", + "source": "Heme_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t282", + "source": "NADPH_simple_molecule_cell", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t283", + "source": "O2_simple_molecule", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t284", + "source": "HMOX1_cell", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t285", + "source": "Heme_simple_molecule", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t286", + "source": "NADPH_simple_molecule_cell", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t287", + "source": "O2_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t288", + "source": "HMOX1_cell", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t289", + "source": "Heme_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t290", + "source": "NADPH_simple_molecule_cell", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t291", + "source": "L-Tryptophan_simple_molecule_human host", + "target": "L-Tryptophan_simple_molecule_human host", + "sign": false + }, + { + "id": "t292", + "source": "3HAA_simple_molecule", + "target": "CA_simple_molecule", + "sign": true + }, + { + "id": "t293", + "source": "3HAA_simple_molecule", + "target": "3HAA_simple_molecule", + "sign": false + }, + { + "id": "t294", + "source": "3HAA_simple_molecule", + "target": "T-cell apoptosis_phenotype", + "sign": true + }, + { + "id": "t295", + "source": "L-Kynurenine_simple_molecule", + "target": "T-cell apoptosis_phenotype", + "sign": true + }, + { + "id": "t296", + "source": "CA_simple_molecule", + "target": "T-cell apoptosis_phenotype", + "sign": true + }, + { + "id": "t297", + "source": "3HKYN_simple_molecule", + "target": "T-cell apoptosis_phenotype", + "sign": true + }, + { + "id": "t298", + "source": "3HKYN_simple_molecule", + "target": "Dendritic cell maturation_phenotype", + "sign": true + }, + { + "id": "t299", + "source": "3HAA_simple_molecule", + "target": "Dendritic cell maturation_phenotype", + "sign": true + }, + { + "id": "t300", + "source": "O2_simple_molecule", + "target": "Citrulline_simple_molecule", + "sign": true + }, + { + "id": "t301", + "source": "L-Arginine_simple_molecule", + "target": "Citrulline_simple_molecule", + "sign": true + }, + { + "id": "t302", + "source": "NADPH_simple_molecule_cell", + "target": "Citrulline_simple_molecule", + "sign": true + }, + { + "id": "t303", + "source": "iNOS", "target": "Citrulline_simple_molecule", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json index d52b0f123..2c8959bf5 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json @@ -632,264 +632,564 @@ "edges": [ { "id": "t1", - "source": "ASC:MAVS_complex", + "source": "TRAF3", "target": "ASC:MAVS:TRAF3_complex_cell", "sign": true }, { "id": "t2", + "source": "ASC:MAVS_complex", + "target": "ASC:MAVS:TRAF3_complex_cell", + "sign": true + }, + { + "id": "t3", + "source": "SUGT1:HSP90AB1_complex", + "target": "NLRP3:SUGT1:HSP90_complex", + "sign": true + }, + { + "id": "t4", "source": "NLRP3_cell", "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { - "id": "t3", + "id": "t5", "source": "CASP1_cell", "target": "NLRP3 oligomer:ASC:proCaspase1_complex", "sign": true }, { - "id": "t4", + "id": "t6", + "source": "NLRP3 oligomer:ASC_complex", + "target": "NLRP3 oligomer:ASC:proCaspase1_complex", + "sign": true + }, + { + "id": "t7", + "source": "CTSG", + "target": "NLRP3 oligomer:ASC_complex", + "sign": true + }, + { + "id": "t8", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "target": "NLRP3 oligomer:ASC_complex", + "sign": true + }, + { + "id": "t9", "source": "ASC_ubiquitinated", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { - "id": "t5", + "id": "t10", + "source": "NLRP3_cell", + "target": "NLRP3 oligomer:ASC_complex", + "sign": true + }, + { + "id": "t11", "source": "CASP1(120-197):CASP1(317-404)_complex", "target": "Caspase-1 Tetramer_complex", "sign": true }, { - "id": "t6", + "id": "t12", + "source": "TXNIP", + "target": "TXNIP:NLRP3_complex", + "sign": true + }, + { + "id": "t13", "source": "NLRP3_cell", "target": "TXNIP:NLRP3_complex", "sign": true }, { - "id": "t7", + "id": "t14", "source": "CASP1_cell", "target": "CASP1(120-197):CASP1(317-404)_complex", "sign": true }, { - "id": "t8", + "id": "t15", "source": "TRAF3:SARS Orf3a_complex_cell", "target": "ASC:MAVS:TRAF3_complex_cell", "sign": true }, { - "id": "t9", + "id": "t16", "source": "Nf-KB Complex_complex_cell", "target": "NF-KB COMPLEX:IKBA_complex", "sign": true }, { - "id": "t10", + "id": "t17", + "source": "IKBA_phosphorylated_phosphorylated", + "target": "NF-KB COMPLEX:IKBA_complex", + "sign": true + }, + { + "id": "t18", "source": "p50", "target": "Nf-KB Complex_complex_cell", "sign": true }, { - "id": "t11", + "id": "t19", + "source": "p65", + "target": "Nf-KB Complex_complex_cell", + "sign": true + }, + { + "id": "t20", + "source": "Nf-KB Complex_complex_cell", + "target": "Nf-KB Complex_complex_nucleus", + "sign": true + }, + { + "id": "t21", "source": "NF-KB COMPLEX:IKBA_complex", "target": "Nf-KB Complex_complex_nucleus", "sign": true }, { - "id": "t12", + "id": "t22", + "source": "TXN_cell", + "target": "Thioredoxin:TXNIP_complex", + "sign": true + }, + { + "id": "t23", "source": "TXNIP", "target": "Thioredoxin:TXNIP_complex", "sign": true }, { - "id": "t13", + "id": "t24", "source": "ASC", "target": "ASC:MAVS_complex", "sign": true }, { - "id": "t14", + "id": "t25", + "source": "MAVS", + "target": "ASC:MAVS_complex", + "sign": true + }, + { + "id": "t26", + "source": "TRAF3", + "target": "TRAF3:SARS Orf3a_complex_cell", + "sign": true + }, + { + "id": "t27", "source": "Orf3a", "target": "TRAF3:SARS Orf3a_complex_cell", "sign": true }, { - "id": "t15", + "id": "t28", "source": "Ca2+_ion", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { - "id": "t16", + "id": "t29", + "source": "NLRP3 Elicitor Proteins", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t30", + "source": "NLRP3:SUGT1:HSP90_complex", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t31", + "source": "PAMPs_phenotype", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t32", + "source": "Reactive Oxygen Species_simple_molecule", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t33", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t34", + "source": "DAMPs_phenotype", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t35", + "source": "TXNIP:NLRP3_complex", + "target": "SUGT1:HSP90AB1_complex", + "sign": true + }, + { + "id": "t36", "source": "CO_simple_molecule", "target": "CO_simple_molecule", "sign": false }, { - "id": "t17", + "id": "t37", "source": "Thioredoxin:TXNIP_complex", "target": "TXNIP", "sign": true }, { - "id": "t18", + "id": "t38", "source": "proIL-18_rna", "target": "proIL-18_cell", "sign": true }, { - "id": "t19", + "id": "t39", "source": "proIL-1B_rna", "target": "proIL-1B_cell", "sign": true }, { - "id": "t20", + "id": "t40", + "source": "proIL-18_cell", + "target": "IL-18_cell", + "sign": true + }, + { + "id": "t41", "source": "Caspase-1 Tetramer_complex", "target": "IL-18_cell", "sign": true }, { - "id": "t21", + "id": "t42", + "source": "proIL-1B_cell", + "target": "IL-1B_cell", + "sign": true + }, + { + "id": "t43", "source": "Caspase-1 Tetramer_complex", "target": "IL-1B_cell", "sign": true }, { - "id": "t22", + "id": "t44", "source": "Caspase-1 Tetramer_complex", "target": "proIL-18_cell", "sign": true }, { - "id": "t23", + "id": "t45", "source": "IL-18_cell", "target": "IL-18_default_compartment", "sign": true }, { - "id": "t24", + "id": "t46", "source": "IL-1B_cell", "target": "IL-1B_default_compartment", "sign": true }, { - "id": "t25", + "id": "t47", "source": "p105_ubiquitinated", "target": "p50", "sign": true }, { - "id": "t26", + "id": "t48", "source": "TRAF3:SARS Orf3a_complex_cell", "target": "p105_ubiquitinated", "sign": true }, { - "id": "t27", + "id": "t49", "source": "Nf-KB Complex_complex_nucleus", "target": "proIL-18_rna", "sign": true }, { - "id": "t28", + "id": "t50", "source": "Nf-KB Complex_complex_nucleus", "target": "proIL-1B_rna", "sign": true }, { - "id": "t29", + "id": "t51", "source": "ASC:MAVS:TRAF3_complex_cell", "target": "TRAF3", "sign": true }, { - "id": "t30", + "id": "t52", "source": "Ca2+_ion", "target": "NLRP3_cell", "sign": true }, { - "id": "t31", + "id": "t53", + "source": "NLRP3 Elicitor Proteins", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t54", + "source": "NLRP3:SUGT1:HSP90_complex", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t55", + "source": "PAMPs_phenotype", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t56", + "source": "Reactive Oxygen Species_simple_molecule", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t57", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t58", + "source": "DAMPs_phenotype", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t59", + "source": "TXNIP:NLRP3_complex", + "target": "NLRP3_cell", + "sign": true + }, + { + "id": "t60", "source": "ASC:MAVS:TRAF3_complex_cell", "target": "MAVS", "sign": true }, { - "id": "t32", + "id": "t61", "source": "ASC:MAVS:TRAF3_complex_cell", "target": "ASC_ubiquitinated", "sign": true }, { - "id": "t33", + "id": "t62", "source": "E_Golgi apparatus", "target": "Ca2+_ion", "sign": true }, { - "id": "t34", + "id": "t63", + "source": "E_endoplasmic reticulum-Golgi intermediate compartment", + "target": "Ca2+_ion", + "sign": true + }, + { + "id": "t64", + "source": "O2_simple_molecule", + "target": "NADP+_simple_molecule", + "sign": true + }, + { + "id": "t65", "source": "HMOX1", "target": "NADP+_simple_molecule", "sign": true }, { - "id": "t35", + "id": "t66", + "source": "Heme_simple_molecule", + "target": "NADP+_simple_molecule", + "sign": true + }, + { + "id": "t67", + "source": "NADPH_simple_molecule", + "target": "NADP+_simple_molecule", + "sign": true + }, + { + "id": "t68", + "source": "O2_simple_molecule", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t69", "source": "HMOX1", "target": "Biliverdin_simple_molecule", "sign": true }, { - "id": "t36", + "id": "t70", + "source": "Heme_simple_molecule", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t71", + "source": "NADPH_simple_molecule", + "target": "Biliverdin_simple_molecule", + "sign": true + }, + { + "id": "t72", + "source": "O2_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t73", "source": "HMOX1", "target": "H2O_simple_molecule", "sign": true }, { - "id": "t37", + "id": "t74", + "source": "Heme_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t75", + "source": "NADPH_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t76", + "source": "O2_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t77", "source": "HMOX1", "target": "CO_simple_molecule", "sign": true }, { - "id": "t38", + "id": "t78", + "source": "Heme_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t79", + "source": "NADPH_simple_molecule", + "target": "CO_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "O2_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t81", "source": "HMOX1", "target": "Fe2+_ion", "sign": true }, { - "id": "t39", + "id": "t82", + "source": "Heme_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t83", + "source": "NADPH_simple_molecule", + "target": "Fe2+_ion", + "sign": true + }, + { + "id": "t84", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t40", + "id": "t85", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t86", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t41", + "id": "t87", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t88", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t42", + "id": "t89", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t90", "source": "CTSG", "target": "CASP1_cell", "sign": true }, { - "id": "t43", + "id": "t91", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "target": "CASP1_cell", + "sign": true + }, + { + "id": "t92", "source": "Caspase-1 Tetramer_complex", "target": "proIL-1B_cell", "sign": true }, { - "id": "t44", + "id": "t93", + "source": "Thioredoxin:TXNIP_complex", + "target": "TXN_cell", + "sign": true + }, + { + "id": "t94", "source": "Reactive Oxygen Species_simple_molecule", "target": "TXN_cell", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json index 67f1bae5f..6a98c0d47 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json @@ -1807,444 +1807,3330 @@ "edges": [ { "id": "t1", - "source": "Nsp14_mitochondrion", + "source": "SIRT5", "target": "SIRT5:Nsp14_complex", "sign": true }, { "id": "t2", - "source": "Nsp14_cell", - "target": "GLA:Nsp14_complex", + "source": "Nsp14_mitochondrion", + "target": "SIRT5:Nsp14_complex", "sign": true }, { "id": "t3", - "source": "Nsp14_cell", - "target": "IMPDH2:Nsp14_complex", + "source": "GLA", + "target": "GLA:Nsp14_complex", "sign": true }, { "id": "t4", - "source": "Galacitol_simple_molecule", - "target": "D-Galactose_simple_molecule", + "source": "Nsp14_cell", + "target": "GLA:Nsp14_complex", "sign": true }, { "id": "t5", - "source": "D-Galactose_simple_molecule", - "target": "_alpha_-D-Galactose_simple_molecule", + "source": "IMPDH2", + "target": "IMPDH2:Nsp14_complex", "sign": true }, { "id": "t6", - "source": "ATP_simple_molecule", - "target": "_alpha_-D-Galactose-1P_simple_molecule", + "source": "Nsp14_cell", + "target": "IMPDH2:Nsp14_complex", "sign": true }, { "id": "t7", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", - "target": "ADP_simple_molecule", + "source": "NADP_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t8", - "source": "UDP-_alpha_-D-Glucose_simple_molecule", - "target": "UDP-_alpha_-D-Galactose_simple_molecule", + "source": "LCT", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t9", - "source": "PPi_simple_molecule", - "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "source": "AKR1B1", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t10", - "source": "PPi_simple_molecule", - "target": "UTP_simple_molecule", + "source": "Galacitol_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t11", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "PPi_simple_molecule", + "source": "Melibiose_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t12", - "source": "UDP-_alpha_-D-Galactose_simple_molecule", - "target": "Lactose_simple_molecule", + "source": "GLA:Nsp14_complex", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t13", - "source": "H2O_simple_molecule_cell", - "target": "_alpha_-D-Glucose_simple_molecule", + "source": "Migalastat_drug", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t14", - "source": "UDP-_alpha_-D-Galactose_simple_molecule", - "target": "UDP_simple_molecule", + "source": "Lactose_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t15", - "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", - "target": "H2O_simple_molecule_cell", + "source": "GLB1", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t16", - "source": "ATP_simple_molecule", - "target": "NADP_simple_molecule", + "source": "GLA", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t17", - "source": "Ammonium_simple_molecule", - "target": "NADPH_simple_molecule", + "source": "Raffinose_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t18", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", - "target": "H_simple_molecule", + "source": "Stachyose_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t19", "source": "H2O_simple_molecule_cell", - "target": "Raffinose_simple_molecule", + "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t20", - "source": "H2O_simple_molecule_cell", - "target": "Sucrose_simple_molecule", + "source": "D-Galactose_simple_molecule", + "target": "_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t21", - "source": "CD38", - "target": "Nicotinamide_simple_molecule", + "source": "GALM", + "target": "_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t22", - "source": "H2O_simple_molecule_cell", - "target": "N-Ribosyl-nicotinamide_simple_molecule", + "source": "_alpha_-D-Galactose_simple_molecule", + "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t23", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "source": "ATP_simple_molecule", + "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t24", - "source": "ATP_simple_molecule", - "target": "NAD_simple_molecule", + "source": "GALK1", + "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t25", - "source": "ATP_simple_molecule", - "target": "Deamino-NAD_simple_molecule", + "source": "DCK", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t26", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "Nicotinate D-ribonucleotide_simple_molecule", + "source": "NME6", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t27", - "source": "H2O_simple_molecule_cell", - "target": "NADH_simple_molecule", + "source": "GMP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t28", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "L-Glutamate_simple_molecule", + "source": "AK1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t29", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "AMP_simple_molecule", + "source": "ADK", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t30", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", - "target": "Pi_simple_molecule", + "source": "GUK1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t31", - "source": "CD38", - "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", + "source": "NAD_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t32", - "source": "ATP_simple_molecule", - "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t33", - "source": "Adenosine_simple_molecule", - "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "source": "dGMP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t34", - "source": "H2O_simple_molecule_mitochondrion", - "target": "Histone-L-lysine_simple_molecule", + "source": "Adenosine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t35", - "source": "H2O_simple_molecule_mitochondrion", - "target": "O-Acetyl-ADP-ribose_simple_molecule", + "source": "GALK1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t36", - "source": "CD38", - "target": "ADP-D-ribose_simple_molecule", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t37", "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "CO2_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t38", - "source": "_alpha_D-Ribose 1P_simple_molecule", - "target": "D-Ribose 5P_simple_molecule", + "source": "dAMP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t39", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "5-phospho-beta-D-ribosylamine_simple_molecule", + "source": "NADK", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t40", - "source": "5-phospho-beta-D-ribosylamine_simple_molecule", - "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "source": "L-Aspartate_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t41", - "source": "10-Formyltetrahydrofolate_simple_molecule", - "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "source": "AMP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t42", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", - "target": "Tetrahydrofolate_simple_molecule", + "source": "L-Glutamine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t43", - "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", - "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "source": "NME7", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t44", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", - "target": "Aminoimidazole ribotide_simple_molecule", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t45", - "source": "Aminoimidazole ribotide_simple_molecule", - "target": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "source": "PFAS", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t46", - "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", - "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t47", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", - "target": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "source": "AK5", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t48", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", - "target": "Fumarate_simple_molecule", + "source": "H2O_simple_molecule_cell", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t49", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", - "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "source": "dADP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t50", - "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", - "target": "IMP_simple_molecule", + "source": "NME5", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t51", - "source": "H2O_simple_molecule_cell", - "target": "XMP_simple_molecule", + "source": "NAPRT1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t52", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", - "target": "GMP_simple_molecule", + "source": "Nicotinate_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t53", - "source": "ATP_simple_molecule", - "target": "GDP_simple_molecule", + "source": "GART", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t54", - "source": "ATP_simple_molecule", - "target": "GTP_simple_molecule", + "source": "dGDP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t55", - "source": "ATP_simple_molecule", - "target": "dGDP_simple_molecule", + "source": "NME3", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t56", - "source": "ADP_simple_molecule", - "target": "Thioredoxin disulfide_simple_molecule", + "source": "N-Ribosyl-nicotinamide_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t57", - "source": "ATP_simple_molecule", - "target": "dGTP_simple_molecule", + "source": "AK7", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t58", "source": "ATP_simple_molecule", - "target": "dGMP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t59", "source": "Deoxyguanosine_simple_molecule", - "target": "Guanine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t60", - "source": "GMP_simple_molecule", - "target": "Guanosine_simple_molecule", + "source": "PAICS", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t61", - "source": "Deoxyguanosine_simple_molecule", - "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "source": "Nucleoside diphosphate kinase_complex_cell", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t62", - "source": "AMP_simple_molecule", - "target": "Ammonium_simple_molecule", + "source": "NADSYN1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t63", - "source": "H2O_simple_molecule_cell", - "target": "Xanthosine_simple_molecule", + "source": "AK8", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t64", - "source": "Guanine_simple_molecule", - "target": "Xanthine_simple_molecule", + "source": "Deoxyadenosine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t65", - "source": "Adenosine_simple_molecule", - "target": "Inosine_simple_molecule", + "source": "_alpha_-D-Galactose_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t66", - "source": "Inosine_simple_molecule", - "target": "Hypoxanthine_simple_molecule", + "source": "NRK1", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t67", - "source": "AMP_simple_molecule", - "target": "Adenosine_simple_molecule", + "source": "Glycine_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t68", - "source": "Adenosine_simple_molecule", - "target": "Adenine_simple_molecule", + "source": "GDP_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t69", - "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", - "target": "Deoxyinosine_simple_molecule", + "source": "Deamino-NAD_simple_molecule", + "target": "ADP_simple_molecule", "sign": true }, { "id": "t70", - "source": "ATP_simple_molecule", - "target": "dAMP_simple_molecule", + "source": "_alpha_-D-Galactose-1P_simple_molecule", + "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t71", - "source": "ADP_simple_molecule", - "target": "dADP_simple_molecule", + "source": "UDP-_alpha_-D-Glucose_simple_molecule", + "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t72", - "source": "ATP_simple_molecule", - "target": "dATP_simple_molecule", + "source": "GALT", + "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t73", - "source": "IMPDH2", - "target": "Guanine nucleotide synthesis_phenotype", + "source": "GALE", + "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t74", + "source": "UDP-_alpha_-D-Glucose_simple_molecule", + "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "sign": true + }, + { + "id": "t75", + "source": "UGP2", + "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "sign": true + }, + { + "id": "t76", + "source": "_alpha_-D-Galactose-1P_simple_molecule", + "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "sign": true + }, + { + "id": "t77", + "source": "GALT", + "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "sign": true + }, + { + "id": "t78", + "source": "PPi_simple_molecule", + "target": "_alpha_-D-Glucose-1-P_simple_molecule", + "sign": true + }, + { + "id": "t79", + "source": "PPi_simple_molecule", + "target": "UTP_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "UDP-_alpha_-D-Glucose_simple_molecule", + "target": "UTP_simple_molecule", + "sign": true + }, + { + "id": "t81", + "source": "UGP2", + "target": "UTP_simple_molecule", + "sign": true + }, + { + "id": "t82", + "source": "Nicotinamide_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t83", + "source": "NMNAT3", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t84", + "source": "NAPRT1", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t85", + "source": "Guanine_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t86", + "source": "Nicotinate_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t87", + "source": "HPRT1", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t88", + "source": "GMPS", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t89", + "source": "dGTP_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t90", + "source": "PPAT", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t91", + "source": "APRT", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t92", + "source": "ATP_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t93", + "source": "QPRT", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t94", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t95", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t96", + "source": "Hypoxanthine_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t97", + "source": "NMNAT2", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t98", + "source": "Adenine_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t99", + "source": "H_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t100", + "source": "L-Glutamine_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t101", + "source": "NMNAT1", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t102", + "source": "Quinolinate_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t103", + "source": "ENPP1", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t104", + "source": "ENPP3", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t105", + "source": "XMP_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t106", + "source": "NAMPT", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t107", + "source": "Nicotinate D-ribonucleotide_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t108", + "source": "H2O_simple_molecule_cell", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t109", + "source": "ITPA", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t110", + "source": "_alpha_-D-Glucose_simple_molecule", + "target": "Lactose_simple_molecule", + "sign": true + }, + { + "id": "t111", + "source": "UDP-_alpha_-D-Galactose_simple_molecule", + "target": "Lactose_simple_molecule", + "sign": true + }, + { + "id": "t112", + "source": "lactose synthetase_complex", + "target": "Lactose_simple_molecule", + "sign": true + }, + { + "id": "t113", + "source": "Melibiose_simple_molecule", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t114", + "source": "LCT", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t115", + "source": "GLA:Nsp14_complex", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t116", + "source": "Migalastat_drug", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t117", + "source": "Lactose_simple_molecule", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t118", + "source": "GLB1", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t119", + "source": "GLA", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t120", + "source": "H2O_simple_molecule_cell", + "target": "_alpha_-D-Glucose_simple_molecule", + "sign": true + }, + { + "id": "t121", + "source": "_alpha_-D-Glucose_simple_molecule", + "target": "UDP_simple_molecule", + "sign": true + }, + { + "id": "t122", + "source": "UDP-_alpha_-D-Galactose_simple_molecule", + "target": "UDP_simple_molecule", + "sign": true + }, + { + "id": "t123", + "source": "lactose synthetase_complex", + "target": "UDP_simple_molecule", + "sign": true + }, + { + "id": "t124", + "source": "GDP_simple_molecule", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t125", + "source": "ATIC", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t126", + "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t127", + "source": "ribonucleoside reductase_complex_cell", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t128", + "source": "Thioredoxin_simple_molecule", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t129", + "source": "ADP_simple_molecule", + "target": "H2O_simple_molecule_cell", + "sign": true + }, + { + "id": "t130", + "source": "NADK", + "target": "NADP_simple_molecule", + "sign": true + }, + { + "id": "t131", + "source": "NADPH_simple_molecule", + "target": "NADP_simple_molecule", + "sign": true + }, + { + "id": "t132", + "source": "NNT", + "target": "NADP_simple_molecule", + "sign": true + }, + { + "id": "t133", + "source": "NAD_simple_molecule", + "target": "NADP_simple_molecule", + "sign": true + }, + { + "id": "t134", + "source": "ATP_simple_molecule", + "target": "NADP_simple_molecule", + "sign": true + }, + { + "id": "t135", + "source": "NADP_simple_molecule", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t136", + "source": "AKR1B1", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t137", + "source": "Galacitol_simple_molecule", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t138", + "source": "GMPR2", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t139", + "source": "Ammonium_simple_molecule", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t140", + "source": "GMPR", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t141", + "source": "IMP_simple_molecule", + "target": "NADPH_simple_molecule", + "sign": true + }, + { + "id": "t142", + "source": "DCK", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t143", + "source": "NADP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t144", + "source": "GTP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t145", + "source": "Ribavirin_drug", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t146", + "source": "Merimepodib_drug", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t147", + "source": "ENTPD5", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t148", + "source": "ADK", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t149", + "source": "NAD_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t150", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t151", + "source": "10-Formyltetrahydrofolate_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t152", + "source": "Adenosine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t153", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t154", + "source": "NADK", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t155", + "source": "CD38", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t156", + "source": "L-Aspartate_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t157", + "source": "IMPDH1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t158", + "source": "AKR1B1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t159", + "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t160", + "source": "CANT1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t161", + "source": "L-Glutamine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t162", + "source": "GMPR2", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t163", + "source": "Hypoxanthine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t164", + "source": "XDH", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t165", + "source": "CO2_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t166", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t167", + "source": "ENPP3", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t168", + "source": "Aminoimidazole ribotide_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t169", + "source": "PFAS", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t170", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t171", + "source": "IMPDH2", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t172", + "source": "H2O_simple_molecule_cell", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t173", + "source": "ENTPD4", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t174", + "source": "IMPDH2:Nsp14_complex", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t175", + "source": "ENTPD6", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t176", + "source": "GART", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t177", + "source": "Ammonium_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t178", + "source": "N-Ribosyl-nicotinamide_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t179", + "source": "GMPS", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t180", + "source": "dGTP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t181", + "source": "ATP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t182", + "source": "Mycophenolic acid_drug", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t183", + "source": "Deoxyguanosine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t184", + "source": "Galacitol_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t185", + "source": "PAICS", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t186", + "source": "ENTPD2", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t187", + "source": "NADSYN1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t188", + "source": "ENPP1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t189", + "source": "Deoxyadenosine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t190", + "source": "NRK1", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t191", + "source": "Glycine_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t192", + "source": "XMP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t193", + "source": "GMPR", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t194", + "source": "GDP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t195", + "source": "IMP_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t196", + "source": "NTPCR", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t197", + "source": "Deamino-NAD_simple_molecule", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t198", + "source": "ITPA", + "target": "H_simple_molecule", + "sign": true + }, + { + "id": "t199", + "source": "GLA:Nsp14_complex", + "target": "Raffinose_simple_molecule", + "sign": true + }, + { + "id": "t200", + "source": "Migalastat_drug", + "target": "Raffinose_simple_molecule", + "sign": true + }, + { + "id": "t201", + "source": "GLA", + "target": "Raffinose_simple_molecule", + "sign": true + }, + { + "id": "t202", + "source": "Stachyose_simple_molecule", + "target": "Raffinose_simple_molecule", + "sign": true + }, + { + "id": "t203", + "source": "H2O_simple_molecule_cell", + "target": "Raffinose_simple_molecule", + "sign": true + }, + { + "id": "t204", + "source": "GLA:Nsp14_complex", + "target": "Sucrose_simple_molecule", + "sign": true + }, + { + "id": "t205", + "source": "Migalastat_drug", + "target": "Sucrose_simple_molecule", + "sign": true + }, + { + "id": "t206", + "source": "GLA", + "target": "Sucrose_simple_molecule", + "sign": true + }, + { + "id": "t207", + "source": "Raffinose_simple_molecule", + "target": "Sucrose_simple_molecule", + "sign": true + }, + { + "id": "t208", + "source": "H2O_simple_molecule_cell", + "target": "Sucrose_simple_molecule", + "sign": true + }, + { + "id": "t209", + "source": "PNP", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t210", + "source": "CD38", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t211", + "source": "NADP_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t212", + "source": "Pi_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t213", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t214", + "source": "H2O_simple_molecule_mitochondrion", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t215", + "source": "Nicotinate_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t216", + "source": "NAD_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t217", + "source": "SIRT5", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t218", + "source": "N-Ribosyl-nicotinamide_simple_molecule", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t219", + "source": "SIRT5:Nsp14_complex", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t220", + "source": "H2O_simple_molecule_cell", + "target": "Nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t221", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "target": "N-Ribosyl-nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t222", + "source": "H2O_simple_molecule_cell", + "target": "N-Ribosyl-nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t223", + "source": "NT5E", + "target": "N-Ribosyl-nicotinamide_simple_molecule", + "sign": true + }, + { + "id": "t224", + "source": "Nicotinamide_simple_molecule", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t225", + "source": "NAD_simple_molecule", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t226", + "source": "ENPP1", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t227", + "source": "N-Ribosyl-nicotinamide_simple_molecule", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t228", + "source": "ENPP3", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t229", + "source": "NRK1", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t230", + "source": "NAMPT", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t231", + "source": "ATP_simple_molecule", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t232", + "source": "H2O_simple_molecule_cell", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t233", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "Nicotinamide D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t234", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t235", + "source": "NMNAT2", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t236", + "source": "H_simple_molecule", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t237", + "source": "L-Glutamine_simple_molecule", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t238", + "source": "NMNAT3", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t239", + "source": "NMNAT1", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t240", + "source": "NADSYN1", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t241", + "source": "ATP_simple_molecule", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t242", + "source": "H2O_simple_molecule_cell", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t243", + "source": "Deamino-NAD_simple_molecule", + "target": "NAD_simple_molecule", + "sign": true + }, + { + "id": "t244", + "source": "NMNAT2", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t245", + "source": "H_simple_molecule", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t246", + "source": "NMNAT3", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t247", + "source": "NMNAT1", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t248", + "source": "Nicotinate D-ribonucleotide_simple_molecule", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t249", + "source": "ATP_simple_molecule", + "target": "Deamino-NAD_simple_molecule", + "sign": true + }, + { + "id": "t250", + "source": "H_simple_molecule", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t251", + "source": "NAPRT1", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t252", + "source": "Nicotinate_simple_molecule", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t253", + "source": "Quinolinate_simple_molecule", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t254", + "source": "ATP_simple_molecule", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t255", + "source": "QPRT", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t256", + "source": "H2O_simple_molecule_cell", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t257", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "Nicotinate D-ribonucleotide_simple_molecule", + "sign": true + }, + { + "id": "t258", + "source": "Mycophenolic acid_drug", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t259", + "source": "IMPDH1", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t260", + "source": "NADPH_simple_molecule", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t261", + "source": "Hypoxanthine_simple_molecule", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t262", + "source": "Ribavirin_drug", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t263", + "source": "NNT", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t264", + "source": "IMPDH2:Nsp14_complex", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t265", + "source": "XDH", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t266", + "source": "Merimepodib_drug", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t267", + "source": "NAD_simple_molecule", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t268", + "source": "IMPDH2", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t269", + "source": "IMP_simple_molecule", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t270", + "source": "H2O_simple_molecule_cell", + "target": "NADH_simple_molecule", + "sign": true + }, + { + "id": "t271", + "source": "L-Glutamine_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t272", + "source": "NADSYN1", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t273", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t274", + "source": "XMP_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t275", + "source": "PPAT", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t276", + "source": "PFAS", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t277", + "source": "GMPS", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t278", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t279", + "source": "ATP_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t280", + "source": "H2O_simple_molecule_cell", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t281", + "source": "Deamino-NAD_simple_molecule", + "target": "L-Glutamate_simple_molecule", + "sign": true + }, + { + "id": "t282", + "source": "ADK", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t283", + "source": "NAD_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t284", + "source": "Adenosine_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t285", + "source": "GMPS", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t286", + "source": "APRT", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t287", + "source": "ATP_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t288", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t289", + "source": "PRPS2", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t290", + "source": "Adenine_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t291", + "source": "D-Ribose 5P_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t292", + "source": "PRPS1", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t293", + "source": "L-Glutamine_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t294", + "source": "ENPP1", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t295", + "source": "ENPP3", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t296", + "source": "XMP_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t297", + "source": "PRPS1L1", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t298", + "source": "H2O_simple_molecule_cell", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t299", + "source": "PNP", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t300", + "source": "GTP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t301", + "source": "GMP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t302", + "source": "ENTPD5", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t303", + "source": "NT5E", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t304", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t305", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t306", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t307", + "source": "L-Aspartate_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t308", + "source": "Hypoxanthine_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t309", + "source": "AMP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t310", + "source": "CANT1", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t311", + "source": "L-Glutamine_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t312", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t313", + "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t314", + "source": "PFAS", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t315", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t316", + "source": "H2O_simple_molecule_cell", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t317", + "source": "ENTPD4", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t318", + "source": "ENTPD6", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t319", + "source": "NAPRT1", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t320", + "source": "Nicotinate_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t321", + "source": "GART", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t322", + "source": "ATP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t323", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t324", + "source": "PAICS", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t325", + "source": "ENTPD2", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t326", + "source": "Glycine_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t327", + "source": "XMP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t328", + "source": "GDP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t329", + "source": "IMP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t330", + "source": "NTPCR", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t331", + "source": "CD38", + "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", + "sign": true + }, + { + "id": "t332", + "source": "NADP_simple_molecule", + "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", + "sign": true + }, + { + "id": "t333", + "source": "Nicotinate_simple_molecule", + "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", + "sign": true + }, + { + "id": "t334", + "source": "D-Ribose 5P_simple_molecule", + "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "sign": true + }, + { + "id": "t335", + "source": "PRPS1", + "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "sign": true + }, + { + "id": "t336", + "source": "PRPS1L1", + "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "sign": true + }, + { + "id": "t337", + "source": "ATP_simple_molecule", + "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "sign": true + }, + { + "id": "t338", + "source": "PRPS2", + "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "sign": true + }, + { + "id": "t339", + "source": "PNP", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t340", + "source": "Pi_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t341", + "source": "Inosine_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t342", + "source": "Xanthosine_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t343", + "source": "N-Ribosyl-nicotinamide_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t344", + "source": "Adenosine_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t345", + "source": "Guanosine_simple_molecule", + "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t346", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "target": "Histone-L-lysine_simple_molecule", + "sign": true + }, + { + "id": "t347", + "source": "H2O_simple_molecule_mitochondrion", + "target": "Histone-L-lysine_simple_molecule", + "sign": true + }, + { + "id": "t348", + "source": "NAD_simple_molecule", + "target": "Histone-L-lysine_simple_molecule", + "sign": true + }, + { + "id": "t349", + "source": "SIRT5", + "target": "Histone-L-lysine_simple_molecule", + "sign": true + }, + { + "id": "t350", + "source": "SIRT5:Nsp14_complex", + "target": "Histone-L-lysine_simple_molecule", + "sign": true + }, + { + "id": "t351", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "target": "O-Acetyl-ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t352", + "source": "H2O_simple_molecule_mitochondrion", + "target": "O-Acetyl-ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t353", + "source": "NAD_simple_molecule", + "target": "O-Acetyl-ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t354", + "source": "SIRT5", + "target": "O-Acetyl-ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t355", + "source": "SIRT5:Nsp14_complex", + "target": "O-Acetyl-ADP-ribose_simple_molecule", + "sign": true + }, + { + "id": "t356", + "source": "CD38", + "target": "ADP-D-ribose_simple_molecule", + "sign": true + }, + { + "id": "t357", + "source": "H2O_simple_molecule_cell", + "target": "ADP-D-ribose_simple_molecule", + "sign": true + }, + { + "id": "t358", + "source": "NAD_simple_molecule", + "target": "ADP-D-ribose_simple_molecule", + "sign": true + }, + { + "id": "t359", + "source": "Quinolinate_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t360", + "source": "QPRT", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t361", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t362", + "source": "H_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t363", + "source": "PGM2", + "target": "D-Ribose 5P_simple_molecule", + "sign": true + }, + { + "id": "t364", + "source": "_alpha_D-Ribose 1P_simple_molecule", + "target": "D-Ribose 5P_simple_molecule", + "sign": true + }, + { + "id": "t365", + "source": "L-Glutamine_simple_molecule", + "target": "5-phospho-beta-D-ribosylamine_simple_molecule", + "sign": true + }, + { + "id": "t366", + "source": "PPAT", + "target": "5-phospho-beta-D-ribosylamine_simple_molecule", + "sign": true + }, + { + "id": "t367", + "source": "H2O_simple_molecule_cell", + "target": "5-phospho-beta-D-ribosylamine_simple_molecule", + "sign": true + }, + { + "id": "t368", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "5-phospho-beta-D-ribosylamine_simple_molecule", + "sign": true + }, + { + "id": "t369", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t370", + "source": "Glycine_simple_molecule", + "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t371", + "source": "ATP_simple_molecule", + "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t372", + "source": "GART", + "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t373", + "source": "GART", + "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t374", + "source": "10-Formyltetrahydrofolate_simple_molecule", + "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t375", + "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "sign": true + }, + { + "id": "t376", + "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "target": "Tetrahydrofolate_simple_molecule", + "sign": true + }, + { + "id": "t377", + "source": "GART", + "target": "Tetrahydrofolate_simple_molecule", + "sign": true + }, + { + "id": "t378", + "source": "ATIC", + "target": "Tetrahydrofolate_simple_molecule", + "sign": true + }, + { + "id": "t379", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "target": "Tetrahydrofolate_simple_molecule", + "sign": true + }, + { + "id": "t380", + "source": "10-Formyltetrahydrofolate_simple_molecule", + "target": "Tetrahydrofolate_simple_molecule", + "sign": true + }, + { + "id": "t381", + "source": "L-Glutamine_simple_molecule", + "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "sign": true + }, + { + "id": "t382", + "source": "PFAS", + "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "sign": true + }, + { + "id": "t383", + "source": "H2O_simple_molecule_cell", + "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "sign": true + }, + { + "id": "t384", + "source": "ATP_simple_molecule", + "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "sign": true + }, + { + "id": "t385", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "sign": true + }, + { + "id": "t386", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "target": "Aminoimidazole ribotide_simple_molecule", + "sign": true + }, + { + "id": "t387", + "source": "GART", + "target": "Aminoimidazole ribotide_simple_molecule", + "sign": true + }, + { + "id": "t388", + "source": "ATP_simple_molecule", + "target": "Aminoimidazole ribotide_simple_molecule", + "sign": true 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"1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "sign": true + }, + { + "id": "t395", + "source": "PAICS", + "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "sign": true + }, + { + "id": "t396", + "source": "ADSL", + "target": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "sign": true + }, + { + "id": "t397", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "target": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "sign": true + }, + { + "id": "t398", + "source": "ADSL", + "target": "Fumarate_simple_molecule", + "sign": true + }, + { + "id": "t399", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "target": "Fumarate_simple_molecule", + "sign": true + }, + { + "id": "t400", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "sign": true + }, + { + "id": "t401", + "source": "10-Formyltetrahydrofolate_simple_molecule", + "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "sign": true + }, + { + "id": "t402", + "source": "ATIC", + "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "sign": true + }, + { + "id": "t403", + "source": "Hypoxanthine_simple_molecule", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t404", + "source": "AMP_simple_molecule", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t405", + "source": "H_simple_molecule", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t406", + "source": "AMPD1", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t407", + "source": "AMDP2", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t408", + "source": "AMPD3", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t409", + "source": "ATIC", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t410", + "source": "HPRT1", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t411", + "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t412", + "source": "H2O_simple_molecule_cell", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t413", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "IMP_simple_molecule", + "sign": true + }, + { + "id": "t414", + "source": "Mycophenolic acid_drug", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t415", + "source": "IMPDH1", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t416", + "source": "Ribavirin_drug", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t417", + "source": "IMPDH2:Nsp14_complex", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t418", + "source": "Merimepodib_drug", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t419", + "source": "NAD_simple_molecule", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t420", + "source": "IMPDH2", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t421", + "source": "IMP_simple_molecule", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t422", + "source": "H2O_simple_molecule_cell", + "target": "XMP_simple_molecule", + "sign": true + }, + { + "id": "t423", + "source": "NADP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t424", + "source": "ENTPD4", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t425", + "source": "GTP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t426", + "source": "ENTPD6", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t427", + "source": "Guanine_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t428", + "source": "ENTPD5", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t429", + "source": "Ammonium_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t430", + "source": "HPRT1", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t431", + "source": "GMPS", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t432", + "source": "ATP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t433", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t434", + "source": "CANT1", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t435", + "source": "L-Glutamine_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t436", + "source": "GMPR2", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t437", + "source": "ENTPD2", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t438", + "source": "XMP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t439", + "source": "GMPR", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t440", + "source": "GDP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t441", + "source": "IMP_simple_molecule", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t442", + "source": "H2O_simple_molecule_cell", + "target": "GMP_simple_molecule", + "sign": true + }, + { + "id": "t443", + "source": "GTP_simple_molecule", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t444", + "source": "GMP_simple_molecule", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t445", + "source": "ENTPD2", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t446", + "source": "GUK1", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t447", + "source": "H2O_simple_molecule_cell", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t448", + "source": "ATP_simple_molecule", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t449", + "source": "NTPCR", + "target": "GDP_simple_molecule", + "sign": true + }, + { + "id": "t450", + "source": "NME6", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t451", + "source": "NME5", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t452", + "source": "Nucleoside diphosphate kinase_complex_cell", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t453", + "source": "NME7", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t454", + "source": "NME3", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t455", + "source": "GDP_simple_molecule", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t456", + "source": "ATP_simple_molecule", + "target": "GTP_simple_molecule", + "sign": true + }, + { + "id": "t457", + "source": "GDP_simple_molecule", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t458", + "source": "GUK1", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t459", + "source": "dGMP_simple_molecule", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t460", + "source": "ribonucleoside reductase_complex_cell", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t461", + "source": "ATP_simple_molecule", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t462", + "source": "Thioredoxin_simple_molecule", + "target": "dGDP_simple_molecule", + "sign": true + }, + { + "id": "t463", + "source": "GDP_simple_molecule", + "target": "Thioredoxin disulfide_simple_molecule", + "sign": true + }, + { + "id": "t464", + "source": "ribonucleoside reductase_complex_cell", + "target": "Thioredoxin disulfide_simple_molecule", + "sign": true + }, + { + "id": "t465", + "source": "Thioredoxin_simple_molecule", + "target": "Thioredoxin disulfide_simple_molecule", + "sign": true + }, + { + "id": "t466", + "source": "ADP_simple_molecule", + "target": "Thioredoxin disulfide_simple_molecule", + "sign": true + }, + { + "id": "t467", + "source": "NME6", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t468", + "source": "NME5", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t469", + "source": "Nucleoside diphosphate kinase_complex_cell", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t470", + "source": "NME7", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t471", + "source": "dGDP_simple_molecule", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t472", + "source": "NME3", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t473", + "source": "ATP_simple_molecule", + "target": "dGTP_simple_molecule", + "sign": true + }, + { + "id": "t474", + "source": "DCK", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t475", + "source": "Deoxyguanosine_simple_molecule", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t476", + "source": "ENPP1", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t477", + "source": "ENPP3", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t478", + "source": "dGTP_simple_molecule", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t479", + "source": "ATP_simple_molecule", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t480", + "source": "H2O_simple_molecule_cell", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t481", + "source": "ITPA", + "target": "dGMP_simple_molecule", + "sign": true + }, + { + "id": "t482", + "source": "PNP", + "target": "Guanine_simple_molecule", + "sign": true + }, + { + "id": "t483", + "source": "Deoxyguanosine_simple_molecule", + "target": "Guanine_simple_molecule", + "sign": true + }, + { + "id": "t484", + "source": "Pi_simple_molecule", + "target": "Guanine_simple_molecule", + "sign": true + }, + { + "id": "t485", + "source": "Guanosine_simple_molecule", + "target": "Guanine_simple_molecule", + "sign": true + }, + { + "id": "t486", + "source": "GMP_simple_molecule", + "target": "Guanosine_simple_molecule", + "sign": true + }, + { + "id": "t487", + "source": "H2O_simple_molecule_cell", + "target": "Guanosine_simple_molecule", + "sign": true + }, + { + "id": "t488", + "source": "NT5E", + "target": "Guanosine_simple_molecule", + "sign": true + }, + { + "id": "t489", + "source": "PNP", + "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t490", + "source": "Deoxyguanosine_simple_molecule", + "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t491", + "source": "Pi_simple_molecule", + "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "sign": true + }, + { + "id": "t492", + "source": "AMP_simple_molecule", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t493", + "source": "AMPD1", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t494", + "source": "H_simple_molecule", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t495", + "source": "Guanine_simple_molecule", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t496", + "source": "AMDP2", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t497", + "source": "AMPD3", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t498", + "source": "Deoxyadenosine_simple_molecule", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t499", + "source": "GDA", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t500", + "source": "Adenosine_simple_molecule", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t501", + "source": "H2O_simple_molecule_cell", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t502", + "source": "ADA", + "target": "Ammonium_simple_molecule", + "sign": true + }, + { + "id": "t503", + "source": "XMP_simple_molecule", + "target": "Xanthosine_simple_molecule", + "sign": true + }, + { + "id": "t504", + "source": "H2O_simple_molecule_cell", + "target": "Xanthosine_simple_molecule", + "sign": true + }, + { + "id": "t505", + "source": "NT5E", + "target": "Xanthosine_simple_molecule", + "sign": true + }, + { + "id": "t506", + "source": "PNP", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t507", + "source": "Hypoxanthine_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t508", + "source": "Pi_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t509", + "source": "XDH", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t510", + "source": "H_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t511", + "source": "Guanine_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t512", + "source": "Xanthosine_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t513", + "source": "NAD_simple_molecule", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t514", + "source": "GDA", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t515", + "source": "H2O_simple_molecule_cell", + "target": "Xanthine_simple_molecule", + "sign": true + }, + { + "id": "t516", + "source": "H_simple_molecule", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t517", + "source": "NT5E", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t518", + "source": "Adenosine_simple_molecule", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t519", + "source": "IMP_simple_molecule", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t520", + "source": "H2O_simple_molecule_cell", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t521", + "source": "ADA", + "target": "Inosine_simple_molecule", + "sign": true + }, + { + "id": "t522", + "source": "PNP", + "target": "Hypoxanthine_simple_molecule", + "sign": true + }, + { + "id": "t523", + "source": "Pi_simple_molecule", + "target": "Hypoxanthine_simple_molecule", + "sign": true + }, + { + "id": "t524", + "source": "Inosine_simple_molecule", + "target": "Hypoxanthine_simple_molecule", + "sign": true + }, + { + "id": "t525", + "source": "H2O_simple_molecule_cell", + "target": "Adenosine_simple_molecule", + "sign": true + }, + { + "id": "t526", + "source": "AMP_simple_molecule", + "target": "Adenosine_simple_molecule", + "sign": true + }, + { + "id": "t527", + "source": "NT5E", + "target": "Adenosine_simple_molecule", + "sign": true + }, + { + "id": "t528", + "source": "PNP", + "target": "Adenine_simple_molecule", + "sign": true + }, + { + "id": "t529", + "source": "Pi_simple_molecule", + "target": "Adenine_simple_molecule", + "sign": true + }, + { + "id": "t530", + "source": "Adenosine_simple_molecule", + "target": "Adenine_simple_molecule", + "sign": true + }, + { + "id": "t531", + "source": "Hypoxanthine_simple_molecule", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t532", + "source": "PNP", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t533", + "source": "H_simple_molecule", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t534", + "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t535", + "source": "Deoxyadenosine_simple_molecule", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t536", + "source": "H2O_simple_molecule_cell", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t537", + "source": "ADA", + "target": "Deoxyinosine_simple_molecule", + "sign": true + }, + { + "id": "t538", + "source": "Deoxyadenosine_simple_molecule", + "target": "dAMP_simple_molecule", + "sign": true + }, + { + "id": "t539", + "source": "DCK", + "target": "dAMP_simple_molecule", + "sign": true + }, + { + "id": "t540", + "source": "ATP_simple_molecule", + "target": "dAMP_simple_molecule", + "sign": true + }, + { + "id": "t541", + "source": "ribonucleoside reductase_complex_cell", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t542", + "source": "AK5", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t543", + "source": "ATP_simple_molecule", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t544", + "source": "Thioredoxin_simple_molecule", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t545", + "source": "dAMP_simple_molecule", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t546", + "source": "ADP_simple_molecule", + "target": "dADP_simple_molecule", + "sign": true + }, + { + "id": "t547", + "source": "dADP_simple_molecule", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t548", + "source": "NME6", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t549", + "source": "NME5", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t550", + "source": "Nucleoside diphosphate kinase_complex_cell", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t551", + "source": "NME7", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t552", + "source": "NME3", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t553", + "source": "ATP_simple_molecule", + "target": "dATP_simple_molecule", + "sign": true + }, + { + "id": "t554", + "source": "IMPDH2", + "target": "Guanine nucleotide synthesis_phenotype", + "sign": true + }, + { + "id": "t555", "source": "SIRT5", "target": "Urea cycle_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json index 847cfecec..be960294e 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json @@ -700,258 +700,378 @@ }, { "id": "t2", + "source": "Nsp4_cell", + "target": "Nsp3:Nsp4:Nsp6_complex", + "sign": true + }, + { + "id": "t3", + "source": "Nsp6", + "target": "Nsp3:Nsp4:Nsp6_complex", + "sign": true + }, + { + "id": "t4", + "source": "Nsp4_cell", + "target": "Nsp4_ALG11_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t5", "source": "ALG11_endoplasmic reticulum", "target": "Nsp4_ALG11_complex_endoplasmic reticulum", "sign": true }, { - "id": "t3", + "id": "t6", "source": "Nsp4:IDE_complex_cell", "target": "Nsp4_IDE_complex", "sign": true }, { - "id": "t4", + "id": "t7", "source": "DNAJC11", "target": "Nsp4:DNAJC11_complex", "sign": true }, { - "id": "t5", + "id": "t8", + "source": "Nsp4_cell", + "target": "Nsp4:DNAJC11_complex", + "sign": true + }, + { + "id": "t9", "source": "F-ATPase_complex_mitochondrial matrix", "target": "F-ATPase:Nsp6_complex", "sign": true }, { - "id": "t6", + "id": "t10", + "source": "Nsp6", + "target": "F-ATPase:Nsp6_complex", + "sign": true + }, + { + "id": "t11", "source": "Nsp4:NUP210_complex_endoplasmic reticulum", "target": "Nsp4:NUP210_complex_nucleus", "sign": true }, { - "id": "t7", + "id": "t12", + "source": "Nsp4_cell", + "target": "Nsp4:NUP210_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t13", "source": "NUP210_endoplasmic reticulum", "target": "Nsp4:NUP210_complex_endoplasmic reticulum", "sign": true }, { - "id": "t8", + "id": "t14", + "source": "Several drugs_drug", + "target": "SIGMAR1:Drugs_complex", + "sign": true + }, + { + "id": "t15", "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1:Drugs_complex", "sign": true }, { - "id": "t9", + "id": "t16", "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "target": "Nsp6:SIGMAR1_complex_nucleus", "sign": true }, { - "id": "t10", + "id": "t17", "source": "V-ATPase:Nsp6_complex_endoplasmic reticulum", "target": "V-ATPase:Nsp6_complex_endosome", "sign": true }, { - "id": "t11", + "id": "t18", "source": "Nsp4_mitochondrion", "target": "TIM complex:Nsp4_complex", "sign": true }, { - "id": "t12", + "id": "t19", + "source": "TIM complex_complex", + "target": "TIM complex:Nsp4_complex", + "sign": true + }, + { + "id": "t20", "source": "Nsp6", "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", "sign": true }, { - "id": "t13", + "id": "t21", + "source": "V-ATPase_complex_endoplasmic reticulum", + "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t22", "source": "ATP5MG", "target": "F-ATPase_complex_mitochondrial matrix", "sign": true }, { - "id": "t14", + "id": "t23", + "source": "V-type_space_proton_space_ATPase_complex", + "target": "V-ATPase_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t24", "source": "ATP6AP1", "target": "V-ATPase_complex_endoplasmic reticulum", "sign": true }, { - "id": "t15", + "id": "t25", "source": "NUP210_endoplasmic reticulum", "target": "NUP210:Selinexor_complex", "sign": true }, { - "id": "t16", + "id": "t26", + "source": "Selinexor_drug", + "target": "NUP210:Selinexor_complex", + "sign": true + }, + { + "id": "t27", "source": "ATP13A3", "target": "P-ATPase_complex_cell", "sign": true }, { - "id": "t17", + "id": "t28", + "source": "P-ATPase_complex_cell", + "target": "P-ATPase:Nsp6_complex", + "sign": true + }, + { + "id": "t29", "source": "Nsp6", "target": "P-ATPase:Nsp6_complex", "sign": true }, { - "id": "t18", + "id": "t30", "source": "Nsp4:IDE_complex_cell", "target": "Nsp4:IDE_complex_cell", "sign": true }, { - "id": "t19", + "id": "t31", + "source": "SLC6A15", + "target": "SLC6A15:Nsp6_complex", + "sign": true + }, + { + "id": "t32", "source": "Nsp6", "target": "SLC6A15:Nsp6_complex", "sign": true }, { - "id": "t20", + "id": "t33", + "source": "SLC6A15", + "target": "SLC6A15:Orf9c_complex", + "sign": true + }, + { + "id": "t34", "source": "Orf9c", "target": "SLC6A15:Orf9c_complex", "sign": true }, { - "id": "t21", + "id": "t35", + "source": "SLC6A15", + "target": "SLC6A15:M_complex", + "sign": true + }, + { + "id": "t36", "source": "M", "target": "SLC6A15:M_complex", "sign": true }, { - "id": "t22", + "id": "t37", + "source": "SLC6A15", + "target": "SLC6A15:Loratadine_complex", + "sign": true + }, + { + "id": "t38", "source": "Loratadine_drug", "target": "SLC6A15:Loratadine_complex", "sign": true }, { - "id": "t23", + "id": "t39", "source": "V-ATPase_complex_endoplasmic reticulum", "target": "V-ATPase_complex_endosome", "sign": true }, { - "id": "t24", + "id": "t40", + "source": "Bafilomycin A1_drug", + "target": "ATP6AP1:Bafilomycin A1_complex", + "sign": true + }, + { + "id": "t41", "source": "ATP6AP1", "target": "ATP6AP1:Bafilomycin A1_complex", "sign": true }, { - "id": "t25", + "id": "t42", "source": "Nsp6", "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "sign": true }, { - "id": "t26", + "id": "t43", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t44", + "source": "Nsp4_cell", + "target": "Nsp4:IDE_complex_cell", + "sign": true + }, + { + "id": "t45", "source": "IDE_cell", "target": "Nsp4:IDE_complex_cell", "sign": true }, { - "id": "t27", + "id": "t46", "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "target": "Nsp6:SIGMAR1_complex_cell", "sign": true }, { - "id": "t28", + "id": "t47", "source": "Nsp4 (-)_rna", "target": "Nsp4 (+)_rna", "sign": true }, { - "id": "t29", + "id": "t48", "source": "Nsp4 (+)_rna", "target": "Nsp4_cell", "sign": true }, { - "id": "t30", + "id": "t49", "source": "Nsp6 (-)_rna", "target": "Nsp6 (+)_rna", "sign": true }, { - "id": "t31", + "id": "t50", "source": "Nsp6 (+)_rna", "target": "Nsp6", "sign": true }, { - "id": "t32", + "id": "t51", "source": "IDE_cell", "target": "IDE_human host", "sign": true }, { - "id": "t33", + "id": "t52", "source": "Nsp3 (-)_rna", "target": "Nsp3 (+)_rna", "sign": true }, { - "id": "t34", + "id": "t53", "source": "Nsp3 (+)_rna", "target": "Nsp3", "sign": true }, { - "id": "t35", + "id": "t54", "source": "Nsp3:Nsp4:Nsp6_complex", "target": "Plasma membrane organization_phenotype", "sign": true }, { - "id": "t36", + "id": "t55", + "source": "TOM complex_complex", + "target": "Nsp4_mitochondrion", + "sign": true + }, + { + "id": "t56", "source": "Nsp4_cell", "target": "Nsp4_mitochondrion", "sign": true }, { - "id": "t37", + "id": "t57", "source": "Nsp6 (+)_rna", "target": "Nsp6 (-)_rna", "sign": true }, { - "id": "t38", + "id": "t58", "source": "Nsp3 (+)_rna", "target": "Nsp3 (-)_rna", "sign": true }, { - "id": "t39", + "id": "t59", "source": "Nsp4 (+)_rna", "target": "Nsp4 (-)_rna", "sign": true }, { - "id": "t40", + "id": "t60", "source": "NUP210_endoplasmic reticulum", "target": "NUP210_nucleus", "sign": true }, { - "id": "t41", + "id": "t61", "source": "IDE_cell", "target": "IDE_cell", "sign": true }, { - "id": "t42", + "id": "t62", "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1_nucleus", "sign": true }, { - "id": "t43", + "id": "t63", "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1_cell", "sign": true }, { - "id": "t44", + "id": "t64", "source": "V-type_space_proton_space_ATPase_complex", "target": "H+_ion", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json index ab479d22f..60e27a51c 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json @@ -2518,714 +2518,1536 @@ "edges": [ { "id": "t1", - "source": "Fibrillin_complex_human host", + "source": "Nsp9_cell", "target": "Fibrillincomp_complex", "sign": true }, { "id": "t2", - "source": "Nsp9_cell", - "target": "Nuclear Pore comp_complex", + "source": "Fibrillin_complex_human host", + "target": "Fibrillincomp_complex", "sign": true }, { "id": "t3", - "source": "MIB1", - "target": "MIBcomp_complex", + "source": "PLG", + "target": "Fibrillincomp_complex", "sign": true }, { "id": "t4", - "source": "COPS_complex_nucleus", - "target": "COPS_complex_nucleus", + "source": "FBLN5", + "target": "Fibrillincomp_complex", "sign": true }, { "id": "t5", - "source": "Phosphatidyl serine_simple_molecule", - "target": "lipidcomp_complex", + "source": "Nsp9_cell", + "target": "Nuclear Pore comp_complex", "sign": true }, { "id": "t6", - "source": "MAT1A", - "target": "SAdComp_complex", + "source": "Nuclear Pore_complex", + "target": "Nuclear Pore comp_complex", "sign": true }, { "id": "t7", - "source": "nup1_complex", - "target": "Nuclear Pore_complex", + "source": "MIB1", + "target": "MIBcomp_complex", "sign": true }, { "id": "t8", - "source": "Nsp8", - "target": "EXOCcomp_complex", + "source": "DLL1", + "target": "MIBcomp_complex", "sign": true }, { "id": "t9", - "source": "GTF2F2", - "target": "gtf2f2comp_complex", + "source": "Vpr", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t10", - "source": "EDN1-homo_complex_human host", - "target": "EDN1-homo_complex_cell", + "source": "COPS_complex_nucleus", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t11", - "source": "MIB1", - "target": "mibcomp_complex", + "source": "SCARB1", + "target": "lipidcomp_complex", "sign": true }, { "id": "t12", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_human host", + "source": "Phosphatidyl serine_simple_molecule", + "target": "lipidcomp_complex", "sign": true }, { "id": "t13", - "source": "Nsp9_nucleus", - "target": "znfcomp_complex", + "source": "S-Adenosylmethionine_drug", + "target": "SAdComp_complex", "sign": true }, { "id": "t14", - "source": "Nsp8", - "target": "Nsp7812_complex_cell", + "source": "MAT1A", + "target": "SAdComp_complex", "sign": true }, { "id": "t15", - "source": "Nsp7812_complex_cell", - "target": "Nsp7812_complex_cell", + "source": "nup1_complex", + "target": "Nuclear Pore_complex", "sign": true }, { "id": "t16", - "source": "NUP54", - "target": "nup1_complex", + "source": "nup2_complex", + "target": "Nuclear Pore_complex", "sign": true }, { "id": "t17", - "source": "NUP88", - "target": "nup2_complex", + "source": "EXOSC2", + "target": "EXOCcomp_complex", "sign": true }, { "id": "t18", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_nucleus", + "source": "Nsp8", + "target": "EXOCcomp_complex", "sign": true }, { "id": "t19", - "source": "NEK6", - "target": "NEKs_complex", + "source": "EXOSC5", + "target": "EXOCcomp_complex", "sign": true }, { "id": "t20", - "source": "GTF2F2", - "target": "gtfrnapoly_complex", + "source": "EXOSC3", + "target": "EXOCcomp_complex", "sign": true }, { "id": "t21", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_endoplasmic reticulum", + "source": "EXOSC8", + "target": "EXOCcomp_complex", "sign": true }, { "id": "t22", - "source": "EDN1", - "target": "EDN1-homo_complex_nucleus", + "source": "GTF2F2", + "target": "gtf2f2comp_complex", "sign": true }, { "id": "t23", - "source": "EIF4H", - "target": "eifcomp_complex", + "source": "Nsp9_nucleus", + "target": "gtf2f2comp_complex", "sign": true }, { "id": "t24", - "source": "COPS2", - "target": "COPS_complex_nucleus", + "source": "EDN1-homo_complex_human host", + "target": "EDN1-homo_complex_cell", "sign": true }, { "id": "t25", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_nucleus", + "source": "EDNRA", + "target": "EDN1-homo_complex_cell", "sign": true }, { "id": "t26", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_nucleus", + "source": "Nsp9_cell", + "target": "mibcomp_complex", "sign": true }, { "id": "t27", - "source": "EDN1-homo_complex_nucleus", - "target": "EDN1-homo_complex_endoplasmic reticulum", + "source": "MIB1", + "target": "mibcomp_complex", "sign": true }, { "id": "t28", - "source": "GTF2F2", - "target": "TAT-HIV_complex", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_human host", "sign": true }, { "id": "t29", - "source": "DCAF7", - "target": "dcafcomp_complex", + "source": "Nsp9_nucleus", + "target": "znfcomp_complex", "sign": true }, { "id": "t30", - "source": "AIFM1", - "target": "SPARTcomp_complex", + "source": "ZNF503", + "target": "znfcomp_complex", "sign": true }, { "id": "t31", - "source": "Nsp9_cell", - "target": "pathogen_complex", + "source": "Nsp8", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t32", - "source": "CA12", - "target": "HCTcomp_complex", + "source": "Nsp7", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t33", - "source": "Nsp8", - "target": "FOCADcomp_complex", + "source": "Nsp12", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t34", - "source": "Nsp9_cell", - "target": "spartcomp_complex", + "source": "Nsp7812_complex_cell", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t35", - "source": "homodimer_complex", - "target": "RNArecognition_complex", + "source": "remdesivir _drug", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t36", - "source": "MAT2B", - "target": "mat2bcomp_complex", + "source": "RdRpassembled_rna", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t37", - "source": "MAT2A", - "target": "SAdComp2_complex", + "source": "favipiravir_drug", + "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t38", - "source": "PTGS2", - "target": "PTGScomp_complex", + "source": "NUP62", + "target": "nup1_complex", "sign": true }, { "id": "t39", - "source": "Nsp7", - "target": "RHOA7comp_complex", + "source": "NUP58", + "target": "nup1_complex", "sign": true }, { "id": "t40", - "source": "MAT2B", - "target": "MAT_complex", + "source": "NUP54", + "target": "nup1_complex", "sign": true }, { "id": "t41", - "source": "MAT2B", - "target": "NEC1_complex", + "source": "NUP88", + "target": "nup2_complex", "sign": true }, { "id": "t42", - "source": "AIFM1", - "target": "AIFMFlaComp_complex", + "source": "NUP214", + "target": "nup2_complex", "sign": true }, { "id": "t43", - "source": "EDNRA", - "target": "EDNRASitaComp_complex", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t44", - "source": "Ambrisentan_drug", - "target": "EDNRAmbComp_complex", + "source": "BAG6", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t45", - "source": "Acetylsalicylic acid_drug", - "target": "EDNRAcetComp_complex", + "source": "NEK6", + "target": "NEKs_complex", "sign": true }, { "id": "t46", - "source": "EDNRA", - "target": "EDNRMacComp_complex", + "source": "NEK7", + "target": "NEKs_complex", "sign": true }, { "id": "t47", - "source": "Pyridoxal phosphate_simple_molecule", - "target": "SPcomp_complex", + "source": "NEK9", + "target": "NEKs_complex", "sign": true }, { "id": "t48", - "source": "MYCBP2", - "target": "MYCBPcomp_complex", + "source": "POLR2E", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t49", - "source": "Nsp12", - "target": "SBNOcomp_complex", + "source": "POLR2B", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t50", - "source": "BCKDK", - "target": "s389_complex", + "source": "POLR2A", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t51", - "source": "ADP_simple_molecule", - "target": "ADPcomp_complex", + "source": "GTF2F2", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t52", - "source": "DCAF7", - "target": "dcafznf_complex", + "source": "GTF2B", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t53", - "source": "Nsp12", - "target": "RBMcomp_complex", + "source": "POLR2G", + "target": "gtfrnapoly_complex", "sign": true }, { "id": "t54", - "source": "Nsp12", - "target": "ZNFcomp_complex", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_endoplasmic reticulum", "sign": true }, { "id": "t55", - "source": "LARP4B ", - "target": "LARPcomp_complex", + "source": "EDN1", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t56", - "source": "Nsp8", - "target": "SRP54comp_complex", + "source": "EIF4H", + "target": "eifcomp_complex", "sign": true }, { "id": "t57", - "source": "Nsp12", - "target": "ZC3H7Acomp_complex", + "source": "Nsp9_nucleus", + "target": "eifcomp_complex", "sign": true }, { "id": "t58", - "source": "Insulin", - "target": "NECINsComp_complex", + "source": "COPS5", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t59", - "source": "Nsp7", - "target": "SCARB1_complex", + "source": "COPS4", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t60", - "source": "CA12", - "target": "CA12comp_complex", + "source": "COPS8", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t61", - "source": "CA12", - "target": "ZonisamideComp_complex", + "source": "COPS2", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t62", - "source": "CA12", - "target": "EAcomp_complex", + "source": "COPS7A", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t63", - "source": "CA12", - "target": "HFTcomp_complex", + "source": "COPS6", + "target": "COPS_complex_nucleus", "sign": true }, { "id": "t64", - "source": "Benzthiazide_drug", - "target": "BZcomp_complex", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t65", - "source": "AP2A2", - "target": "AP2A2comp_complex", + "source": "COPS6", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t66", - "source": "Fibrillin_complex_human host", - "target": "Fibrillin_complex_human host", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t67", - "source": "ELN", - "target": "RofecoxibComp_complex", + "source": "UBQLN4", + "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t68", - "source": "Nsp8", - "target": "NspComp_complex", + "source": "EDN1-homo_complex_nucleus", + "target": "EDN1-homo_complex_endoplasmic reticulum", "sign": true }, { "id": "t69", - "source": "ENV", - "target": "NECENVComp_complex", + "source": "TAT", + "target": "TAT-HIV_complex", "sign": true }, { "id": "t70", - "source": "CYB5R3", - "target": "NADHcomp_complex", + "source": "GTF2F2", + "target": "TAT-HIV_complex", "sign": true }, { "id": "t71", - "source": "CYB5R3", - "target": "CYB5R3comp_complex", + "source": "DCAF7", + "target": "dcafcomp_complex", "sign": true }, { "id": "t72", - "source": "CYB5R3", - "target": "FADcomp_complex", + "source": "Nsp9_nucleus", + "target": "dcafcomp_complex", "sign": true }, { "id": "t73", - "source": "COMT", - "target": "COMT_complex", + "source": "AIFM1", + "target": "SPARTcomp_complex", "sign": true }, { "id": "t74", + "source": "SPART", + "target": "SPARTcomp_complex", + "sign": true + }, + { + "id": "t75", + "source": "Nsp16", + "target": "pathogen_complex", + "sign": true + }, + { + "id": "t76", + "source": "Nsp14_cell", + "target": "pathogen_complex", + "sign": true + }, + { + "id": "t77", + "source": "Nsp10_cell", + "target": "pathogen_complex", + "sign": true + }, + { + "id": "t78", + "source": "Nsp9_cell", + "target": "pathogen_complex", + "sign": true + }, + { + "id": "t79", + "source": "NEMF", + "target": "pathogen_complex", + "sign": true + }, + { + "id": "t80", + "source": "Hydrochlorothiazide_drug", + "target": "HCTcomp_complex", + "sign": true + }, + { + "id": "t81", + "source": "CA12", + "target": "HCTcomp_complex", + "sign": true + }, + { + "id": "t82", + "source": "FOCAD", + "target": "FOCADcomp_complex", + "sign": true + }, + { + "id": "t83", + "source": "Nsp8", + "target": "FOCADcomp_complex", + "sign": true + }, + { + "id": "t84", + "source": "Nsp7", + "target": "FOCADcomp_complex", + "sign": true + }, + { + "id": "t85", + "source": "Nsp9_cell", + "target": "spartcomp_complex", + "sign": true + }, + { + "id": "t86", + "source": "SPART", + "target": "spartcomp_complex", + "sign": true + }, + { + "id": "t87", + "source": "ssRNAoligo_rna", + "target": "RNArecognition_complex", + "sign": true + }, + { + "id": "t88", + "source": "homodimer_complex", + "target": "RNArecognition_complex", + "sign": true + }, + { + "id": "t89", + "source": "Nsp9_cell", + "target": "mat2bcomp_complex", + "sign": true + }, + { + "id": "t90", + "source": "MAT2B", + "target": "mat2bcomp_complex", + "sign": true + }, + { + "id": "t91", + "source": "S-Adenosylmethionine_drug", + "target": "SAdComp2_complex", + "sign": true + }, + { + "id": "t92", + "source": "MAT2A", + "target": "SAdComp2_complex", + "sign": true + }, + { + "id": "t93", + "source": "Rofecoxib_drug", + "target": "PTGScomp_complex", + "sign": true + }, + { + "id": "t94", + "source": "PTGS2", + "target": "PTGScomp_complex", + "sign": true + }, + { + "id": "t95", + "source": "RHOA", + "target": "RHOA7comp_complex", + "sign": true + }, + { + "id": "t96", + "source": "Nsp7", + "target": "RHOA7comp_complex", + "sign": true + }, + { + "id": "t97", + "source": "MAT1A", + "target": "MAT_complex", + "sign": true + }, + { + "id": "t98", + "source": "MAT2A", + "target": "MAT_complex", + "sign": true + }, + { + "id": "t99", + "source": "MAT2B", + "target": "MAT_complex", + "sign": true + }, + { + "id": "t100", + "source": "PCSK1", + "target": "NEC1_complex", + "sign": true + }, + { + "id": "t101", + "source": "MAT2B", + "target": "NEC1_complex", + "sign": true + }, + { + "id": "t102", + "source": "Flavin adenine dinucleotide_drug", + "target": "AIFMFlaComp_complex", + "sign": true + }, + { + "id": "t103", + "source": "AIFM1", + "target": "AIFMFlaComp_complex", + "sign": true + }, + { + "id": "t104", + "source": "Sitaxentan_drug", + "target": "EDNRASitaComp_complex", + "sign": true + }, + { + "id": "t105", + "source": "EDNRA", + "target": "EDNRASitaComp_complex", + "sign": true + }, + { + "id": "t106", + "source": "Ambrisentan_drug", + "target": "EDNRAmbComp_complex", + "sign": true + }, + { + "id": "t107", + "source": "EDNRA", + "target": "EDNRAmbComp_complex", + "sign": true + }, + { + "id": "t108", + "source": "EDNRA", + "target": "EDNRAcetComp_complex", + "sign": true + }, + { + "id": "t109", + "source": "Acetylsalicylic acid_drug", + "target": "EDNRAcetComp_complex", + "sign": true + }, + { + "id": "t110", + "source": "Macitentan_drug", + "target": "EDNRMacComp_complex", + "sign": true + }, + { + "id": "t111", + "source": "EDNRA", + "target": "EDNRMacComp_complex", + "sign": true + }, + { + "id": "t112", + "source": "SEPSECS", + "target": "SPcomp_complex", + "sign": true + }, + { + "id": "t113", + "source": "Pyridoxal phosphate_simple_molecule", + "target": "SPcomp_complex", + "sign": true + }, + { + "id": "t114", + "source": "MYCBP2", + "target": "MYCBPcomp_complex", + "sign": true + }, + { + "id": "t115", + "source": "Nsp12", + "target": "MYCBPcomp_complex", + "sign": true + }, + { + "id": "t116", + "source": "SBNO1", + "target": "SBNOcomp_complex", + "sign": true + }, + { + "id": "t117", + "source": "Nsp12", + "target": "SBNOcomp_complex", + "sign": true + }, + { + "id": "t118", + "source": "BCKDK", + "target": "s389_complex", + "sign": true + }, + { + "id": "t119", + "source": "Nsp12", + "target": "s389_complex", + "sign": true + }, + { + "id": "t120", + "source": "ADP_simple_molecule", + "target": "ADPcomp_complex", + "sign": true + }, + { + "id": "t121", + "source": "BCKDK", + "target": "ADPcomp_complex", + "sign": true + }, + { + "id": "t122", + "source": "DCAF7", + "target": "dcafznf_complex", + "sign": true + }, + { + "id": "t123", + "source": "ZNF503", + "target": "dcafznf_complex", + "sign": true + }, + { + "id": "t124", + "source": "RBM41", + "target": "RBMcomp_complex", + "sign": true + }, + { + "id": "t125", + "source": "Nsp12", + "target": "RBMcomp_complex", + "sign": true + }, + { + "id": "t126", + "source": "ZNF318", + "target": "ZNFcomp_complex", + "sign": true + }, + { + "id": "t127", + "source": "Nsp12", + "target": "ZNFcomp_complex", + "sign": true + }, + { + "id": "t128", + "source": "LARP4B ", + "target": "LARPcomp_complex", + "sign": true + }, + { + "id": "t129", + "source": "Nsp12", + "target": "LARPcomp_complex", + "sign": true + }, + { + "id": "t130", + "source": "SRP54", + "target": "SRP54comp_complex", + "sign": true + }, + { + "id": "t131", + "source": "Nsp8", + "target": "SRP54comp_complex", + "sign": true + }, + { + "id": "t132", + "source": "SRP19", + "target": "SRP54comp_complex", + "sign": true + }, + { + "id": "t133", + "source": "ZC3H7A ", + "target": "ZC3H7Acomp_complex", + "sign": true + }, + { + "id": "t134", + "source": "Nsp12", + "target": "ZC3H7Acomp_complex", + "sign": true + }, + { + "id": "t135", + "source": "PCSK1", + "target": "NECINsComp_complex", + "sign": true + }, + { + "id": "t136", + "source": "Insulin", + "target": "NECINsComp_complex", + "sign": true + }, + { + "id": "t137", + "source": "SCARB1", + "target": "SCARB1_complex", + "sign": true + }, + { + "id": "t138", + "source": "Nsp7", + "target": "SCARB1_complex", + "sign": true + }, + { + "id": "t139", + "source": "CA12", + "target": "CA12comp_complex", + "sign": true + }, + { + "id": "t140", + "source": "Nsp7", + "target": "CA12comp_complex", + "sign": true + }, + { + "id": "t141", + "source": "CA12", + "target": "ZonisamideComp_complex", + "sign": true + }, + { + "id": "t142", + "source": "Zonisamide_drug", + "target": "ZonisamideComp_complex", + "sign": true + }, + { + "id": "t143", + "source": "Ellagic Acid_drug", + "target": "EAcomp_complex", + "sign": true + }, + { + "id": "t144", + "source": "CA12", + "target": "EAcomp_complex", + "sign": true + }, + { + "id": "t145", + "source": "Hydroflumethiazide_drug", + "target": "HFTcomp_complex", + "sign": true + }, + { + "id": "t146", + "source": "CA12", + "target": "HFTcomp_complex", + "sign": true + }, + { + "id": "t147", + "source": "CA12", + "target": "BZcomp_complex", + "sign": true + }, + { + "id": "t148", + "source": "Benzthiazide_drug", + "target": "BZcomp_complex", + "sign": true + }, + { + "id": "t149", + "source": "Nsp10_cell", + "target": "AP2A2comp_complex", + "sign": true + }, + { + "id": "t150", + "source": "AP2A2", + "target": "AP2A2comp_complex", + "sign": true + }, + { + "id": "t151", + "source": "ELN", + "target": "Fibrillin_complex_human host", + "sign": true + }, + { + "id": "t152", + "source": "Fibrillin_complex_human host", + "target": "Fibrillin_complex_human host", + "sign": true + }, + { + "id": "t153", + "source": "PLG", + "target": "Fibrillin_complex_human host", + "sign": true + }, + { + "id": "t154", + "source": "ELN", + "target": "RofecoxibComp_complex", + "sign": true + }, + { + "id": "t155", + "source": "Rofecoxib_drug", + "target": "RofecoxibComp_complex", + "sign": true + }, + { + "id": "t156", + "source": "Nsp9_cell", + "target": "NspComp_complex", + "sign": true + }, + { + "id": "t157", + "source": "Nsp8", + "target": "NspComp_complex", + "sign": true + }, + { + "id": "t158", + "source": "ENV", + "target": "NECENVComp_complex", + "sign": true + }, + { + "id": "t159", + "source": "PCSK1", + "target": "NECENVComp_complex", + "sign": true + }, + { + "id": "t160", + "source": "CYB5R3", + "target": "NADHcomp_complex", + "sign": true + }, + { + "id": "t161", + "source": "NADH_simple_molecule", + "target": "NADHcomp_complex", + "sign": true + }, + { + "id": "t162", + "source": "CYB5R3", + "target": "CYB5R3comp_complex", + "sign": true + }, + { + "id": "t163", + "source": "Nsp7", + "target": "CYB5R3comp_complex", + "sign": true + }, + { + "id": "t164", + "source": "CYB5R3", + "target": "FADcomp_complex", + "sign": true + }, + { + "id": "t165", + "source": "FAD_simple_molecule", + "target": "FADcomp_complex", + "sign": true + }, + { + "id": "t166", + "source": "COMT", + "target": "COMT_complex", + "sign": true + }, + { + "id": "t167", + "source": "Nsp7", + "target": "COMT_complex", + "sign": true + }, + { + "id": "t168", + "source": "RALA", + "target": "GDPcomp_complex", + "sign": true + }, + { + "id": "t169", "source": "GDP_simple_molecule", "target": "GDPcomp_complex", "sign": true }, { - "id": "t75", + "id": "t170", + "source": "RALA", + "target": "RALAcomp_complex", + "sign": true + }, + { + "id": "t171", "source": "Nsp7", "target": "RALAcomp_complex", "sign": true }, { - "id": "t76", + "id": "t172", + "source": "Tolcapone_drug", + "target": "TCcomp_complex", + "sign": true + }, + { + "id": "t173", "source": "COMT", "target": "TCcomp_complex", "sign": true }, { - "id": "t77", + "id": "t174", "source": "COMT", "target": "NCcomp_complex", "sign": true }, { - "id": "t78", + "id": "t175", + "source": "Entacapone_drug", + "target": "NCcomp_complex", + "sign": true + }, + { + "id": "t176", "source": "3,5-Dinitrocatechol_drug", "target": "DCcomp_complex", "sign": true }, { - "id": "t79", + "id": "t177", + "source": "COMT", + "target": "DCcomp_complex", + "sign": true + }, + { + "id": "t178", + "source": "COMT", + "target": "ACcomp_complex", + "sign": true + }, + { + "id": "t179", "source": "Ademetionine_drug", "target": "ACcomp_complex", "sign": true }, { - "id": "t80", + "id": "t180", "source": "(3,4-DIHYDROXY-2-NITROPHENYL)(PHENYL)METHANONE_drug", "target": "DNCcomp_complex", "sign": true }, { - "id": "t81", + "id": "t181", + "source": "COMT", + "target": "DNCcomp_complex", + "sign": true + }, + { + "id": "t182", + "source": "COMT", + "target": "MCcomp_complex", + "sign": true + }, + { + "id": "t183", "source": "2-Methoxyestradiol_drug", "target": "MCcomp_complex", "sign": true }, { - "id": "t82", + "id": "t184", + "source": "RAB7A", + "target": "RAB7comp_complex", + "sign": true + }, + { + "id": "t185", "source": "Nsp7", "target": "RAB7comp_complex", "sign": true }, { - "id": "t83", + "id": "t186", "source": "GDP_simple_molecule", "target": "RGcomp_complex_cell", "sign": true }, { - "id": "t84", + "id": "t187", + "source": "RAB7A", + "target": "RGcomp_complex_cell", + "sign": true + }, + { + "id": "t188", + "source": "Suramin_drug", + "target": "SScomp_complex", + "sign": true + }, + { + "id": "t189", "source": "SIRT5", "target": "SScomp_complex", "sign": true }, { - "id": "t85", + "id": "t190", "source": "GDP_simple_molecule", "target": "RGcomp_complex_cell", "sign": true }, { - "id": "t86", + "id": "t191", + "source": "RHOA", + "target": "RGcomp_complex_cell", + "sign": true + }, + { + "id": "t192", + "source": "NEK9", + "target": "nek9comp_complex", + "sign": true + }, + { + "id": "t193", "source": "Nsp9_nucleus", "target": "nek9comp_complex", "sign": true }, { - "id": "t87", + "id": "t194", + "source": "MPHOSPH10", + "target": "MPHOSPHcomp_complex", + "sign": true + }, + { + "id": "t195", "source": "Nsp8", "target": "MPHOSPHcomp_complex", "sign": true }, { - "id": "t88", + "id": "t196", "source": "ACSL3", "target": "ACSLcomp_complex", "sign": true }, { - "id": "t89", + "id": "t197", + "source": "Nsp7", + "target": "ACSLcomp_complex", + "sign": true + }, + { + "id": "t198", + "source": "Mercaptopurine_drug", + "target": "IMercomp_complex", + "sign": true + }, + { + "id": "t199", "source": "IMPDH2", "target": "IMercomp_complex", "sign": true }, { - "id": "t90", + "id": "t200", + "source": "MRPS5", + "target": "MRPScomp_complex", + "sign": true + }, + { + "id": "t201", + "source": "MRPS2", + "target": "MRPScomp_complex", + "sign": true + }, + { + "id": "t202", "source": "Nsp8", "target": "MRPScomp_complex", "sign": true }, { - "id": "t91", + "id": "t203", + "source": "IMPDH2", + "target": "IRcomp_complex", + "sign": true + }, + { + "id": "t204", "source": "Ribavirin_drug", "target": "IRcomp_complex", "sign": true }, { - "id": "t92", + "id": "t205", + "source": "LOXL1", + "target": "LOXcomp_complex", + "sign": true + }, + { + "id": "t206", + "source": "PLG", + "target": "LOXcomp_complex", + "sign": true + }, + { + "id": "t207", "source": "FBLN5", "target": "LOXcomp_complex", "sign": true }, { - "id": "t93", + "id": "t208", + "source": "SEPSECS", + "target": "SEPSECScomp_complex", + "sign": true + }, + { + "id": "t209", "source": "Nsp8", "target": "SEPSECScomp_complex", "sign": true }, { - "id": "t94", + "id": "t210", "source": "Nsp8", "target": "NOL10comp_complex", "sign": true }, { - "id": "t95", + "id": "t211", + "source": "NOL10", + "target": "NOL10comp_complex", + "sign": true + }, + { + "id": "t212", + "source": "SRP72", + "target": "SRP72comp_complex", + "sign": true + }, + { + "id": "t213", "source": "Nsp7", "target": "SRP72comp_complex", "sign": true }, { - "id": "t96", + "id": "t214", + "source": "NARS2", + "target": "NLcomp_complex", + "sign": true + }, + { + "id": "t215", "source": "L-Asparagine_simple_molecule", "target": "NLcomp_complex", "sign": true }, { - "id": "t97", + "id": "t216", + "source": "SIRT5", + "target": "SIRT5comp_complex", + "sign": true + }, + { + "id": "t217", "source": "Nsp14_cell", "target": "SIRT5comp_complex", "sign": true }, { - "id": "t98", + "id": "t218", "source": "Nsp8", "target": "AATFcomp_complex", "sign": true }, { - "id": "t99", + "id": "t219", + "source": "AATF", + "target": "AATFcomp_complex", + "sign": true + }, + { + "id": "t220", "source": "IMPDH2", "target": "INPDH2comp_complex", "sign": true }, { - "id": "t100", + "id": "t221", + "source": "Nsp14_nucleus", + "target": "INPDH2comp_complex", + "sign": true + }, + { + "id": "t222", "source": "Nsp8", "target": "DDX10comp_complex", "sign": true }, { - "id": "t101", + "id": "t223", + "source": "DDX10", + "target": "DDX10comp_complex", + "sign": true + }, + { + "id": "t224", + "source": "TCF12", + "target": "TCFcomp_complex", + "sign": true + }, + { + "id": "t225", "source": "Nsp12", "target": "TCFcomp_complex", "sign": true }, { - "id": "t102", + "id": "t226", + "source": "Nsp10_nucleus", + "target": "ERGIC1comp_complex", + "sign": true + }, + { + "id": "t227", "source": "ERGIC1", "target": "ERGIC1comp_complex", "sign": true }, { - "id": "t103", + "id": "t228", "source": "GFER", "target": "GFERcomp_complex", "sign": true }, { - "id": "t104", + "id": "t229", + "source": "Nsp10_cell", + "target": "GFERcomp_complex", + "sign": true + }, + { + "id": "t230", + "source": "GFER", + "target": "FGCOMP_complex", + "sign": true + }, + { + "id": "t231", "source": "FAD_simple_molecule", "target": "FGCOMP_complex", "sign": true }, { - "id": "t105", + "id": "t232", "source": "AP2M1", "target": "AP2M1comp_complex", "sign": true }, { - "id": "t106", + "id": "t233", + "source": "Nsp10_cell", + "target": "AP2M1comp_complex", + "sign": true + }, + { + "id": "t234", "source": "Mycophenolic acid_drug", "target": "IMcomp_complex", "sign": true }, { - "id": "t107", + "id": "t235", + "source": "IMPDH2", + "target": "IMcomp_complex", + "sign": true + }, + { + "id": "t236", "source": "Nsp8", "target": "NGDNcomp_complex", "sign": true }, { - "id": "t108", + "id": "t237", + "source": "NGDN", + "target": "NGDNcomp_complex", + "sign": true + }, + { + "id": "t238", + "source": "CCDC86", + "target": "CCDCcomp_complex", + "sign": true + }, + { + "id": "t239", "source": "Nsp8", "target": "CCDCcomp_complex", "sign": true }, { - "id": "t109", + "id": "t240", "source": "Nsp8", "target": "MEPCEcomp_complex", "sign": true }, { - "id": "t110", + "id": "t241", + "source": "LARP7", + "target": "MEPCEcomp_complex", + "sign": true + }, + { + "id": "t242", + "source": "MEPCE", + "target": "MEPCEcomp_complex", + "sign": true + }, + { + "id": "t243", "source": "Nsp9_cell", "target": "homodimer_complex", "sign": true }, { - "id": "t111", + "id": "t244", + "source": "NARS2", + "target": "NARS2comp_complex", + "sign": true + }, + { + "id": "t245", "source": "Nsp8", "target": "NARS2comp_complex", "sign": true }, { - "id": "t112", + "id": "t246", + "source": "ZNF250", + "target": "ZNF250comp_complex", + "sign": true + }, + { + "id": "t247", "source": "Nsp14_nucleus", "target": "ZNF250comp_complex", "sign": true }, { - "id": "t113", + "id": "t248", "source": "Nsp14_cell", "target": "PEG10comp_complex", "sign": true }, { - "id": "t114", + "id": "t249", + "source": "PEG10", + "target": "PEG10comp_complex", + "sign": true + }, + { + "id": "t250", "source": "EDN1_rna", "target": "EDN1", "sign": true }, { - "id": "t115", + "id": "t251", "source": "DCAF7", "target": "EDN1_rna", "sign": true }, { - "id": "t116", + "id": "t252", "source": "Nsp7812_complex_cell", "target": "virus_replication_phenotype", "sign": true }, { - "id": "t117", + "id": "t253", "source": "pathogen_complex", "target": "Neutrophil_activation_phenotype", "sign": true }, { - "id": "t118", + "id": "t254", "source": "Mycophenolate mofetil_drug", "target": "Mycophenolic acid_drug", "sign": true }, { - "id": "t119", + "id": "t255", + "source": "PLAT", + "target": "PLG", + "sign": true + }, + { + "id": "t256", "source": "Nafamostat_drug", "target": "PLG", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json index 1eb47a8ba..a2815c607 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json @@ -614,255 +614,615 @@ "edges": [ { "id": "t1", - "source": "CSN5_complex", + "source": "Cul2 ubiquitin ligase:Orf10_complex", "target": "Cul2 ubiquitin ligase_complex", "sign": true }, { "id": "t2", + "source": "Rbx1:Cul2_complex", + "target": "Cul2 ubiquitin ligase_complex", + "sign": true + }, + { + "id": "t3", + "source": "Cul2 ubiquitin ligase:N8_complex", + "target": "Cul2 ubiquitin ligase_complex", + "sign": true + }, + { + "id": "t4", + "source": "Zyg11B:EloBC_complex", + "target": "Cul2 ubiquitin ligase_complex", + "sign": true + }, + { + "id": "t5", + "source": "CSN5_complex", + "target": "Cul2 ubiquitin ligase_complex", + "sign": true + }, + { + "id": "t6", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "target": "Cul2 ubiquitin ligase_complex", + "sign": true + }, + { + "id": "t7", + "source": "ELOB:ELOC_complex", + "target": "Zyg11B:EloBC_complex", + "sign": true + }, + { + "id": "t8", + "source": "Cul2 ubiquitin ligase_complex", + "target": "Zyg11B:EloBC_complex", + "sign": true + }, + { + "id": "t9", "source": "ZYG11B", "target": "Zyg11B:EloBC_complex", "sign": true }, { - "id": "t3", + "id": "t10", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "target": "Cul2 ubiquitin ligase:Orf10_complex", + "sign": true + }, + { + "id": "t11", + "source": "Cul2 ubiquitin ligase_complex", + "target": "Cul2 ubiquitin ligase:Orf10_complex", + "sign": true + }, + { + "id": "t12", "source": "Orf10", "target": "Cul2 ubiquitin ligase:Orf10_complex", "sign": true }, { - "id": "t4", + "id": "t13", + "source": "Cul2 ubiquitin ligase:N8:Orf10_complex", + "target": "Cul2 ubiquitin ligase:Orf10_complex", + "sign": true + }, + { + "id": "t14", + "source": "CSN5_complex", + "target": "Cul2 ubiquitin ligase:Orf10_complex", + "sign": true + }, + { + "id": "t15", "source": "Cul2 ubiquitin ligase_complex", "target": "Cul2 ubiquitin ligase:substrate_complex_cell", "sign": true }, { - "id": "t5", + "id": "t16", + "source": "ubit_traget", + "target": "Cul2 ubiquitin ligase:substrate_complex_cell", + "sign": true + }, + { + "id": "t17", + "source": "Zyg11B:EloBC_complex", + "target": "ELOB:ELOC_complex", + "sign": true + }, + { + "id": "t18", "source": "ELOB", "target": "ELOB:ELOC_complex", "sign": true }, { - "id": "t6", + "id": "t19", + "source": "ELOC", + "target": "ELOB:ELOC_complex", + "sign": true + }, + { + "id": "t20", + "source": "NAE_complex", + "target": "NAE:Pevonedistat_complex", + "sign": true + }, + { + "id": "t21", "source": "Pevonedistat_drug", "target": "NAE:Pevonedistat_complex", "sign": true }, { - "id": "t7", + "id": "t22", "source": "NEDD8", "target": "NAE:NEDD8_complex", "sign": true }, { - "id": "t8", + "id": "t23", + "source": "NAE_complex", + "target": "NAE:NEDD8_complex", + "sign": true + }, + { + "id": "t24", "source": "CUL2", "target": "Rbx1:Cul2_complex", "sign": true }, { - "id": "t9", + "id": "t25", + "source": "Cul2 ubiquitin ligase_complex", + "target": "Rbx1:Cul2_complex", + "sign": true + }, + { + "id": "t26", + "source": "RBX1", + "target": "Rbx1:Cul2_complex", + "sign": true + }, + { + "id": "t27", "source": "Cul2 ubiquitin ligase:Orf10_complex", "target": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "sign": true }, { - "id": "t10", + "id": "t28", + "source": "ubit_traget", + "target": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "sign": true + }, + { + "id": "t29", "source": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:E2:substrate-Ub_complex", "sign": true }, { - "id": "t11", + "id": "t30", "source": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "target": "Cul2 ubiquitin ligase:substrate_complex_cell", "sign": true }, { - "id": "t12", + "id": "t31", + "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", + "target": "Cul2 ubiquitin ligase:substrate_complex_cell", + "sign": true + }, + { + "id": "t32", + "source": "UBE2M:NEDD8_complex", + "target": "Cul2 ubiquitin ligase:substrate_complex_cell", + "sign": true + }, + { + "id": "t33", "source": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:E2:substrate-Ub_complex", "sign": true }, { - "id": "t13", + "id": "t34", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "target": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", + "sign": true + }, + { + "id": "t35", "source": "E2_ubiquitinated", "target": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "sign": true }, { - "id": "t14", + "id": "t36", "source": "Cul2 ubiquitin ligase:N8:E2:substrate-Ub_complex", "target": "Cul2 ubiquitin ligase:N8:substrate-Ub_complex", "sign": true }, { - "id": "t15", + "id": "t37", "source": "Cul2 ubiquitin ligase:N8:substrate-Ub_complex", "target": "Cul2 ubiquitin ligase:N8_complex", "sign": true }, { - "id": "t16", + "id": "t38", "source": "E2", "target": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", "sign": true }, { - "id": "t17", + "id": "t39", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "target": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", + "sign": true + }, + { + "id": "t40", "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate-Ub_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10_complex", "sign": true }, { - "id": "t18", + "id": "t41", + "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "target": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", + "sign": true + }, + { + "id": "t42", "source": "E2_ubiquitinated", "target": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", "sign": true }, { - "id": "t19", + "id": "t43", + "source": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", + "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "sign": true + }, + { + "id": "t44", "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "sign": true }, { - "id": "t20", + "id": "t45", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "sign": true + }, + { + "id": "t46", + "source": "UBE2M:NEDD8_complex", + "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "sign": true + }, + { + "id": "t47", + "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "target": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", + "sign": true + }, + { + "id": "t48", "source": "E2", "target": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", "sign": true }, { - "id": "t21", + "id": "t49", "source": "UBE2M", "target": "UBE2M:NEDD8_complex", "sign": true }, { - "id": "t22", + "id": "t50", + "source": "NAE:NEDD8_complex", + "target": "UBE2M:NEDD8_complex", + "sign": true + }, + { + "id": "t51", + "source": "NAE:Pevonedistat_complex", + "target": "NAE_complex", + "sign": true + }, + { + "id": "t52", "source": "NAE1", "target": "NAE_complex", "sign": true }, { - "id": "t23", + "id": "t53", + "source": "UBA3", + "target": "NAE_complex", + "sign": true + }, + { + "id": "t54", + "source": "ELOB:ELOC_complex", + "target": "ELOB", + "sign": true + }, + { + "id": "t55", "source": "ELOB_rna", "target": "ELOB", "sign": true }, { - "id": "t24", + "id": "t56", "source": "ELOC_rna", "target": "ELOC", "sign": true }, { - "id": "t25", + "id": "t57", + "source": "ELOB:ELOC_complex", + "target": "ELOC", + "sign": true + }, + { + "id": "t58", + "source": "Zyg11B:EloBC_complex", + "target": "ZYG11B", + "sign": true + }, + { + "id": "t59", "source": "ZYG11B_rna", "target": "ZYG11B", "sign": true }, { - "id": "t26", + "id": "t60", "source": "RBX1_rna", "target": "RBX1", "sign": true }, { - "id": "t27", + "id": "t61", + "source": "Rbx1:Cul2_complex", + "target": "RBX1", + "sign": true + }, + { + "id": "t62", + "source": "Rbx1:Cul2_complex", + "target": "CUL2", + "sign": true + }, + { + "id": "t63", "source": "CUL2_rna", "target": "CUL2", "sign": true }, { - "id": "t28", + "id": "t64", "source": "E1_rna", "target": "E1", "sign": true }, { - "id": "t29", + "id": "t65", + "source": "E2", + "target": "E1", + "sign": true + }, + { + "id": "t66", + "source": "E1_ubiquitinated", + "target": "E1", + "sign": true + }, + { + "id": "t67", "source": "E2_rna", "target": "E2", "sign": true }, { - "id": "t30", + "id": "t68", + "source": "Cul2 ubiquitin ligase:N8:E2:substrate-Ub_complex", + "target": "E2", + "sign": true + }, + { + "id": "t69", + "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", + "target": "E2", + "sign": true + }, + { + "id": "t70", + "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", + "target": "E2", + "sign": true + }, + { + "id": "t71", "source": "DUB_rna", "target": "DUB", "sign": true }, { - "id": "t31", + "id": "t72", "source": "E1", "target": "E1_ubiquitinated", "sign": true }, { - "id": "t32", + "id": "t73", + "source": "Ub_simple_molecule", + "target": "E1_ubiquitinated", + "sign": true + }, + { + "id": "t74", + "source": "ATP_simple_molecule", + "target": "E1_ubiquitinated", + "sign": true + }, + { + "id": "t75", + "source": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", + "target": "E2_ubiquitinated", + "sign": true + }, + { + "id": "t76", + "source": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", + "target": "E2_ubiquitinated", + "sign": true + }, + { + "id": "t77", + "source": "E2", + "target": "E2_ubiquitinated", + "sign": true + }, + { + "id": "t78", "source": "E1_ubiquitinated", "target": "E2_ubiquitinated", "sign": true }, { - "id": "t33", + "id": "t79", "source": "E1", "target": "AMP_simple_molecule", "sign": true }, { - "id": "t34", + "id": "t80", + "source": "Ub_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t81", + "source": "ATP_simple_molecule", + "target": "AMP_simple_molecule", + "sign": true + }, + { + "id": "t82", "source": "E1", "target": "PPi_simple_molecule", "sign": true }, { - "id": "t35", + "id": "t83", + "source": "Ub_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t84", + "source": "ATP_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t85", "source": "NAE:Pevonedistat_complex", "target": "Pevonedistat_drug", "sign": true }, { - "id": "t36", + "id": "t86", "source": "Orf10 (+)ss sgmRNA_rna", "target": "Orf10", "sign": true }, { - "id": "t37", + "id": "t87", + "source": "Cul2 ubiquitin ligase:Orf10_complex", + "target": "Orf10", + "sign": true + }, + { + "id": "t88", + "source": "UBE2M:NEDD8_complex", + "target": "UBE2M", + "sign": true + }, + { + "id": "t89", "source": "UBE2M_rna", "target": "UBE2M", "sign": true }, { - "id": "t38", + "id": "t90", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "target": "UBE2M", + "sign": true + }, + { + "id": "t91", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "target": "UBE2M", + "sign": true + }, + { + "id": "t92", + "source": "ubit_traget_ubiquitinated", + "target": "ubit_traget", + "sign": true + }, + { + "id": "t93", "source": "DUB", "target": "ubit_traget", "sign": true }, { - "id": "t39", + "id": "t94", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "target": "ubit_traget", + "sign": true + }, + { + "id": "t95", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "target": "ubit_traget", + "sign": true + }, + { + "id": "t96", "source": "NEDD8_rna", "target": "NEDD8", "sign": true }, { - "id": "t40", + "id": "t97", "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate-Ub_complex", "target": "ubit_traget_ubiquitinated", "sign": true }, { - "id": "t41", + "id": "t98", + "source": "Cul2 ubiquitin ligase:N8:substrate-Ub_complex", + "target": "ubit_traget_ubiquitinated", + "sign": true + }, + { + "id": "t99", "source": "NAE1_rna", "target": "NAE1", "sign": true }, { - "id": "t42", + "id": "t100", + "source": "NAE_complex", + "target": "NAE1", + "sign": true + }, + { + "id": "t101", "source": "UBA3_rna", "target": "UBA3", "sign": true + }, + { + "id": "t102", + "source": "NAE_complex", + "target": "UBA3", + "sign": true } ], "parameters": [] diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json index 643730547..a61878654 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json @@ -475,132 +475,264 @@ }, { "id": "t3", - "source": "MYD88", + "source": "TLR4", "target": "LPS/TLR4/MYD88_complex", "sign": true }, { "id": "t4", + "source": "IRF6", + "target": "LPS/TLR4/MYD88_complex", + "sign": true + }, + { + "id": "t5", + "source": "MYD88", + "target": "LPS/TLR4/MYD88_complex", + "sign": true + }, + { + "id": "t6", + "source": "TRAF3", + "target": "P65/P015_complex", + "sign": true + }, + { + "id": "t7", + "source": "Orf3a", + "target": "P65/P015_complex", + "sign": true + }, + { + "id": "t8", + "source": "IKBKG/IKBKB/CHUK_complex", + "target": "P65/P015_complex", + "sign": true + }, + { + "id": "t9", "source": "E", "target": "P65/P015_complex", "sign": true }, { - "id": "t5", + "id": "t10", + "source": "TRIM30a/TRIM38_complex", + "target": "TAB2/TAB3/TAK1_complex", + "sign": true + }, + { + "id": "t11", "source": "TRAF6", "target": "TAB2/TAB3/TAK1_complex", "sign": true }, { - "id": "t6", + "id": "t12", "source": "ssRNA_rna", "target": "TLR7/8/9_complex", "sign": true }, { - "id": "t7", + "id": "t13", "source": "TAB2/TAB3/TAK1_complex", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { - "id": "t8", + "id": "t14", + "source": "TRIM29", + "target": "NEMO/IKKA/IKKB_complex", + "sign": true + }, + { + "id": "t15", + "source": "TRIM14/TRIM23_complex", + "target": "NEMO/IKKA/IKKB_complex", + "sign": true + }, + { + "id": "t16", + "source": "TRIM22", + "target": "NEMO/IKKA/IKKB_complex", + "sign": true + }, + { + "id": "t17", + "source": "TRIM27/TRIM21_complex", + "target": "NEMO/IKKA/IKKB_complex", + "sign": true + }, + { + "id": "t18", + "source": "NFKB1", + "target": "NFKB1:NFKNIA_complex", + "sign": true + }, + { + "id": "t19", "source": "CACTIN", "target": "NFKB1:NFKNIA_complex", "sign": true }, { - "id": "t9", + "id": "t20", + "source": "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated", + "target": "NFKB1:NFKNIA_complex", + "sign": true + }, + { + "id": "t21", "source": "Orf3a", "target": "TRIM59", "sign": true }, { - "id": "t10", + "id": "t22", "source": "ORF8b", "target": "NLRP3", "sign": true }, { - "id": "t11", + "id": "t23", "source": "TRAF3", "target": "PYCARD_ubiquitinated_ubiquitinated_ubiquitinated", "sign": true }, { - "id": "t12", + "id": "t24", + "source": "Orf3a", + "target": "PYCARD_ubiquitinated_ubiquitinated_ubiquitinated", + "sign": true + }, + { + "id": "t25", "source": "TICAM1", "target": "TRAF3", "sign": true }, { - "id": "t13", + "id": "t26", "source": "NLRP3", "target": "CASP1", "sign": true }, { - "id": "t14", + "id": "t27", + "source": "PYCARD_ubiquitinated_ubiquitinated_ubiquitinated", + "target": "CASP1", + "sign": true + }, + { + "id": "t28", + "source": "TRIM38", + "target": "TRAF6", + "sign": true + }, + { + "id": "t29", "source": "LPS/TLR4/MYD88_complex", "target": "TRAF6", "sign": true }, { - "id": "t15", + "id": "t30", + "source": "TRIM23", + "target": "TRAF6", + "sign": true + }, + { + "id": "t31", + "source": "MYD88", + "target": "TRAF6", + "sign": true + }, + { + "id": "t32", + "source": "TRIM38", + "target": "TICAM1", + "sign": true + }, + { + "id": "t33", "source": "TLR3", "target": "TICAM1", "sign": true }, { - "id": "t16", + "id": "t34", + "source": "TRIM59", + "target": "MYD88", + "sign": true + }, + { + "id": "t35", "source": "TLR7/8/9_complex", "target": "MYD88", "sign": true }, { - "id": "t17", + "id": "t36", + "source": "NEMO/IKKA/IKKB_complex", + "target": "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated", + "sign": true + }, + { + "id": "t37", "source": "BTRC", "target": "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated", "sign": true }, { - "id": "t18", + "id": "t38", "source": "TRIM9", "target": "BTRC", "sign": true }, { - "id": "t19", + "id": "t39", "source": "TRIM39", "target": "CACTIN", "sign": true }, { - "id": "t20", + "id": "t40", "source": "Orf3a", "target": "S", "sign": true }, { - "id": "t21", + "id": "t41", "source": "TAB2/TAB3/TAK1_complex", "target": "SERPINF2", "sign": true }, { - "id": "t22", + "id": "t42", "source": "SERPINF2", "target": "IFNB1", "sign": true }, { - "id": "t23", + "id": "t43", + "source": "P65/P015_complex", + "target": "IL1b", + "sign": true + }, + { + "id": "t44", + "source": "E", + "target": "IL1b", + "sign": true + }, + { + "id": "t45", "source": "CASP1", "target": "IL1b", "sign": true }, { - "id": "t24", + "id": "t46", "source": "double-stranded RNA_rna", "target": "TLR3", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json index 094833a81..abf62bac3 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json @@ -764,267 +764,627 @@ "edges": [ { "id": "t1", - "source": "IRAK1", + "source": "MYD88", "target": "MYD88:IRAK:TRAF_complex", "sign": true }, { "id": "t2", + "source": "IRAK4", + "target": "MYD88:IRAK:TRAF_complex", + "sign": true + }, + { + "id": "t3", + "source": "IRAK1", + "target": "MYD88:IRAK:TRAF_complex", + "sign": true + }, + { + "id": "t4", + "source": "TRAF6", + "target": "MYD88:IRAK:TRAF_complex", + "sign": true + }, + { + "id": "t5", + "source": "TRAF5", + "target": "MAVS:TRAF_complex", + "sign": true + }, + { + "id": "t6", "source": "MAVS", "target": "MAVS:TRAF_complex", "sign": true }, { - "id": "t3", + "id": "t7", + "source": "TRAF2", + "target": "MAVS:TRAF_complex", + "sign": true + }, + { + "id": "t8", + "source": "TRAF6", + "target": "MAVS:TRAF_complex", + "sign": true + }, + { + "id": "t9", + "source": "TRADD", + "target": "MAVS:TRADD_complex", + "sign": true + }, + { + "id": "t10", "source": "MAVS", "target": "MAVS:TRADD_complex", "sign": true }, { - "id": "t4", + "id": "t11", "source": "TICAM1_cell", "target": "TICAM1:TRAF3:TRAF6_complex", "sign": true }, { - "id": "t5", + "id": "t12", + "source": "TRAF6", + "target": "TICAM1:TRAF3:TRAF6_complex", + "sign": true + }, + { + "id": "t13", + "source": "TICAM1_cell", + "target": "TICAM1:TRAF3:TRAF6_complex", + "sign": true + }, + { + "id": "t14", + "source": "IKBKB", + "target": "IKK Complex_complex_cell", + "sign": true + }, + { + "id": "t15", + "source": "IKBKG", + "target": "IKK Complex_complex_cell", + "sign": true + }, + { + "id": "t16", "source": "CHUK", "target": "IKK Complex_complex_cell", "sign": true }, { - "id": "t6", + "id": "t17", "source": "NFKBIA", "target": "NFKB:NFKBIA_complex_cell", "sign": true }, { - "id": "t7", + "id": "t18", + "source": "NFKB1", + "target": "NFKB:NFKBIA_complex_cell", + "sign": true + }, + { + "id": "t19", + "source": "RELA", + "target": "NFKB:NFKBIA_complex_cell", + "sign": true + }, + { + "id": "t20", "source": "Nsp3", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, { - "id": "t8", + "id": "t21", "source": "M", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, { - "id": "t9", + "id": "t22", + "source": "MAVS:TRADD_complex", + "target": "TANK:TRAF3:IKBKE_complex_cell", + "sign": true + }, + { + "id": "t23", + "source": "M", + "target": "TANK:TRAF3:IKBKE_complex_cell", + "sign": true + }, + { + "id": "t24", + "source": "TICAM1:TRAF3:TRAF6_complex", + "target": "TANK:TRAF3:IKBKE_complex_cell", + "sign": true + }, + { + "id": "t25", "source": "MAVS:TRADD_complex", "target": "RIPK1:FADD_complex", "sign": true }, { - "id": "t10", + "id": "t26", "source": "dsRNA_rna_endosome", "target": "TLR3:dsRNA_complex", "sign": true }, { - "id": "t11", + "id": "t27", + "source": "TRAF3", + "target": "TANK:TRAF3:IKBKE_complex_cell", + "sign": true + }, + { + "id": "t28", + "source": "TANK", + "target": "TANK:TRAF3:IKBKE_complex_cell", + "sign": true + }, + { + "id": "t29", "source": "IKBKE_cell", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, { - "id": "t12", + "id": "t30", + "source": "ssRNA_rna", + "target": "TLR7:ssRNA_complex", + "sign": true + }, + { + "id": "t31", "source": "TLR7", "target": "TLR7:ssRNA_complex", "sign": true }, { - "id": "t13", + "id": "t32", + "source": "ssRNA_rna", + "target": "TLR8:ssRNA_complex", + "sign": true + }, + { + "id": "t33", "source": "TLR8", "target": "TLR8:ssRNA_complex", "sign": true }, { - "id": "t14", + "id": "t34", + "source": "Nsp3", + "target": "DDX58:dsRNA_complex", + "sign": true + }, + { + "id": "t35", + "source": "M", + "target": "DDX58:dsRNA_complex", + "sign": true + }, + { + "id": "t36", "source": "DDX58", "target": "DDX58:dsRNA_complex", "sign": true }, { - "id": "t15", + "id": "t37", + "source": "dsRNA_rna_cell", + "target": "DDX58:dsRNA_complex", + "sign": true + }, + { + "id": "t38", + "source": "Nsp3", + "target": "IFIH1:dsRNA_complex", + "sign": true + }, + { + "id": "t39", + "source": "M", + "target": "IFIH1:dsRNA_complex", + "sign": true + }, + { + "id": "t40", + "source": "dsRNA_rna_cell", + "target": "IFIH1:dsRNA_complex", + "sign": true + }, + { + "id": "t41", "source": "IFIH1", "target": "IFIH1:dsRNA_complex", "sign": true }, { - "id": "t16", + "id": "t42", + "source": "Nsp15", + "target": "IFIH1:dsRNA_complex", + "sign": true + }, + { + "id": "t43", + "source": "MAP2K7_phosphorylated", + "target": "JNK_complex", + "sign": true + }, + { + "id": "t44", "source": "MAP2K4_phosphorylated", "target": "JNK_complex", "sign": true }, { - "id": "t17", + "id": "t45", + "source": "NFKB:NFKBIA_complex_cell", + "target": "NFKB_complex", + "sign": true + }, + { + "id": "t46", "source": "N", "target": "NFKB_complex", "sign": true }, { - "id": "t18", + "id": "t47", + "source": "Nsp15", + "target": "EIF2AK2:dsRNA_complex", + "sign": true + }, + { + "id": "t48", "source": "EIF2AK2", "target": "EIF2AK2:dsRNA_complex", "sign": true }, { - "id": "t19", + "id": "t49", + "source": "dsRNA_rna_cell", + "target": "EIF2AK2:dsRNA_complex", + "sign": true + }, + { + "id": "t50", "source": "IKK Complex_complex_cell", "target": "NFKB:NFKBIA_complex_cell", "sign": true }, { - "id": "t20", + "id": "t51", + "source": "TRAF6_ubiquitinated", + "target": "IKK Complex_complex_cell", + "sign": true + }, + { + "id": "t52", + "source": "M", + "target": "IKK Complex_complex_cell", + "sign": true + }, + { + "id": "t53", + "source": "CASP8", + "target": "IKK Complex_complex_cell", + "sign": true + }, + { + "id": "t54", "source": "CASP10", "target": "IKK Complex_complex_cell", "sign": true }, { - "id": "t21", + "id": "t55", + "source": "JNK_complex", + "target": "AP1_complex", + "sign": true + }, + { + "id": "t56", "source": "MAPK14_phosphorylated", "target": "AP1_complex", "sign": true }, { - "id": "t22", + "id": "t57", "source": "TLR7:ssRNA_complex", "target": "MYD88", "sign": true }, { - "id": "t23", + "id": "t58", + "source": "TLR8:ssRNA_complex", + "target": "MYD88", + "sign": true + }, + { + "id": "t59", + "source": "TLR3:dsRNA_complex", + "target": "TICAM1_cell", + "sign": true + }, + { + "id": "t60", "source": "TICAM1_cell", "target": "TICAM1_cell", "sign": true }, { - "id": "t24", + "id": "t61", "source": "TBK1_cell", "target": "TBK1_cell", "sign": true }, { - "id": "t25", + "id": "t62", + "source": "TANK:TRAF3:IKBKE_complex_cell", + "target": "TBK1_cell", + "sign": true + }, + { + "id": "t63", + "source": "Nsp3", + "target": "IKBKE_cell", + "sign": true + }, + { + "id": "t64", + "source": "TANK:TRAF3:IKBKE_complex_cell", + "target": "IKBKE_cell", + "sign": true + }, + { + "id": "t65", "source": "IKBKE_cell", "target": "IKBKE_cell", "sign": true }, { - "id": "t26", + "id": "t66", + "source": "Nsp3", + "target": "IRF3_phosphorylated_cell", + "sign": true + }, + { + "id": "t67", + "source": "Orf3b", + "target": "IRF3_phosphorylated_cell", + "sign": true + }, + { + "id": "t68", + "source": "TBK1_cell", + "target": "IRF3_phosphorylated_cell", + "sign": true + }, + { + "id": "t69", "source": "IRF3", "target": "IRF3_phosphorylated_cell", "sign": true }, { - "id": "t27", + "id": "t70", + "source": "Orf8", + "target": "IRF3_phosphorylated_cell", + "sign": true + }, + { + "id": "t71", + "source": "RNF135", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t72", + "source": "DDX58:dsRNA_complex", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t73", + "source": "TRIM25", + "target": "DDX58_ubiquitinated", + "sign": true + }, + { + "id": "t74", "source": "N", "target": "DDX58_ubiquitinated", "sign": true }, { - "id": "t28", + "id": "t75", + "source": "IFIH1:dsRNA_complex", + "target": "MAVS", + "sign": true + }, + { + "id": "t76", "source": "DDX58_ubiquitinated", "target": "MAVS", "sign": true }, { - "id": "t29", + "id": "t77", + "source": "TRAF6_ubiquitinated", + "target": "TRAF6", + "sign": true + }, + { + "id": "t78", "source": "Nsp3", "target": "TRAF6", "sign": true }, { - "id": "t30", + "id": "t79", "source": "IRF3_phosphorylated_cell", "target": "IRF3_phosphorylated_nucleus", "sign": true }, { - "id": "t31", + "id": "t80", "source": "IKBKE_cell", "target": "IRF7_phosphorylated", "sign": true }, { - "id": "t32", + "id": "t81", + "source": "MYD88:IRAK:TRAF_complex", + "target": "IRF7_phosphorylated", + "sign": true + }, + { + "id": "t82", "source": "IRF3_phosphorylated_cell", "target": "IRF3_phosphorylated_nucleus", "sign": true }, { - "id": "t33", + "id": "t83", + "source": "MAVS:TRAF_complex", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t84", + "source": "UBE2N", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t85", "source": "TRAF6", "target": "TRAF6_ubiquitinated", "sign": true }, { - "id": "t34", + "id": "t86", + "source": "MYD88:IRAK:TRAF_complex", + "target": "TRAF6_ubiquitinated", + "sign": true + }, + { + "id": "t87", "source": "TRAF6_ubiquitinated", "target": "MAP3K7", "sign": true }, { - "id": "t35", + "id": "t88", + "source": "TICAM1:TRAF3:TRAF6_complex", + "target": "MAP3K7", + "sign": true + }, + { + "id": "t89", "source": "MAP2K3_phosphorylated", "target": "MAPK14_phosphorylated", "sign": true }, { - "id": "t36", + "id": "t90", + "source": "MAP2K6_phosphorylated", + "target": "MAPK14_phosphorylated", + "sign": true + }, + { + "id": "t91", "source": "RIPK1:FADD_complex", "target": "CASP10", "sign": true }, { - "id": "t37", + "id": "t92", "source": "RIPK1:FADD_complex", "target": "CASP8", "sign": true }, { - "id": "t38", + "id": "t93", "source": "Orf9", "target": "ITCH", "sign": true }, { - "id": "t39", + "id": "t94", "source": "MAP3K7", "target": "MAP2K6_phosphorylated", "sign": true }, { - "id": "t40", + "id": "t95", + "source": "EIF2AK2:dsRNA_complex", + "target": "MAP2K6_phosphorylated", + "sign": true + }, + { + "id": "t96", "source": "MAP3K7", "target": "MAP2K3_phosphorylated", "sign": true }, { - "id": "t41", + "id": "t97", "source": "MAP3K7", "target": "MAP2K4_phosphorylated", "sign": true }, { - "id": "t42", + "id": "t98", "source": "MAP3K7", "target": "MAP2K7_phosphorylated", "sign": true }, { - "id": "t43", + "id": "t99", + "source": "NFKB:NFKBIA_complex_cell", + "target": "NFKBIA_phosphorylated", + "sign": true + }, + { + "id": "t100", "source": "N", "target": "NFKBIA_phosphorylated", "sign": true }, { - "id": "t44", + "id": "t101", "source": "IRF3_phosphorylated_nucleus", "target": "transcription of proinflammatory proteins_phenotype", "sign": true + }, + { + "id": "t102", + "source": "IRF7_phosphorylated", + "target": "transcription of proinflammatory proteins_phenotype", + "sign": true + }, + { + "id": "t103", + "source": "AP1_complex", + "target": "transcription of proinflammatory proteins_phenotype", + "sign": true + }, + { + "id": "t104", + "source": "NFKB_complex", + "target": "transcription of proinflammatory proteins_phenotype", + "sign": true } ], "parameters": [] diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json index cc19a0cc1..38a97e144 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json @@ -970,351 +970,813 @@ "edges": [ { "id": "t1", - "source": "IRF3_phosphorylated", + "source": "NF-kB_complex", "target": "IFNB1_space_expression_space_complex_complex", "sign": true }, { "id": "t2", + "source": "IRF3_phosphorylated", + "target": "IFNB1_space_expression_space_complex_complex", + "sign": true + }, + { + "id": "t3", "source": "cGAMP:STING_complex_endoplasmic reticulum", "target": "cGAMP:STING_complex_Golgi apparatus", "sign": true }, { - "id": "t3", + "id": "t4", + "source": "cGAMP_simple_molecule", + "target": "cGAMP:STING_complex_endoplasmic reticulum", + "sign": true + }, + { + "id": "t5", "source": "STING_endoplasmic reticulum", "target": "cGAMP:STING_complex_endoplasmic reticulum", "sign": true }, { - "id": "t4", + "id": "t6", "source": "cGAMP-STING_complex_COPII-coated vesicle", "target": "cGAMP-STING_complex_endoplasmic reticulum-Golgi intermediate compartment", "sign": true }, { - "id": "t5", + "id": "t7", + "source": "cGAMP-STING_complex_endoplasmic reticulum-Golgi intermediate compartment", + "target": "cGAMP:STING:LC3_complex", + "sign": true + }, + { + "id": "t8", + "source": "LC3", + "target": "cGAMP:STING:LC3_complex", + "sign": true + }, + { + "id": "t9", "source": "WIPI2", "target": "cGAMP:STING:LC3_complex", "sign": true }, { - "id": "t6", + "id": "t10", "source": "cGAS", "target": "cGAS:dsDNA_complex", "sign": true }, { - "id": "t7", + "id": "t11", + "source": "dsDNA_simple_molecule", + "target": "cGAS:dsDNA_complex", + "sign": true + }, + { + "id": "t12", "source": "MRE11", "target": "MRE11:dsDNA_complex", "sign": true }, { - "id": "t8", + "id": "t13", + "source": "dsDNA_simple_molecule", + "target": "MRE11:dsDNA_complex", + "sign": true + }, + { + "id": "t14", + "source": "cGAMP:STING_complex_Golgi apparatus", + "target": "STING:TBK1_complex_Golgi apparatus", + "sign": true + }, + { + "id": "t15", "source": "TBK1", "target": "STING:TBK1_complex_Golgi apparatus", "sign": true }, { - "id": "t9", + "id": "t16", + "source": "STING_Golgi apparatus", + "target": "STING:TBK1_complex_Golgi apparatus", + "sign": true + }, + { + "id": "t17", "source": "SAR1A", "target": "cGAMP-STING_complex_COPII-coated vesicle", "sign": true }, { - "id": "t10", + "id": "t18", + "source": "cGAMP:STING_complex_endoplasmic reticulum", + "target": "cGAMP-STING_complex_COPII-coated vesicle", + "sign": true + }, + { + "id": "t19", "source": "STING:TBK1_complex_Golgi apparatus", "target": "STING:TBK1_complex_endolysosome", "sign": true }, { - "id": "t11", + "id": "t20", "source": "MRE11:RAD50:DNA_complex_pulmonary endothelial cell", "target": "MRE11:RAD50:DNA_complex_endoplasmic reticulum", "sign": true }, { - "id": "t12", + "id": "t21", + "source": "RAD50", + "target": "MRE11:RAD50:DNA_complex_pulmonary endothelial cell", + "sign": true + }, + { + "id": "t22", "source": "MRE11:dsDNA_complex", "target": "MRE11:RAD50:DNA_complex_pulmonary endothelial cell", "sign": true }, { - "id": "t13", + "id": "t23", + "source": "N-carbamoyl-L-aspartate_simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t24", + "source": "H+simple_molecule", + "target": "H2O_simple_molecule", + "sign": true + }, + { + "id": "t25", "source": "CAD", "target": "H2O_simple_molecule", "sign": true }, { - "id": "t14", + "id": "t26", "source": "UMPS", "target": "UMP_simple_molecule", "sign": true }, { - "id": "t15", + "id": "t27", + "source": "UCK2", + "target": "UMP_simple_molecule", + "sign": true + }, + { + "id": "t28", + "source": "uridine_simple_molecule", + "target": "UMP_simple_molecule", + "sign": true + }, + { + "id": "t29", + "source": "orotidine_space_5'-monophosphate_simple_molecule", + "target": "UMP_simple_molecule", + "sign": true + }, + { + "id": "t30", + "source": "GTP_simple_molecule", + "target": "cGAMP_simple_molecule", + "sign": true + }, + { + "id": "t31", + "source": "cGAS:dsDNA_complex", + "target": "cGAMP_simple_molecule", + "sign": true + }, + { + "id": "t32", "source": "ATP_simple_molecule", "target": "cGAMP_simple_molecule", "sign": true }, { - "id": "t16", + "id": "t33", "source": "RTC and transcription pw_phenotype", "target": "RNA_space_biosynthesis_phenotype", "sign": true }, { - "id": "t17", + "id": "t34", "source": "CDP_simple_molecule", "target": "dCDP_simple_molecule", "sign": true }, { - "id": "t18", + "id": "t35", + "source": "ribonucleoside-diphosphate reductase_complex", + "target": "dCDP_simple_molecule", + "sign": true + }, + { + "id": "t36", "source": "UMP_simple_molecule", "target": "UDP_simple_molecule", "sign": true }, { - "id": "t19", + "id": "t37", + "source": "CMPK", + "target": "UDP_simple_molecule", + "sign": true + }, + { + "id": "t38", "source": "dUMP_simple_molecule", "target": "dTMP_simple_molecule", "sign": true }, { - "id": "t20", + "id": "t39", + "source": "TYMS", + "target": "dTMP_simple_molecule", + "sign": true + }, + { + "id": "t40", "source": "IFNA1_rna", "target": "IFNA1_pulmonary endothelial cell", "sign": true }, { - "id": "t21", + "id": "t41", + "source": "L-Gln_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t42", + "source": "L-Asp_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t43", + "source": "H2O_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t44", + "source": "CAD", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t45", "source": "ATP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { - "id": "t22", + "id": "t46", + "source": "CAP_simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t47", + "source": "HCO3-simple_molecule", + "target": "Pi_simple_molecule", + "sign": true + }, + { + "id": "t48", + "source": "N-carbamoyl-L-aspartate_simple_molecule", + "target": "(S)-dihydroorotate_simple_molecule", + "sign": true + }, + { + "id": "t49", + "source": "H+simple_molecule", + "target": "(S)-dihydroorotate_simple_molecule", + "sign": true + }, + { + "id": "t50", "source": "CAD", "target": "(S)-dihydroorotate_simple_molecule", "sign": true }, { - "id": "t23", + "id": "t51", + "source": "L-Gln_simple_molecule", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t52", + "source": "H2O_simple_molecule", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t53", + "source": "HCO3-simple_molecule", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t54", "source": "ATP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { - "id": "t24", + "id": "t55", + "source": "CAD", + "target": "ADP_simple_molecule", + "sign": true + }, + { + "id": "t56", + "source": "dCMP_simple_molecule", + "target": "dUMP_simple_molecule", + "sign": true + }, + { + "id": "t57", + "source": "DUT", + "target": "dUMP_simple_molecule", + "sign": true + }, + { + "id": "t58", + "source": "DCTD", + "target": "dUMP_simple_molecule", + "sign": true + }, + { + "id": "t59", "source": "dUTP_simple_molecule", "target": "dUMP_simple_molecule", "sign": true }, { - "id": "t25", + "id": "t60", + "source": "CAP_simple_molecule", + "target": "N-carbamoyl-L-aspartate_simple_molecule", + "sign": true + }, + { + "id": "t61", + "source": "L-Asp_simple_molecule", + "target": "N-carbamoyl-L-aspartate_simple_molecule", + "sign": true + }, + { + "id": "t62", "source": "CAD", "target": "N-carbamoyl-L-aspartate_simple_molecule", "sign": true }, { - "id": "t26", + "id": "t63", "source": "cytidine_simple_molecule", "target": "CMP_simple_molecule", "sign": true }, { - "id": "t27", + "id": "t64", + "source": "UCK2", + "target": "CMP_simple_molecule", + "sign": true + }, + { + "id": "t65", "source": "CMP_simple_molecule", "target": "CDP_simple_molecule", "sign": true }, { - "id": "t28", + "id": "t66", + "source": "CMPK", + "target": "CDP_simple_molecule", + "sign": true + }, + { + "id": "t67", "source": "IFNB1_pulmonary endothelial cell", "target": "IFNB1_human host", "sign": true }, { - "id": "t29", + "id": "t68", "source": "dTTP_simple_molecule", "target": "DNA_gene", "sign": true }, { - "id": "t30", + "id": "t69", + "source": "DNA_space_biosynthesis_phenotype", + "target": "DNA_gene", + "sign": true + }, + { + "id": "t70", + "source": "dsDNA_simple_molecule", + "target": "DNA_gene", + "sign": true + }, + { + "id": "t71", + "source": "virus_space_replication_phenotype", + "target": "DNA_gene", + "sign": true + }, + { + "id": "t72", "source": "dTMP_simple_molecule", "target": "dTDP_simple_molecule", "sign": true }, { - "id": "t31", + "id": "t73", + "source": "dTYMK", + "target": "dTDP_simple_molecule", + "sign": true + }, + { + "id": "t74", "source": "DNA damage_phenotype", "target": "dsDNA_simple_molecule", "sign": true }, { - "id": "t32", + "id": "t75", "source": "IFNB1_space_expression_space_complex_complex", "target": "IFNA1_rna", "sign": true }, { - "id": "t33", + "id": "t76", "source": "UDP_simple_molecule", "target": "UTP_simple_molecule", "sign": true }, { - "id": "t34", + "id": "t77", + "source": "NME1", + "target": "UTP_simple_molecule", + "sign": true + }, + { + "id": "t78", "source": "dTDP_simple_molecule", "target": "dTTP_simple_molecule", "sign": true }, { - "id": "t35", + "id": "t79", + "source": "orotate_simple_molecule", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t80", + "source": "UMPS", + "target": "PPi_simple_molecule", + "sign": true + }, + { + "id": "t81", "source": "PRPP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { - "id": "t36", + "id": "t82", + "source": "L-Gln_simple_molecule", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t83", + "source": "H2O_simple_molecule", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t84", + "source": "HCO3-simple_molecule", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t85", "source": "ATP_simple_molecule", "target": "L-Glu_simple_molecule", "sign": true }, { - "id": "t37", + "id": "t86", + "source": "CAD", + "target": "L-Glu_simple_molecule", + "sign": true + }, + { + "id": "t87", + "source": "cytidine_simple_molecule", + "target": "uridine_simple_molecule", + "sign": true + }, + { + "id": "t88", "source": "CDA", "target": "uridine_simple_molecule", "sign": true }, { - "id": "t38", + "id": "t89", "source": "IFNB1_rna", "target": "IFNB1_pulmonary endothelial cell", "sign": true }, { - "id": "t39", + "id": "t90", "source": "IFNA1_pulmonary endothelial cell", "target": "IFNA1_human host", "sign": true }, { - "id": "t40", + "id": "t91", + "source": "L-Gln_simple_molecule", + "target": "CAP_simple_molecule", + "sign": true + }, + { + "id": "t92", + "source": "H2O_simple_molecule", + "target": "CAP_simple_molecule", + "sign": true + }, + { + "id": "t93", + "source": "HCO3-simple_molecule", + "target": "CAP_simple_molecule", + "sign": true + }, + { + "id": "t94", "source": "ATP_simple_molecule", "target": "CAP_simple_molecule", "sign": true }, { - "id": "t41", + "id": "t95", + "source": "CAD", + "target": "CAP_simple_molecule", + "sign": true + }, + { + "id": "t96", "source": "dCTP_simple_molecule", "target": "dCMP_simple_molecule", "sign": true }, { - "id": "t42", + "id": "t97", + "source": "DCTPP1", + "target": "dCMP_simple_molecule", + "sign": true + }, + { + "id": "t98", "source": "MRE11:RAD50:DNA_complex_endoplasmic reticulum", "target": "STING_Golgi apparatus", "sign": true }, { - "id": "t43", + "id": "t99", + "source": "STING_endoplasmic reticulum", + "target": "STING_Golgi apparatus", + "sign": true + }, + { + "id": "t100", "source": "dCDP_simple_molecule", "target": "dCTP_simple_molecule", "sign": true }, { - "id": "t44", + "id": "t101", + "source": "NME1", + "target": "dCTP_simple_molecule", + "sign": true + }, + { + "id": "t102", "source": "STING:TBK1_complex_endolysosome", "target": "IRF3_phosphorylated", "sign": true }, { - "id": "t45", + "id": "t103", "source": "(S)-dihydroorotate_simple_molecule", "target": "QH2_simple_molecule", "sign": true }, { - "id": "t46", + "id": "t104", + "source": "Teriflunomide_drug", + "target": "QH2_simple_molecule", + "sign": true + }, + { + "id": "t105", + "source": "P1788_simple_molecule", + "target": "QH2_simple_molecule", + "sign": true + }, + { + "id": "t106", + "source": "CoQ_simple_molecule", + "target": "QH2_simple_molecule", + "sign": true + }, + { + "id": "t107", + "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", + "target": "QH2_simple_molecule", + "sign": true + }, + { + "id": "t108", + "source": "orotate_simple_molecule", + "target": "orotidine_space_5'-monophosphate_simple_molecule", + "sign": true + }, + { + "id": "t109", + "source": "UMPS", + "target": "orotidine_space_5'-monophosphate_simple_molecule", + "sign": true + }, + { + "id": "t110", "source": "PRPP_simple_molecule", "target": "orotidine_space_5'-monophosphate_simple_molecule", "sign": true }, { - "id": "t47", + "id": "t111", + "source": "NME1", + "target": "dUTP_simple_molecule", + "sign": true + }, + { + "id": "t112", "source": "dUDP_simple_molecule", "target": "dUTP_simple_molecule", "sign": true }, { - "id": "t48", + "id": "t113", "source": "(S)-dihydroorotate_simple_molecule", "target": "orotate_simple_molecule", "sign": true }, { - "id": "t49", + "id": "t114", + "source": "Teriflunomide_drug", + "target": "orotate_simple_molecule", + "sign": true + }, + { + "id": "t115", + "source": "P1788_simple_molecule", + "target": "orotate_simple_molecule", + "sign": true + }, + { + "id": "t116", + "source": "CoQ_simple_molecule", + "target": "orotate_simple_molecule", + "sign": true + }, + { + "id": "t117", + "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", + "target": "orotate_simple_molecule", + "sign": true + }, + { + "id": "t118", "source": "UMPS", "target": "CO2_simple_molecule", "sign": true }, { - "id": "t50", + "id": "t119", + "source": "orotidine_space_5'-monophosphate_simple_molecule", + "target": "CO2_simple_molecule", + "sign": true + }, + { + "id": "t120", "source": "CDP_simple_molecule", "target": "CTP_simple_molecule", "sign": true }, { - "id": "t51", + "id": "t121", + "source": "UTP_simple_molecule", + "target": "CTP_simple_molecule", + "sign": true + }, + { + "id": "t122", + "source": "NME1", + "target": "CTP_simple_molecule", + "sign": true + }, + { + "id": "t123", + "source": "CTPS1", + "target": "CTP_simple_molecule", + "sign": true + }, + { + "id": "t124", "source": "UDP_simple_molecule", "target": "dUDP_simple_molecule", "sign": true }, { - "id": "t52", + "id": "t125", + "source": "ribonucleoside-diphosphate reductase_complex", + "target": "dUDP_simple_molecule", + "sign": true + }, + { + "id": "t126", "source": "IFNB1_space_expression_space_complex_complex", "target": "IFNB1_rna", "sign": true }, { - "id": "t53", + "id": "t127", "source": "CTP_simple_molecule", "target": "RTC and transcription pw_phenotype", "sign": true }, { - "id": "t54", + "id": "t128", "source": "Teriflunomide_drug", "target": "DNA damage_phenotype", "sign": true }, { - "id": "t55", + "id": "t129", "source": "IFNA1_human host", "target": "HCoVs Type I Ifn signalling(WP4868)_phenotype", "sign": true }, { - "id": "t56", + "id": "t130", + "source": "IFNB1_human host", + "target": "HCoVs Type I Ifn signalling(WP4868)_phenotype", + "sign": true + }, + { + "id": "t131", "source": "IFNA1_human host", "target": "Interferon 1 pathway_phenotype", "sign": true }, { - "id": "t57", + "id": "t132", + "source": "IFNB1_human host", + "target": "Interferon 1 pathway_phenotype", + "sign": true + }, + { + "id": "t133", "source": "cGAMP:STING:LC3_complex", "target": "HCoVs autophagy (WP4863)_phenotype", "sign": true }, { - "id": "t58", + "id": "t134", "source": "IFNA1_human host", "target": "HCoVs IFN induction WP4880_phenotype", "sign": true + }, + { + "id": "t135", + "source": "IFNB1_human host", + "target": "HCoVs IFN induction WP4880_phenotype", + "sign": true } ], "parameters": [] diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json index f1f379488..8bec1221c 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json @@ -316,186 +316,228 @@ }, { "id": "t2", + "source": "complex_complex_cell", + "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", + "sign": true + }, + { + "id": "t3", + "source": "CoV_space_poly-br_merase_space_complex_complex_cell", + "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", + "sign": true + }, + { + "id": "t4", + "source": "nsp9_cell", + "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", + "sign": true + }, + { + "id": "t5", + "source": "nsp8_space_(I)", + "target": "complex_complex_cell", + "sign": true + }, + { + "id": "t6", + "source": "nsp8_space_(II)", + "target": "complex_complex_cell", + "sign": true + }, + { + "id": "t7", "source": "nsp7", "target": "complex_complex_cell", "sign": true }, { - "id": "t3", + "id": "t8", + "source": "nsp14", + "target": "CoV_space_poly-br_merase_space_complex_complex_cell", + "sign": true + }, + { + "id": "t9", "source": "nsp10", "target": "CoV_space_poly-br_merase_space_complex_complex_cell", "sign": true }, { - "id": "t4", + "id": "t10", + "source": "nsp12", + "target": "CoV_space_poly-br_merase_space_complex_complex_cell", + "sign": true + }, + { + "id": "t11", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "CoV_space_poly-br_merase_space_complex_complex_double membrane vesicle viral factory", "sign": true }, { - "id": "t5", + "id": "t12", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "complex_complex_double membrane vesicle viral factory", "sign": true }, { - "id": "t6", + "id": "t13", "source": "pp1a_cell", "target": "nsp2", "sign": true }, { - "id": "t7", + "id": "t14", "source": "pp1a_cell", "target": "nsp5", "sign": true }, { - "id": "t8", + "id": "t15", "source": "pp1ab_cell", "target": "nsp14", "sign": true }, { - "id": "t9", + "id": "t16", "source": "pp1a_cell", "target": "nsp3", "sign": true }, { - "id": "t10", + "id": "t17", "source": "pp1a_cell", "target": "nsp4", "sign": true }, { - "id": "t11", + "id": "t18", "source": "pp1ab_cell", "target": "nsp15", "sign": true }, { - "id": "t12", + "id": "t19", "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_cell", "target": "pp1ab_cell", "sign": true }, { - "id": "t13", + "id": "t20", "source": "pp1a_cell", "target": "nsp9_cell", "sign": true }, { - "id": "t14", + "id": "t21", "source": "pp1ab_cell", "target": "nsp16", "sign": true }, { - "id": "t15", + "id": "t22", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_double membrane vesicle viral factory", "sign": true }, { - "id": "t16", + "id": "t23", "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_double membrane vesicle viral factory", "target": "pp1a_double membrane vesicle viral factory", "sign": true }, { - "id": "t17", + "id": "t24", "source": "pp1a_cell", "target": "nsp8_space_(I)", "sign": true }, { - "id": "t18", + "id": "t25", "source": "pp1a_cell", "target": "nsp1", "sign": true }, { - "id": "t19", + "id": "t26", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "(+)sgRNA_space_(2-9)_gene", "sign": true }, { - "id": "t20", + "id": "t27", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "nsp9_double membrane vesicle viral factory", "sign": true }, { - "id": "t21", + "id": "t28", "source": "pp1a_cell", "target": "nsp7", "sign": true }, { - "id": "t22", + "id": "t29", "source": "pp1ab_cell", "target": "nsp12", "sign": true }, { - "id": "t23", + "id": "t30", "source": "pp1ab_cell", "target": "nsp13", "sign": true }, { - "id": "t24", + "id": "t31", "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_cell", "target": "pp1a_cell", "sign": true }, { - "id": "t25", + "id": "t32", "source": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "target": "(-)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene", "sign": true }, { - "id": "t26", + "id": "t33", "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_double membrane vesicle viral factory", "target": "pp1ab_double membrane vesicle viral factory", "sign": true }, { - "id": "t27", + "id": "t34", "source": "pp1a_cell", "target": "nsp10", "sign": true }, { - "id": "t28", + "id": "t35", "source": "pp1a_cell", "target": "nsp11", "sign": true }, { - "id": "t29", + "id": "t36", "source": "pp1a_cell", "target": "nsp8_space_(II)", "sign": true }, { - "id": "t30", + "id": "t37", "source": "(+)sgRNA_space_(2-9)_gene", "target": "viral_space_accessory", "sign": true }, { - "id": "t31", + "id": "t38", "source": "pp1a_cell", "target": "nsp6", "sign": true }, { - "id": "t32", + "id": "t39", "source": "(+)sgRNA_space_(2-9)_gene", "target": "structural_space_proteins", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json index 1b2a5e8a7..2ed1e2392 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json @@ -841,258 +841,780 @@ "edges": [ { "id": "t1", - "source": "ACE2_cell", + "source": "AGTR1_cell", "target": "ACE2:AGTR1_complex", "sign": true }, { "id": "t2", "source": "ACE2_cell", - "target": "ACE2-Spike complex_complex", + "target": "ACE2:AGTR1_complex", "sign": true }, { "id": "t3", + "source": "angiotensin II_simple_molecule_cell", + "target": "ACE2:AGTR1_complex", + "sign": true + }, + { + "id": "t4", + "source": "Camostat mesilate_drug", + "target": "ACE2-Spike complex_complex", + "sign": true + }, + { + "id": "t5", + "source": "S", + "target": "ACE2-Spike complex_complex", + "sign": true + }, + { + "id": "t6", + "source": "TMPRSS2", + "target": "ACE2-Spike complex_complex", + "sign": true + }, + { + "id": "t7", + "source": "ACE2_cell", + "target": "ACE2-Spike complex_complex", + "sign": true + }, + { + "id": "t8", + "source": "MAS1_cell", + "target": "MAS1:AGTR1_complex", + "sign": true + }, + { + "id": "t9", "source": "AGTR1_cell_active", "target": "MAS1:AGTR1_complex", "sign": true }, { - "id": "t4", + "id": "t10", + "source": "REN", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t11", + "source": "AGT", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t12", "source": "ACE_cell", "target": "angiotensin I_simple_molecule", "sign": true }, { - "id": "t5", + "id": "t13", + "source": "angiotensin 1-12_simple_molecule", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t14", + "source": "CTSG", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t15", + "source": "CTSD", + "target": "angiotensin I_simple_molecule", + "sign": true + }, + { + "id": "t16", + "source": "angiotensin I_simple_molecule", + "target": "angiotensin 1-9_simple_molecule", + "sign": true + }, + { + "id": "t17", "source": "ACE2_cell", "target": "angiotensin 1-9_simple_molecule", "sign": true }, { - "id": "t6", + "id": "t18", "source": "ACE_cell", "target": "angiotensin II_simple_molecule_cell", "sign": true }, { - "id": "t7", + "id": "t19", + "source": "angiotensin 1-12_simple_molecule", + "target": "angiotensin II_simple_molecule_cell", + "sign": true + }, + { + "id": "t20", + "source": "angiotensin I_simple_molecule", + "target": "angiotensin II_simple_molecule_cell", + "sign": true + }, + { + "id": "t21", + "source": "CMA1", + "target": "angiotensin II_simple_molecule_cell", + "sign": true + }, + { + "id": "t22", + "source": "KLK1", + "target": "angiotensin II_simple_molecule_cell", + "sign": true + }, + { + "id": "t23", + "source": "S", + "target": "angiotensin II_simple_molecule_cell", + "sign": true + }, + { + "id": "t24", + "source": "THOP1", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t25", + "source": "MME_cell", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t26", + "source": "PREP", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t27", + "source": "angiotensin 1-12_simple_molecule", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t28", + "source": "angiotensin 1-9_simple_molecule", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t29", + "source": "angiotensin I_simple_molecule", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t30", + "source": "ACE_cell_active", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t31", + "source": "angiotensin II_simple_molecule_cell", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t32", + "source": "PRCP", + "target": "angiotensin 1-7_simple_molecule_cell", + "sign": true + }, + { + "id": "t33", "source": "ACE2_cell", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { - "id": "t8", + "id": "t34", + "source": "CGP42112A_drug", + "target": "AGTR2_cell_active", + "sign": true + }, + { + "id": "t35", + "source": "angiotensin 1-9_simple_molecule", + "target": "AGTR2_cell_active", + "sign": true + }, + { + "id": "t36", "source": "AGTR2_cell", "target": "AGTR2_cell_active", "sign": true }, { - "id": "t9", + "id": "t37", + "source": "angiotensin A_simple_molecule", + "target": "AGTR2_cell_active", + "sign": true + }, + { + "id": "t38", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "AGTR2_cell_active", + "sign": true + }, + { + "id": "t39", + "source": "angiotensin II_simple_molecule_cell", + "target": "AGTR2_cell_active", + "sign": true + }, + { + "id": "t40", "source": "MAS1_cell", "target": "MAS1_cell_active", "sign": true }, { - "id": "t10", + "id": "t41", + "source": "angiotensin 1-5_simple_molecule", + "target": "MAS1_cell_active", + "sign": true + }, + { + "id": "t42", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "MAS1_cell_active", + "sign": true + }, + { + "id": "t43", + "source": "AR234960_drug", + "target": "MAS1_cell_active", + "sign": true + }, + { + "id": "t44", "source": "Calcitriol_simple_molecule", "target": "ACE_cell", "sign": true }, { - "id": "t11", + "id": "t45", + "source": "estradiol_simple_molecule", + "target": "ACE_cell", + "sign": true + }, + { + "id": "t46", + "source": "ACE2_gene", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t47", + "source": "Calcitriol_simple_molecule", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t48", + "source": "SARS-CoV-2 infection_phenotype", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t49", + "source": "aging_phenotype", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t50", + "source": "estradiol_simple_molecule", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t51", + "source": "hypertension_phenotype", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t52", + "source": "S", + "target": "ACE2_cell", + "sign": true + }, + { + "id": "t53", "source": " Diabetes mellitus, type II_phenotype", "target": "ACE2_cell", "sign": true }, { - "id": "t12", + "id": "t54", "source": "ACE_cell_active", "target": "angiotensin 1-5_simple_molecule", "sign": true }, { - "id": "t13", + "id": "t55", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "angiotensin 1-5_simple_molecule", + "sign": true + }, + { + "id": "t56", "source": "ethynylestradiol_simple_molecule", "target": "AGT", "sign": true }, { - "id": "t14", + "id": "t57", "source": "androgen_simple_molecule", "target": "TMPRSS2", "sign": true }, { - "id": "t15", + "id": "t58", + "source": "angiotensin A_simple_molecule", + "target": "alamandine_simple_molecule", + "sign": true + }, + { + "id": "t59", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "alamandine_simple_molecule", + "sign": true + }, + { + "id": "t60", "source": "ACE2_cell", "target": "alamandine_simple_molecule", "sign": true }, { - "id": "t16", + "id": "t61", "source": "MRGPRD_cell", "target": "MRGPRD_cell_active", "sign": true }, { - "id": "t17", + "id": "t62", + "source": "alamandine_simple_molecule", + "target": "MRGPRD_cell_active", + "sign": true + }, + { + "id": "t63", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "MRGPRD_cell_active", + "sign": true + }, + { + "id": "t64", "source": "angiotensin II_simple_molecule_cell", "target": "angiotensin A_simple_molecule", "sign": true }, { - "id": "t18", + "id": "t65", "source": "AGTR1_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { - "id": "t19", + "id": "t66", + "source": "AGTR2_cell_active", + "target": "vasoconstriction_phenotype", + "sign": true + }, + { + "id": "t67", + "source": "MAS1_cell_active", + "target": "vasoconstriction_phenotype", + "sign": true + }, + { + "id": "t68", + "source": "MRGPRD_cell_active", + "target": "vasoconstriction_phenotype", + "sign": true + }, + { + "id": "t69", + "source": "LNPEP_cell_active", + "target": "vasoconstriction_phenotype", + "sign": true + }, + { + "id": "t70", + "source": "LNPEP_cell_active", + "target": "inflammatory response_phenotype", + "sign": true + }, + { + "id": "t71", + "source": "MAS1_cell_active", + "target": "inflammatory response_phenotype", + "sign": true + }, + { + "id": "t72", + "source": "MRGPRD_cell_active", + "target": "inflammatory response_phenotype", + "sign": true + }, + { + "id": "t73", "source": "AGTR1_cell_active", "target": "inflammatory response_phenotype", "sign": true }, { - "id": "t20", + "id": "t74", "source": "ENPEP_cell_active", "target": "angiotensin III_simple_molecule", "sign": true }, { - "id": "t21", + "id": "t75", + "source": "angiotensin II_simple_molecule_cell", + "target": "angiotensin III_simple_molecule", + "sign": true + }, + { + "id": "t76", "source": "ANPEP ", "target": "angiotensin IV_simple_molecule", "sign": true }, { - "id": "t22", + "id": "t77", + "source": "angiotensin III_simple_molecule", + "target": "angiotensin IV_simple_molecule", + "sign": true + }, + { + "id": "t78", + "source": "sex, male_phenotype", + "target": "ENPEP_cell_active", + "sign": true + }, + { + "id": "t79", "source": "ENPEP_cell", "target": "ENPEP_cell_active", "sign": true }, { - "id": "t23", + "id": "t80", + "source": "QGC001_drug", + "target": "ENPEP_cell_active", + "sign": true + }, + { + "id": "t81", "source": "Calcitriol_simple_molecule", "target": "Calcitriol_simple_molecule", "sign": false }, { - "id": "t24", + "id": "t82", + "source": "ADAM17", + "target": "ACE2, soluble", + "sign": true + }, + { + "id": "t83", + "source": "AGTR1_cell_active", + "target": "ACE2, soluble", + "sign": true + }, + { + "id": "t84", "source": "ACE2_cell", "target": "ACE2, soluble", "sign": true }, { - "id": "t25", + "id": "t85", "source": "aldosterone_simple_molecule", "target": "aldosterone_simple_molecule", "sign": false }, { - "id": "t26", + "id": "t86", "source": "SARS-CoV-2 infection_phenotype", "target": "angiotensin II_simple_molecule_human host", "sign": true }, { - "id": "t27", + "id": "t87", + "source": "angiotensin II_simple_molecule_human host", + "target": "angiotensin 1-7_simple_molecule_human host", + "sign": true + }, + { + "id": "t88", "source": "ACE2, soluble", "target": "angiotensin 1-7_simple_molecule_human host", "sign": true }, { - "id": "t28", + "id": "t89", + "source": "sex, male_phenotype", + "target": "ACE2_cell_active", + "sign": true + }, + { + "id": "t90", + "source": "hypertension_phenotype", + "target": "ACE2_cell_active", + "sign": true + }, + { + "id": "t91", + "source": "aging_phenotype", + "target": "ACE2_cell_active", + "sign": true + }, + { + "id": "t92", "source": "ACE2_cell", "target": "ACE2_cell_active", "sign": true }, { - "id": "t29", + "id": "t93", + "source": "sex, male_phenotype", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t94", + "source": "Lisinopril_drug", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t95", + "source": "ACE_cell", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t96", "source": "ABO blood group system_phenotype", "target": "ACE_cell_active", "sign": true }, { - "id": "t30", + "id": "t97", + "source": "aging_phenotype", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t98", + "source": "aldosterone_simple_molecule", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t99", + "source": "hypertension_phenotype", + "target": "ACE_cell_active", + "sign": true + }, + { + "id": "t100", + "source": "MAS1:AGTR1_complex", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t101", + "source": "Losartan_drug", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t102", + "source": "angiotensin IV_simple_molecule", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t103", + "source": "angiotensin A_simple_molecule", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t104", "source": "AGTR1_cell", "target": "AGTR1_cell_active", "sign": true }, { - "id": "t31", + "id": "t105", + "source": "angiotensin 1-7_simple_molecule_cell", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t106", + "source": "angiotensin II_simple_molecule_cell", + "target": "AGTR1_cell_active", + "sign": true + }, + { + "id": "t107", + "source": "angiotensin 1-12_simple_molecule", + "target": "angiotensin 1-4_simple_molecule", + "sign": true + }, + { + "id": "t108", "source": "MME_cell", "target": "angiotensin 1-4_simple_molecule", "sign": true }, { - "id": "t32", + "id": "t109", + "source": "angiotensin 3-7_simple_molecule", + "target": "LNPEP_cell_active", + "sign": true + }, + { + "id": "t110", "source": "LNPEP_cell", "target": "LNPEP_cell_active", "sign": true }, { - "id": "t33", + "id": "t111", + "source": "angiotensin IV_simple_molecule", + "target": "LNPEP_cell_active", + "sign": true + }, + { + "id": "t112", + "source": "MAS1_cell_active", + "target": "oxidative stress_phenotype", + "sign": true + }, + { + "id": "t113", "source": "AGTR1_cell_active", "target": "oxidative stress_phenotype", "sign": true }, { - "id": "t34", + "id": "t114", "source": "angiotensin 1-7_simple_molecule_cell", "target": "angiotensin 3-7_simple_molecule", "sign": true }, { - "id": "t35", + "id": "t115", + "source": "angiotensin IV_simple_molecule", + "target": "angiotensin 3-7_simple_molecule", + "sign": true + }, + { + "id": "t116", + "source": "angiotensin II_simple_molecule_cell", + "target": "angiotensin 3-7_simple_molecule", + "sign": true + }, + { + "id": "t117", "source": "ACE2-Spike complex_complex", "target": "viral replication cycle_phenotype", "sign": true }, { - "id": "t36", + "id": "t118", + "source": "AGTR2_cell_active", + "target": "fibrosis_phenotype", + "sign": true + }, + { + "id": "t119", + "source": "MAS1_cell_active", + "target": "fibrosis_phenotype", + "sign": true + }, + { + "id": "t120", "source": "AGTR1_cell_active", "target": "fibrosis_phenotype", "sign": true }, { - "id": "t37", + "id": "t121", + "source": "MAS1_cell_active", + "target": "thrombosis_phenotype", + "sign": true + }, + { + "id": "t122", "source": "AGTR1_cell_active", "target": "thrombosis_phenotype", "sign": true }, { - "id": "t38", + "id": "t123", "source": "LNPEP_cell_active", "target": "LNPEP_cell_active", "sign": false }, { - "id": "t39", + "id": "t124", + "source": "sex, male_phenotype", + "target": "MME_cell_active", + "sign": true + }, + { + "id": "t125", "source": "MME_cell", "target": "MME_cell_active", "sign": true }, { - "id": "t40", + "id": "t126", "source": "AGTR1_cell_active", "target": "aldosterone_simple_molecule", "sign": true }, { - "id": "t41", + "id": "t127", + "source": "LNPEP_cell_active", + "target": "cognition_phenotype", + "sign": true + }, + { + "id": "t128", "source": "AGTR1_cell_active", "target": "cognition_phenotype", "sign": true }, { - "id": "t42", + "id": "t129", "source": "AGTR1_cell_active", "target": "pulmonary edema_phenotype", "sign": true }, { - "id": "t43", + "id": "t130", "source": "AGTR1_cell_active", "target": "platelet aggregation_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json index 735e37ce7..92ad36a72 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json @@ -201,42 +201,144 @@ "edges": [ { "id": "t1", - "source": "BAMBI", + "source": "BMPR1/2/ACTR2_complex", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t2", + "source": "Orf3a", + "target": "SMAD1/5/8_complex", + "sign": true + }, + { + "id": "t3", + "source": "Nsp7b_cell", + "target": "SMAD1/5/8_complex", + "sign": true + }, + { + "id": "t4", + "source": "E", + "target": "SMAD1/5/8_complex", + "sign": true + }, + { + "id": "t5", + "source": "BAMBI", + "target": "SMAD1/5/8_complex", + "sign": true + }, + { + "id": "t6", + "source": "MAPK3", + "target": "SMAD1/5/8_complex", + "sign": true + }, + { + "id": "t7", + "source": "ACVR1B", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t8", + "source": "Nsp7b_default_compartment", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t9", + "source": "TGFB/TGFBR_complex", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t10", + "source": "Orf3a", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t11", + "source": "E3 ubiquitin ligase complex_complex", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t12", + "source": "BAMBI", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t13", + "source": "MAPK3", + "target": "SMAD2/3_complex", + "sign": true + }, + { + "id": "t14", "source": "ACVR1", "target": "SMAD2/3_complex", "sign": true }, { - "id": "t3", + "id": "t15", + "source": "Orf8", + "target": "TGFB/TGFBR_complex", + "sign": true + }, + { + "id": "t16", + "source": "LTBP1", + "target": "TGFB/TGFBR_complex", + "sign": true + }, + { + "id": "t17", "source": "BAMBI", "target": "TGFB/TGFBR_complex", "sign": true }, { - "id": "t4", + "id": "t18", + "source": "TGFB/TGFBR_complex", + "target": "PP2A_complex", + "sign": true + }, + { + "id": "t19", "source": "Orf7a", "target": "PP2A_complex", "sign": true }, { - "id": "t5", + "id": "t20", + "source": "TGFB/TGFBR_complex", + "target": "RHOA", + "sign": true + }, + { + "id": "t21", "source": "Nsp7", "target": "RHOA", "sign": true }, { - "id": "t6", + "id": "t22", "source": "PP2A_complex", "target": "RPS6KB1_empty", "sign": true }, { - "id": "t7", + "id": "t23", + "source": "SMAD2/3_complex", + "target": "Modulation of cell cycle_phenotype", + "sign": true + }, + { + "id": "t24", "source": "SMAD1/5/8_complex", "target": "Modulation of cell cycle_phenotype", "sign": true diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json index c728452c0..a3622c02a 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json @@ -1947,966 +1947,1944 @@ "edges": [ { "id": "t1", - "source": "Nsp3", + "source": "Nsp10", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t2", - "source": "ACE2_epithelial_space_cell", - "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "Nsp3", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t3", - "source": "E_SARS-CoV-2_space_virion", - "target": "Nucleocapsid_complex_epithelial_space_cell", + "source": "Nsp12", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t4", - "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", - "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "Nsp4_endoplasmic reticulum", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t5", - "source": "NRP1", - "target": "S1:NRP1_space_complex_complex", + "source": "Nsp14", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t6", - "source": "N_epithelial_space_cell", - "target": "Replication_space_transcription_space_complex:N_space_oligomer_complex", + "source": "Nsp16", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t7", - "source": "ACE2_epithelial_space_cell", - "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "Nsp13", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t8", - "source": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", - "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "Nsp7", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t9", - "source": "(+)ss gRNA_rna_epithelial_space_cell", + "source": "Nsp9", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t10", - "source": "(+)ss gRNA_rna_epithelial_space_cell", - "target": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "Nsp2", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t11", - "source": "Nsp4:IDE_complex_epithelial_space_cell", - "target": "Nsp4_IDE_complex", + "source": "Nsp15", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t12", - "source": "IDE_epithelial_space_cell", - "target": "Nsp4:IDE_complex_epithelial_space_cell", + "source": "Nsp6_endoplasmic reticulum", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t13", - "source": "SIGMAR1_endoplasmic reticulum", - "target": "SIGMAR1: drug complex_complex", + "source": "Nsp8", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t14", - "source": "NUP210_endoplasmic reticulum", - "target": "Nsp4:NUP210_complex_endoplasmic reticulum", + "source": "S_SARS-CoV-2_space_virion", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t15", - "source": "V-ATPase_complex_endoplasmic reticulum", - "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "source": "ACE2_epithelial_space_cell", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t16", - "source": "ATP6AP1", - "target": "V-ATPase_complex_endoplasmic reticulum", + "source": "Heparan_space_sulfate_simple_molecule", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t17", - "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", - "target": "Nsp6:SIGMAR1_complex_nucleus", + "source": "S1:NRP1_space_complex_complex", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t18", - "source": "Nsp4:NUP210_complex_endoplasmic reticulum", - "target": "Nsp4:NUP210_complex_nucleus", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t19", - "source": "V-ATPase:Nsp6_complex_endoplasmic reticulum", - "target": "V-ATPase:Nsp6_complex_endosome", + "source": "S2_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t20", - "source": "V-ATPase_complex_endoplasmic reticulum", - "target": "V-ATPase_complex_endosome", + "source": "cholesterol_simple_molecule", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t21", - "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", - "target": "Nsp6:SIGMAR1_complex_epithelial_space_cell", + "source": "S2_epithelial_space_cell", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t22", - "source": "NUP210_endoplasmic reticulum", - "target": "NUP210:Selinexor_complex", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t23", - "source": "SIGMAR1_endoplasmic reticulum", - "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "source": "M_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t24", - "source": "ATP6AP1", - "target": "ATP6AP1:Bafilomycin_space_A1_complex", + "source": "E_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t25", - "source": "ALG11_endoplasmic reticulum", - "target": "Nsp4_ALG11_complex_endoplasmic reticulum", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t26", - "source": "ARL8B", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t27", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", - "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "S1_default_compartment", + "target": "S1:NRP1_space_complex_complex", "sign": true }, { "id": "t28", - "source": "ds_space_gRNA_rna", - "target": "(-)ss_space_gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "NRP1", + "target": "S1:NRP1_space_complex_complex", "sign": true }, { "id": "t29", - "source": "Nsp1", - "target": "Nsp1", - "sign": false + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Replication_space_transcription_space_complex:N_space_oligomer_complex", + "sign": true }, { "id": "t30", - "source": "S_rough_space_endoplasmic_space_reticulum", - "target": "S_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "N_epithelial_space_cell", + "target": "Replication_space_transcription_space_complex:N_space_oligomer_complex", "sign": true }, { "id": "t31", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "S_SARS-CoV-2_space_virion", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t32", - "source": "E_space_ds_space_sgmRNA_rna", - "target": "E_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "ACE2_epithelial_space_cell", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t33", - "source": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", - "target": "Orf9b_space_ds_space_sgmRNA_rna", + "source": "Heparan_space_sulfate_simple_molecule", + "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t34", - "source": "M_space_ds_space_sgmRNA_rna", - "target": "M_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t35", - "source": "Orf9b_rough_space_endoplasmic_space_reticulum", - "target": "Orf9b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "Replication_space_transcription_space_complex:N_space_oligomer_complex", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t36", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "(+)ss gRNA_rna_epithelial_space_cell", + "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t37", - "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", - "target": "pp1ab_space_nsp6-16", + "source": "Replication_space_transcription_space_complex:N_space_oligomer_complex", + "target": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { "id": "t38", - "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", - "target": "E_rough_space_endoplasmic_space_reticulum", + "source": "(+)ss gRNA_rna_epithelial_space_cell", + "target": "Nucleocapsid_complex_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { "id": "t39", - "source": "Orf14_rough_space_endoplasmic_space_reticulum", - "target": "Orf14_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "Nsp4:IDE_complex_epithelial_space_cell", + "target": "Nsp4_IDE_complex", "sign": true }, { "id": "t40", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Nsp4_epithelial_space_cell", + "target": "Nsp4:IDE_complex_epithelial_space_cell", "sign": true }, { "id": "t41", - "source": "pp1ab_space_nsp6-16", - "target": "Nsp13", + "source": "IDE_epithelial_space_cell", + "target": "Nsp4:IDE_complex_epithelial_space_cell", "sign": true }, { "id": "t42", - "source": "(+)ss_space_gRNA_rna", - "target": "pp1a", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "SIGMAR1: drug complex_complex", "sign": true }, { "id": "t43", - "source": "pp1a", - "target": "Nsp1", + "source": "SARS-CoV2 candidate drugs_complex", + "target": "SIGMAR1: drug complex_complex", "sign": true }, { "id": "t44", - "source": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", - "target": "Orf14_space_ds_space_sgmRNA_rna", + "source": "Nsp4_epithelial_space_cell", + "target": "Nsp4:NUP210_complex_endoplasmic reticulum", "sign": true }, { "id": "t45", - "source": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", - "target": "E_space_ds_space_sgmRNA_rna", + "source": "NUP210_endoplasmic reticulum", + "target": "Nsp4:NUP210_complex_endoplasmic reticulum", "sign": true }, { "id": "t46", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Nsp6_epithelial_space_cell", + "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", "sign": true }, { "id": "t47", - "source": "Nsp15", - "target": "Nsp15", - "sign": false + "source": "V-ATPase_complex_endoplasmic reticulum", + "target": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "sign": true }, { "id": "t48", - "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", - "target": "Nsp5_epithelial_space_cell", + "source": "V-type_space_proton_space_ATPase_complex", + "target": "V-ATPase_complex_endoplasmic reticulum", "sign": true }, { "id": "t49", - "source": "Nsp3-4", - "target": "Nsp3-4_glycosylated", + "source": "ATP6AP1", + "target": "V-ATPase_complex_endoplasmic reticulum", "sign": true }, { "id": "t50", - "source": "Nsp3-4_glycosylated", - "target": "Nsp3", + "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_nucleus", "sign": true }, { "id": "t51", - "source": "pp1a_space_Nsp6-11", - "target": "Nsp7", + "source": "Nsp4:NUP210_complex_endoplasmic reticulum", + "target": "Nsp4:NUP210_complex_nucleus", "sign": true }, { "id": "t52", - "source": "pp1ab_space_nsp6-16", - "target": "Nsp16", + "source": "V-ATPase:Nsp6_complex_endoplasmic reticulum", + "target": "V-ATPase:Nsp6_complex_endosome", "sign": true }, { "id": "t53", - "source": "Orf8_space_ds_space_sgmRNA_rna", - "target": "Orf8_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "V-ATPase_complex_endoplasmic reticulum", + "target": "V-ATPase_complex_endosome", "sign": true }, { "id": "t54", - "source": "pp1ab_space_nsp6-16", - "target": "Nsp12", + "source": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_epithelial_space_cell", "sign": true }, { "id": "t55", - "source": "pp1a", - "target": "Nsp2", + "source": "Selinexor_drug", + "target": "NUP210:Selinexor_complex", "sign": true }, { "id": "t56", - "source": "Nucleocapsid_complex_epithelial_space_cell", - "target": "(+)ss_space_gRNA_rna", + "source": "NUP210_endoplasmic reticulum", + "target": "NUP210:Selinexor_complex", "sign": true }, { "id": "t57", - "source": "Orf6_space_ds_space_sgmRNA_rna", - "target": "Orf6_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Nsp6_epithelial_space_cell", + "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "sign": true }, { "id": "t58", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "ds_space_gRNA_rna", + "source": "SIGMAR1_endoplasmic reticulum", + "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "sign": true }, { "id": "t59", - "source": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", - "target": "M_space_ds_space_sgmRNA_rna", + "source": "bafilomycin_space_A1_drug", + "target": "ATP6AP1:Bafilomycin_space_A1_complex", "sign": true }, { "id": "t60", - "source": "Camostat_space_mesylate_drug", - "target": "S2_epithelial_space_cell", + "source": "ATP6AP1", + "target": "ATP6AP1:Bafilomycin_space_A1_complex", "sign": true }, { "id": "t61", - "source": "pp1ab_space_nsp6-16", - "target": "Nsp14", + "source": "Nsp4_epithelial_space_cell", + "target": "Nsp4_ALG11_complex_endoplasmic reticulum", "sign": true }, { "id": "t62", - "source": "Camostat_space_mesylate_drug", - "target": "ACE2_epithelial_space_cell", + "source": "ALG11_endoplasmic reticulum", + "target": "Nsp4_ALG11_complex_endoplasmic reticulum", "sign": true }, { "id": "t63", - "source": "pp1a_space_Nsp6-11", - "target": "Nsp10", + "source": "Ca+2_simple_molecule", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t64", - "source": "E_SARS-CoV-2_space_virion", - "target": "Orf7a_endosome", + "source": "RAB7A", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t65", - "source": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", - "target": "Orf7b_space_ds_space_sgmRNA_rna", + "source": "ARL8B", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t66", - "source": "N_space_space_(-)ss_space_sgmRNA_rna", - "target": "N_space_ds_space_sgmRNA_rna", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t67", - "source": "pp1a_space_Nsp6-11", - "target": "Nsp9", + "source": "RAB7A", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t68", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", - "target": "N_space_space_(-)ss_space_sgmRNA_rna", + "source": "ARL8B", + "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t69", - "source": "E_rough_space_endoplasmic_space_reticulum", - "target": "E_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "ds_space_gRNA_rna", + "target": "(-)ss_space_gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t70", - "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", - "target": "Nsp3-4", - "sign": true + "source": "Nsp1", + "target": "Nsp1", + "sign": false }, { "id": "t71", - "source": "Orf7b_rough_space_endoplasmic_space_reticulum", - "target": "Orf7b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "source": "S_rough_space_endoplasmic_space_reticulum", + "target": "S_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { "id": "t72", - "source": "(+)ss_space_gRNA_rna", - "target": "pp1ab", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t73", - "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", - "target": "Orf3a_rough_space_endoplasmic_space_reticulum", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t74", + "source": "E_space_ds_space_sgmRNA_rna", + "target": "E_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t75", + "source": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf9b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t76", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf9b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t77", + "source": "M_space_ds_space_sgmRNA_rna", + "target": "M_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t78", + "source": "Orf9b_rough_space_endoplasmic_space_reticulum", + "target": "Orf9b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t79", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t80", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t81", + "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "target": "pp1ab_space_nsp6-16", + "sign": true + }, + { + "id": "t82", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "E_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t83", + "source": "E (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "E_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t84", + "source": "Orf14_rough_space_endoplasmic_space_reticulum", + "target": "Orf14_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t85", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t86", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t87", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp13", + "sign": true + }, + { + "id": "t88", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp13", + "sign": true + }, + { + "id": "t89", + "source": "(+)ss_space_gRNA_rna", + "target": "pp1a", + "sign": true + }, + { + "id": "t90", + "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", + "target": "pp1a", + "sign": true + }, + { + "id": "t91", + "source": "pp1a", + "target": "Nsp1", + "sign": true + }, + { + "id": "t92", + "source": "pp1ab", + "target": "Nsp1", + "sign": true + }, + { + "id": "t93", + "source": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf14_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t94", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf14_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t95", + "source": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "E_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t96", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "E_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t97", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t98", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t99", + "source": "Nsp15", + "target": "Nsp15", + "sign": false + }, + { + "id": "t100", + "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "target": "Nsp5_epithelial_space_cell", + "sign": true + }, + { + "id": "t101", + "source": "Nsp3-4", + "target": "Nsp3-4_glycosylated", + "sign": true + }, + { + "id": "t102", + "source": "Nsp3-4_glycosylated", + "target": "Nsp3", + "sign": true + }, + { + "id": "t103", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp7", + "sign": true + }, + { + "id": "t104", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp7", + "sign": true + }, + { + "id": "t105", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp7", + "sign": true + }, + { + "id": "t106", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp7", + "sign": true + }, + { + "id": "t107", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp16", + "sign": true + }, + { + "id": "t108", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp16", + "sign": true + }, + { + "id": "t109", + "source": "Orf8_space_ds_space_sgmRNA_rna", + "target": "Orf8_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t110", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp12", + "sign": true + }, + { + "id": "t111", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp12", + "sign": true + }, + { + "id": "t112", + "source": "pp1a", + "target": "Nsp2", + "sign": true + }, + { + "id": "t113", + "source": "pp1ab", + "target": "Nsp2", + "sign": true + }, + { + "id": "t114", + "source": "Nucleocapsid_complex_epithelial_space_cell", + "target": "(+)ss_space_gRNA_rna", + "sign": true + }, + { + "id": "t115", + "source": "Orf6_space_ds_space_sgmRNA_rna", + "target": "Orf6_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "sign": true + }, + { + "id": "t116", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "ds_space_gRNA_rna", + "sign": true + }, + { + "id": "t117", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "ds_space_gRNA_rna", + "sign": true + }, + { + "id": "t118", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "M_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t119", + "source": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "M_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t120", + "source": "Camostat_space_mesylate_drug", + "target": "S2_epithelial_space_cell", + "sign": true + }, + { + "id": "t121", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "target": "S2_epithelial_space_cell", + "sign": true + }, + { + "id": "t122", + "source": "FURIN", + "target": "S2_epithelial_space_cell", + "sign": true + }, + { + "id": "t123", + "source": "TMPRSS2", + "target": "S2_epithelial_space_cell", + "sign": true + }, + { + "id": "t124", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp14", + "sign": true + }, + { + "id": "t125", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp14", + "sign": true + }, + { + "id": "t126", + "source": "Camostat_space_mesylate_drug", + "target": "ACE2_epithelial_space_cell", + "sign": true + }, + { + "id": "t127", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "target": "ACE2_epithelial_space_cell", + "sign": true + }, + { + "id": "t128", + "source": "FURIN", + "target": "ACE2_epithelial_space_cell", + "sign": true + }, + { + "id": "t129", + "source": "TMPRSS2", + "target": "ACE2_epithelial_space_cell", + "sign": true + }, + { + "id": "t130", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp10", + "sign": true + }, + { + "id": "t131", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp10", + "sign": true + }, + { + "id": "t132", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp10", + "sign": true + }, + { + "id": "t133", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp10", + "sign": true + }, + { + "id": "t134", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t135", + "source": "S2_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t136", + "source": "M_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t137", + "source": "E_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t138", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "Orf7a_endosome", + "sign": true + }, + { + "id": "t139", + "source": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "Orf7b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t140", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7b_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t141", + "source": "N_space_space_(-)ss_space_sgmRNA_rna", + "target": "N_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t142", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "N_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t143", + "source": "pp1a_space_Nsp6-11", + "target": "Nsp9", + "sign": true + }, + { + "id": "t144", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp9", "sign": true }, { - "id": "t74", + "id": "t145", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp9", + "sign": true + }, + { + "id": "t146", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp9", + "sign": true + }, + { + "id": "t147", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "N_space_space_(-)ss_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t148", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "target": "N_space_space_(-)ss_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t149", + "source": "E_rough_space_endoplasmic_space_reticulum", + "target": "E_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t150", + "source": "pp1ab_space_Nsp3-16_endoplasmic reticulum", + "target": "Nsp3-4", + "sign": true + }, + { + "id": "t151", + "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", + "target": "Nsp3-4", + "sign": true + }, + { + "id": "t152", + "source": "Orf7b_rough_space_endoplasmic_space_reticulum", + "target": "Orf7b_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", + "sign": true + }, + { + "id": "t153", + "source": "(+)ss_space_gRNA_rna", + "target": "pp1ab", + "sign": true + }, + { + "id": "t154", + "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", + "target": "pp1ab", + "sign": true + }, + { + "id": "t155", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf3a_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t156", + "source": "Orf3a (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf3a_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t157", + "source": "Orf9b (+)ss sgmRNA_rna_epithelial_space_cell", "target": "Orf9b_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t75", + "id": "t158", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "target": "Orf9b_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t159", + "source": "S1:NRP1_space_complex_complex", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t160", + "source": "cholesterol_simple_molecule", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t161", + "source": "S2_epithelial_space_cell", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t162", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t163", + "source": "M_SARS-CoV-2_space_virion", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t164", "source": "E_SARS-CoV-2_space_virion", "target": "Orf7a_epithelial_space_cell", "sign": true }, { - "id": "t76", + "id": "t165", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "Orf7a_epithelial_space_cell", + "sign": true + }, + { + "id": "t166", "source": "N_space_ds_space_sgmRNA_rna", "target": "N_space_(-)ss_space_sgmRNA_rna", "sign": true }, { - "id": "t77", + "id": "t167", + "source": "Orf6 (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf6_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t168", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf6_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t78", + "id": "t169", "source": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf6_space_ds_space_sgmRNA_rna", "sign": true }, { - "id": "t79", + "id": "t170", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf6_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t171", + "source": "Orf7a (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf7a_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t172", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf7a_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t80", + "id": "t173", "source": "pp1a_space_Nsp6-11", "target": "Nsp8", "sign": true }, { - "id": "t81", + "id": "t174", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp8", + "sign": true + }, + { + "id": "t175", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp8", + "sign": true + }, + { + "id": "t176", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp8", + "sign": true + }, + { + "id": "t177", "source": "pp1a_space_Nsp6-11", "target": "Nsp6_endoplasmic reticulum", "sign": true }, { - "id": "t82", + "id": "t178", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t179", + "source": "pp1ab_space_nsp6-16", + "target": "Nsp6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t180", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp6_endoplasmic reticulum", + "sign": true + }, + { + "id": "t181", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf8_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t182", "source": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf8_space_ds_space_sgmRNA_rna", "sign": true }, { - "id": "t83", + "id": "t183", "source": "Orf7a_space_ds_space_sgmRNA_rna", "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t84", + "id": "t184", "source": "M_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "target": "M_SARS-CoV-2_space_virion", "sign": true }, { - "id": "t85", + "id": "t185", + "source": "Nucleocapsid_complex_epithelial_space_cell", + "target": "N_epithelial_space_cell", + "sign": true + }, + { + "id": "t186", "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", "target": "N_epithelial_space_cell", "sign": true }, { - "id": "t86", + "id": "t187", + "source": "N (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "N_epithelial_space_cell", + "sign": true + }, + { + "id": "t188", "source": "S_space_ds_space_sgmRNA_rna", "target": "S_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t87", + "id": "t189", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t190", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t88", + "id": "t191", "source": "Orf7a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "target": "Orf7a_SARS-CoV-2_space_virion", "sign": true }, { - "id": "t89", + "id": "t192", + "source": "Orf14 (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf14_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t193", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf14_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t90", + "id": "t194", "source": "Camostat_space_mesylate_drug", "target": "ACE2_default_compartment", "sign": true }, { - "id": "t91", + "id": "t195", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "target": "ACE2_default_compartment", + "sign": true + }, + { + "id": "t196", + "source": "FURIN", + "target": "ACE2_default_compartment", + "sign": true + }, + { + "id": "t197", + "source": "TMPRSS2", + "target": "ACE2_default_compartment", + "sign": true + }, + { + "id": "t198", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t199", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t92", + "id": "t200", + "source": "S (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "S_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t201", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "S_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t93", + "id": "t202", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "E_endosome", + "sign": true + }, + { + "id": "t203", + "source": "S2_SARS-CoV-2_space_virion", + "target": "E_endosome", + "sign": true + }, + { + "id": "t204", + "source": "M_SARS-CoV-2_space_virion", + "target": "E_endosome", + "sign": true + }, + { + "id": "t205", "source": "E_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, { - "id": "t94", + "id": "t206", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "E_endosome", + "sign": true + }, + { + "id": "t207", "source": "S_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "target": "S_SARS-CoV-2_space_virion", "sign": true }, { - "id": "t95", + "id": "t208", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t209", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t96", - "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", - "target": "S2_SARS-CoV-2_space_virion", + "id": "t210", + "source": "CTSB", + "target": "S2_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t211", + "source": "CTSL", + "target": "S2_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t212", + "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", + "target": "S2_SARS-CoV-2_space_virion", + "sign": true + }, + { + "id": "t213", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "M_endosome", + "sign": true + }, + { + "id": "t214", + "source": "S2_SARS-CoV-2_space_virion", + "target": "M_endosome", + "sign": true + }, + { + "id": "t215", + "source": "M_SARS-CoV-2_space_virion", + "target": "M_endosome", "sign": true }, { - "id": "t97", + "id": "t216", "source": "E_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, { - "id": "t98", + "id": "t217", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "M_endosome", + "sign": true + }, + { + "id": "t218", "source": "Orf7b_space_ds_space_sgmRNA_rna", "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t99", + "id": "t219", "source": "Orf14_space_ds_space_sgmRNA_rna", "target": "Orf14_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t100", + "id": "t220", "source": "pp1ab", "target": "pp1ab_space_Nsp3-16_endoplasmic reticulum", "sign": true }, { - "id": "t101", + "id": "t221", "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", "target": "pp1a_space_Nsp6-11", "sign": true }, { - "id": "t102", + "id": "t222", "source": "Camostat_space_mesylate_drug", "target": "S1_default_compartment", "sign": true }, { - "id": "t103", + "id": "t223", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "target": "S1_default_compartment", + "sign": true + }, + { + "id": "t224", + "source": "FURIN", + "target": "S1_default_compartment", + "sign": true + }, + { + "id": "t225", + "source": "TMPRSS2", + "target": "S1_default_compartment", + "sign": true + }, + { + "id": "t226", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t227", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t104", + "id": "t228", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t229", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t105", + "id": "t230", "source": "Orf8_rough_space_endoplasmic_space_reticulum", "target": "Orf8_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { - "id": "t106", + "id": "t231", "source": "Orf9b_space_ds_space_sgmRNA_rna", "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t107", + "id": "t232", + "source": "S1:NRP1_space_complex_complex", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t233", + "source": "cholesterol_simple_molecule", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t234", + "source": "S2_epithelial_space_cell", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t235", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t236", + "source": "M_SARS-CoV-2_space_virion", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t237", "source": "E_SARS-CoV-2_space_virion", "target": "M_epithelial_space_cell", "sign": true }, { - "id": "t108", + "id": "t238", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "M_epithelial_space_cell", + "sign": true + }, + { + "id": "t239", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf7b_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t109", + "id": "t240", + "source": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf7b_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t241", "source": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf7a_space_ds_space_sgmRNA_rna", "sign": true }, { - "id": "t110", + "id": "t242", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7a_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t243", "source": "pp1a_space_Nsp6-11", "target": "Nsp11", "sign": true }, { - "id": "t111", + "id": "t244", + "source": "Nsp5_endoplasmic reticulum", + "target": "Nsp11", + "sign": true + }, + { + "id": "t245", + "source": "S1:NRP1_space_complex_complex", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t246", + "source": "cholesterol_simple_molecule", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t247", + "source": "S2_epithelial_space_cell", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t248", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t249", + "source": "M_SARS-CoV-2_space_virion", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t250", "source": "E_SARS-CoV-2_space_virion", "target": "E_epithelial_space_cell", "sign": true }, { - "id": "t112", + "id": "t251", + "source": "Orf7a_SARS-CoV-2_space_virion", + "target": "E_epithelial_space_cell", + "sign": true + }, + { + "id": "t252", "source": "E_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "target": "E_SARS-CoV-2_space_virion", "sign": true }, { - "id": "t113", + "id": "t253", + "source": "CTSB", + "target": "S1_endosome", + "sign": true + }, + { + "id": "t254", + "source": "CTSL", + "target": "S1_endosome", + "sign": true + }, + { + "id": "t255", "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", "target": "S1_endosome", "sign": true }, { - "id": "t114", + "id": "t256", "source": "Orf6_rough_space_endoplasmic_space_reticulum", "target": "Orf6_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { - "id": "t115", + "id": "t257", "source": "Orf3a_space_ds_space_sgmRNA_rna", "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t116", + "id": "t258", "source": "pp1a_space_Nsp3-11_endoplasmic reticulum", "target": "Nsp5_endoplasmic reticulum", "sign": true }, { - "id": "t117", + "id": "t259", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t260", "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t118", + "id": "t261", "source": "Orf7a_rough_space_endoplasmic_space_reticulum", "target": "Orf7a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { - "id": "t119", + "id": "t262", + "source": "M (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "M_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t263", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "M_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t120", + "id": "t264", "source": "Orf3a_rough_space_endoplasmic_space_reticulum", "target": "Orf3a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { - "id": "t121", + "id": "t265", "source": "Nsp3-4_glycosylated", "target": "Nsp4_endoplasmic reticulum", "sign": true }, { - "id": "t122", + "id": "t266", "source": "pp1a", "target": "pp1a_space_Nsp3-11_endoplasmic reticulum", "sign": true }, { - "id": "t123", + "id": "t267", "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf8_rough_space_endoplasmic_space_reticulum", "sign": true }, { - "id": "t124", + "id": "t268", + "source": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", + "target": "Orf8_rough_space_endoplasmic_space_reticulum", + "sign": true + }, + { + "id": "t269", "source": "(+)ss_space_gRNA_rna", "target": "(-)ss_space_gRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t125", + "id": "t270", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t271", "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "S_space_ds_space_sgmRNA_rna", "sign": true }, { - "id": "t126", + "id": "t272", + "source": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "target": "S_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t273", "source": "pp1ab_space_nsp6-16", "target": "Nsp15", "sign": true }, { - "id": "t127", + "id": "t274", + "source": "Nsp5_epithelial_space_cell", + "target": "Nsp15", + "sign": true + }, + { + "id": "t275", "source": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf3a_space_ds_space_sgmRNA_rna", "sign": true }, { - "id": "t128", + "id": "t276", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf3a_space_ds_space_sgmRNA_rna", + "sign": true + }, + { + "id": "t277", "source": "M_rough_space_endoplasmic_space_reticulum", "target": "M_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "sign": true }, { - "id": "t129", + "id": "t278", "source": "IDE_epithelial_space_cell", "target": "IDE_default_compartment", "sign": true }, { - "id": "t130", + "id": "t279", "source": "IDE_epithelial_space_cell", "target": "IDE_epithelial_space_cell", "sign": true }, { - "id": "t131", + "id": "t280", "source": "V-type_space_proton_space_ATPase_complex", "target": "H+_ion", "sign": true }, { - "id": "t132", + "id": "t281", "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1_epithelial_space_cell", "sign": true }, { - "id": "t133", + "id": "t282", "source": "NUP210_endoplasmic reticulum", "target": "NUP210_nucleus", "sign": true }, { - "id": "t134", + "id": "t283", "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1_nucleus", "sign": true }, { - "id": "t135", + "id": "t284", "source": "Nsp3", "target": "double membrane vesicle viral factory assembly_phenotype", "sign": true }, { - "id": "t136", + "id": "t285", + "source": "Nsp4_endoplasmic reticulum", + "target": "double membrane vesicle viral factory assembly_phenotype", + "sign": true + }, + { + "id": "t286", + "source": "Nsp6_endoplasmic reticulum", + "target": "double membrane vesicle viral factory assembly_phenotype", + "sign": true + }, + { + "id": "t287", "source": "bafilomycin_space_A1_drug", "target": "SARS-CoV2 candidate drugs_complex", "sign": false }, { - "id": "t137", + "id": "t288", "source": "ds_space_gRNA_rna", "target": "(+)ss gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t138", + "id": "t289", "source": "N_space_ds_space_sgmRNA_rna", "target": "N (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t139", + "id": "t290", "source": "M_space_ds_space_sgmRNA_rna", "target": "M (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t140", + "id": "t291", "source": "S_space_ds_space_sgmRNA_rna", "target": "S (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t141", + "id": "t292", "source": "E_space_ds_space_sgmRNA_rna", "target": "E (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t142", + "id": "t293", "source": "Orf6_space_ds_space_sgmRNA_rna", "target": "Orf6 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t143", + "id": "t294", "source": "Orf7a_space_ds_space_sgmRNA_rna", "target": "Orf7a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t144", + "id": "t295", "source": "Orf3a_space_ds_space_sgmRNA_rna", "target": "Orf3a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t145", + "id": "t296", "source": "Orf8_space_ds_space_sgmRNA_rna", "target": "Orf8 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t146", + "id": "t297", "source": "DMV molecular pore_complex", "target": "Orf7a (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t147", + "id": "t298", + "source": "Orf7a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7a (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t299", "source": "DMV molecular pore_complex", "target": "S (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t148", + "id": "t300", + "source": "S (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "S (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t301", "source": "DMV molecular pore_complex", "target": "Orf6 (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t149", + "id": "t302", + "source": "Orf6 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf6 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t303", "source": "DMV molecular pore_complex", "target": "E (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t150", + "id": "t304", + "source": "E (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "E (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t305", "source": "DMV molecular pore_complex", "target": "Orf3a (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t151", + "id": "t306", + "source": "Orf3a (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf3a (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t307", "source": "DMV molecular pore_complex", "target": "M (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t152", + "id": "t308", + "source": "M (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "M (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t309", "source": "DMV molecular pore_complex", "target": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t153", + "id": "t310", + "source": "Orf8 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t311", "source": "DMV molecular pore_complex", "target": "N (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t154", + "id": "t312", + "source": "N (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "N (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t313", + "source": "DMV molecular pore_complex", + "target": "(+)ss gRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t314", "source": "(+)ss gRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "(+)ss gRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t155", + "id": "t315", "source": "DMV molecular pore_complex", "target": "Orf9b (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t156", + "id": "t316", + "source": "Orf9b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf9b (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t317", "source": "DMV molecular pore_complex", "target": "Orf14 (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t157", + "id": "t318", + "source": "Orf14 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf14 (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t319", + "source": "Orf7b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "target": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", + "sign": true + }, + { + "id": "t320", "source": "DMV molecular pore_complex", "target": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { - "id": "t158", + "id": "t321", "source": "Orf9b_space_ds_space_sgmRNA_rna", "target": "Orf9b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t159", + "id": "t322", "source": "Orf14_space_ds_space_sgmRNA_rna", "target": "Orf14 (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t160", + "id": "t323", "source": "Orf7b_space_ds_space_sgmRNA_rna", "target": "Orf7b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { - "id": "t161", + "id": "t324", "source": "Orf3a_endoplasmic_space_reticulum-Golgi_space_intermediate_space_compartment", "target": "Orf3a_lysosome", "sign": true From 7ebffadafeecf16287a6a3e1d1774c099e2391f8 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Wed, 24 Apr 2024 16:57:46 -0400 Subject: [PATCH 39/44] Update script to save BIOMD0000000562 to sbml qual examples --- .../process_covid19_diseasemaps_sbml.py | 9 +++ .../regnet_amr_sbml/BIOMD0000000562.json | 68 +++++++++++++------ 2 files changed, 55 insertions(+), 22 deletions(-) diff --git a/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py index 28edbf528..3e4a4d97f 100644 --- a/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py +++ b/scripts/covid19_diseasemaps/process_covid19_diseasemaps_sbml.py @@ -4,6 +4,8 @@ from mira.sources.sbml import template_model_from_sbml_qual_string from mira.modeling.amr.regnet import template_model_to_regnet_json +from mira.sources.biomodels import get_sbml_model + models = [ @@ -46,3 +48,10 @@ regnet = template_model_to_regnet_json(tm) with open(f"regnet_amr_sbml/{model}.json", "w") as fh: json.dump(regnet, fh, indent=1) + + model_id = "BIOMD0000000562" + model_text = get_sbml_model(model_id) + tm = template_model_from_sbml_qual_string(model_text) + regnet = template_model_to_regnet_json(tm) + with open(f"regnet_amr_sbml/{model_id}.json", "w") as fh: + json.dump(regnet, fh, indent=1) diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json index f3f8939e9..758c9803e 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json @@ -274,140 +274,164 @@ { "id": "t4", "source": "map3k1", - "target": "mkk4", + "target": "mkk7", "sign": true }, { "id": "t5", "source": "map3k7", - "target": "nik", + "target": "mkk4", "sign": true }, { "id": "t6", + "source": "map3k1", + "target": "mkk4", + "sign": true + }, + { + "id": "t7", + "source": "map3k7", + "target": "nik", + "sign": true + }, + { + "id": "t8", "source": "mkk7", "target": "jnk", "sign": true }, { - "id": "t7", + "id": "t9", "source": "tnfr", "target": "traf2", "sign": true }, { - "id": "t8", + "id": "t10", "source": "egfr", "target": "pi3k", "sign": true }, { - "id": "t9", + "id": "t11", + "source": "ikk", + "target": "ikb", + "sign": true + }, + { + "id": "t12", "source": "ex", "target": "ikb", "sign": true }, { - "id": "t10", + "id": "t13", "source": "mek", "target": "erk", "sign": true }, { - "id": "t11", + "id": "t14", "source": "ras", "target": "map3k1", "sign": true }, { - "id": "t12", + "id": "t15", "source": "ras", "target": "raf1", "sign": true }, { - "id": "t13", + "id": "t16", "source": "tnfa", "target": "tnfr", "sign": true }, { - "id": "t14", + "id": "t17", "source": "traf2", "target": "map3k7", "sign": true }, { - "id": "t15", + "id": "t18", "source": "traf2", "target": "ask1", "sign": true }, { - "id": "t16", + "id": "t19", "source": "akt", "target": "akt", "sign": false }, { - "id": "t17", + "id": "t20", "source": "pi3k", "target": "akt", "sign": true }, { - "id": "t18", + "id": "t21", "source": "egf", "target": "egfr", "sign": true }, { - "id": "t19", + "id": "t22", "source": "ikb", "target": "ikb", "sign": false }, { - "id": "t20", + "id": "t23", "source": "nfkb", "target": "ex", "sign": true }, { - "id": "t21", + "id": "t24", "source": "cjun", "target": "ap1", "sign": true }, { - "id": "t22", + "id": "t25", "source": "jnk", "target": "cjun", "sign": true }, { - "id": "t23", + "id": "t26", "source": "erk", "target": "ph", "sign": true }, { - "id": "t24", + "id": "t27", "source": "raf1", "target": "mek", "sign": true }, { - "id": "t25", + "id": "t28", "source": "sos", "target": "ras", "sign": true }, { - "id": "t26", + "id": "t29", "source": "egfr", "target": "sos", "sign": true + }, + { + "id": "t30", + "source": "ph", + "target": "sos", + "sign": true } ], "parameters": [] From 6ebf1003ed5146d37ef0b6935e75adfee365cf70 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Thu, 25 Apr 2024 10:07:39 -0400 Subject: [PATCH 40/44] Add more comments to modeling regnet file and fix minor bug, rerun script to regenerate qual regnet amr --- mira/modeling/amr/regnet.py | 6 +- .../regnet_amr_sbml/Apoptosis.json | 42 +- .../regnet_amr_sbml/BIOMD0000000562.json | 4 +- .../regnet_amr_sbml/Coagulation-pathway.json | 178 ++-- .../regnet_amr_sbml/ER_Stress.json | 308 +++--- .../regnet_amr_sbml/ETC.json | 190 ++-- .../regnet_amr_sbml/E_protein.json | 36 +- .../regnet_amr_sbml/HMOX1_Pathway.json | 284 +++--- .../regnet_amr_sbml/IFN-lambda.json | 18 +- .../regnet_amr_sbml/Interferon1.json | 220 ++-- .../regnet_amr_sbml/JNK_pathway.json | 10 +- .../regnet_amr_sbml/Kynurenine_pathway.json | 412 ++++---- .../regnet_amr_sbml/NLRP3_Activation.json | 94 +- .../regnet_amr_sbml/Nsp14.json | 942 +++++++++--------- .../regnet_amr_sbml/Nsp4_Nsp6.json | 24 +- .../regnet_amr_sbml/Nsp9_protein.json | 272 ++--- .../regnet_amr_sbml/Orf10_Cul2_pathway.json | 120 +-- .../regnet_amr_sbml/Orf3a.json | 44 +- .../regnet_amr_sbml/PAMP_signaling.json | 104 +- .../Pyrimidine_deprivation.json | 154 +-- .../RTC-and-transcription.json | 16 +- .../regnet_amr_sbml/Renin_angiotensin.json | 178 ++-- .../regnet_amr_sbml/TGFB_pathway.json | 34 +- .../Virus_replication_cycle.json | 320 +++--- 24 files changed, 2006 insertions(+), 2004 deletions(-) diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index 021c694d8..6dcdb65ed 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -132,6 +132,7 @@ def __init__(self, model: Model): # Possibilities are: # - ControlledReplication / GroupedControlledProduction # - ControlledDegradation / GroupedControlledDegradation + # - ControlledProduction if the control and produced concept are not the same else: # If we have multiple controls then the thing that replicates # is both a control and a produced variable. @@ -146,7 +147,7 @@ def __init__(self, model: Model): # There is one corner case where both controllers are also # the same as the produced variable, in which case. if not indep_ctrl: - indep_ctrl = {transition.consumed[0].key} + indep_ctrl = {transition.produced[0].key} for controller in indep_ctrl: self.create_edge( @@ -163,7 +164,7 @@ def __init__(self, model: Model): transition.consumed[0].key } # There is one corner case where both controllers are also - # the same as the produced variable, in which case. + # the same as the consumed variable, in which case. if not indep_ctrl: indep_ctrl = {transition.consumed[0].key} @@ -177,6 +178,7 @@ def __init__(self, model: Model): edge_id += 1 else: + # ControlledProduction if produced and controller are not the same # ControlledDegradation target = vmap[ transition.consumed[0].key diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json index 49e808ff4..8eca998fb 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Apoptosis.json @@ -411,13 +411,13 @@ }, { "id": "t7", - "source": "TRADD", + "source": "FADD", "target": "TRADD/FADD_complex", "sign": true }, { "id": "t8", - "source": "FADD", + "source": "TRADD", "target": "TRADD/FADD_complex", "sign": true }, @@ -429,7 +429,7 @@ }, { "id": "t10", - "source": "AKT1", + "source": "CASP9_cell", "target": "Apoptosome_complex", "sign": true }, @@ -441,7 +441,7 @@ }, { "id": "t12", - "source": "CASP9_cell", + "source": "AKT1", "target": "Apoptosome_complex", "sign": true }, @@ -465,7 +465,7 @@ }, { "id": "t16", - "source": "BID", + "source": "BCL2/MCL1/BCL2L1_complex", "target": "BAX", "sign": true }, @@ -477,7 +477,7 @@ }, { "id": "t18", - "source": "BCL2/MCL1/BCL2L1_complex", + "source": "BID", "target": "BAX", "sign": true }, @@ -489,13 +489,13 @@ }, { "id": "t20", - "source": "BAX", + "source": "MAPK14", "target": "CYCS", "sign": true }, { "id": "t21", - "source": "MAPK14", + "source": "BAX", "target": "CYCS", "sign": true }, @@ -525,79 +525,79 @@ }, { "id": "t26", - "source": "CASP9_cell_active", + "source": "CASP8", "target": "CASP3", "sign": true }, { "id": "t27", - "source": "CASP8", + "source": "CASP9_cell_active", "target": "CASP3", "sign": true }, { "id": "t28", - "source": "TRADD/FADD_complex", + "source": "FADD", "target": "CASP8", "sign": true }, { "id": "t29", - "source": "Orf3a", + "source": "TRADD/FADD_complex", "target": "CASP8", "sign": true }, { "id": "t30", - "source": "FADD", + "source": "Orf3a", "target": "CASP8", "sign": true }, { "id": "t31", - "source": "CASP3", + "source": "N", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t32", - "source": "N", + "source": "S", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t33", - "source": "Orf8a", + "source": "Orf9b", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t34", - "source": "Orf9b", + "source": "CASP3", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t35", - "source": "Orf3b", + "source": "CASP7", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t36", - "source": "Orf6", + "source": "Orf8a", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t37", - "source": "S", + "source": "Orf3b", "target": "Apoptosis_phenotype", "sign": true }, { "id": "t38", - "source": "CASP7", + "source": "Orf6", "target": "Apoptosis_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json index 758c9803e..94184185c 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/BIOMD0000000562.json @@ -423,13 +423,13 @@ }, { "id": "t29", - "source": "egfr", + "source": "ph", "target": "sos", "sign": true }, { "id": "t30", - "source": "ph", + "source": "egfr", "target": "sos", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json index 128593bc0..5154e2841 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Coagulation-pathway.json @@ -1461,13 +1461,13 @@ "edges": [ { "id": "t1", - "source": "KLKB1", + "source": "KNG1", "target": "KNG1:KLKB1_complex", "sign": true }, { "id": "t2", - "source": "KNG1", + "source": "KLKB1", "target": "KNG1:KLKB1_complex", "sign": true }, @@ -1503,13 +1503,13 @@ }, { "id": "t8", - "source": "PLAT_blood", + "source": "SERPINE1", "target": "PLAT:SERPINE1_complex", "sign": true }, { "id": "t9", - "source": "SERPINE1", + "source": "PLAT_blood", "target": "PLAT:SERPINE1_complex", "sign": true }, @@ -1539,13 +1539,13 @@ }, { "id": "t14", - "source": "Thrombomodulin", + "source": "Thrombin_blood_active", "target": "Thrombin:Thrombomodulin_complex", "sign": true }, { "id": "t15", - "source": "Thrombin_blood_active", + "source": "Thrombomodulin", "target": "Thrombin:Thrombomodulin_complex", "sign": true }, @@ -1575,25 +1575,25 @@ }, { "id": "t20", - "source": "C5b:C6_complex", + "source": "C7", "target": "C5b:C6:C7_complex", "sign": true }, { "id": "t21", - "source": "C7", + "source": "C5b:C6_complex", "target": "C5b:C6:C7_complex", "sign": true }, { "id": "t22", - "source": "C9", + "source": "SARS-CoV-2 infection_phenotype", "target": "C5b-9_complex_endothelium, vascular", "sign": true }, { "id": "t23", - "source": "SARS-CoV-2 infection_phenotype", + "source": "C9", "target": "C5b-9_complex_endothelium, vascular", "sign": true }, @@ -1605,25 +1605,25 @@ }, { "id": "t25", - "source": "C6", + "source": "C5b", "target": "C5b:C6_complex", "sign": true }, { "id": "t26", - "source": "C5b", + "source": "C6", "target": "C5b:C6_complex", "sign": true }, { "id": "t27", - "source": "C4b", + "source": "C2a", "target": "C2a:C4b_complex", "sign": true }, { "id": "t28", - "source": "C2a", + "source": "C4b", "target": "C2a:C4b_complex", "sign": true }, @@ -1641,19 +1641,19 @@ }, { "id": "t31", - "source": "SARS-CoV-2 infection_phenotype", + "source": "SERPINF2", "target": "SERPINF2:Plasmin_complex", "sign": true }, { "id": "t32", - "source": "Plasmin", + "source": "SARS-CoV-2 infection_phenotype", "target": "SERPINF2:Plasmin_complex", "sign": true }, { "id": "t33", - "source": "SERPINF2", + "source": "Plasmin", "target": "SERPINF2:Plasmin_complex", "sign": true }, @@ -1671,25 +1671,25 @@ }, { "id": "t36", - "source": "VWF", + "source": "GP6:alpha2:beta1_complex", "target": "GP6:alpha2beta1:VWF_complex", "sign": true }, { "id": "t37", - "source": "GP6:alpha2:beta1_complex", + "source": "VWF", "target": "GP6:alpha2beta1:VWF_complex", "sign": true }, { "id": "t38", - "source": "GP6", + "source": "ITGA2:ITGAB1_complex", "target": "GP6:alpha2:beta1_complex", "sign": true }, { "id": "t39", - "source": "ITGA2:ITGAB1_complex", + "source": "GP6", "target": "GP6:alpha2:beta1_complex", "sign": true }, @@ -1701,97 +1701,97 @@ }, { "id": "t41", - "source": "F12", + "source": "KLKB1", "target": "F12a", "sign": true }, { "id": "t42", - "source": "KLKB1", + "source": "F12", "target": "F12a", "sign": true }, { "id": "t43", - "source": "F8", + "source": "ACE", "target": "Small peptide", "sign": true }, { "id": "t44", - "source": "ACE", + "source": "F10", "target": "Small peptide", "sign": true }, { "id": "t45", - "source": "Antithrombin", + "source": "F12", "target": "Small peptide", "sign": true }, { "id": "t46", - "source": "PROC", + "source": "Bradykinin", "target": "Small peptide", "sign": true }, { "id": "t47", - "source": "F10", + "source": "F8", "target": "Small peptide", "sign": true }, { "id": "t48", - "source": "F12", + "source": "KLKB1", "target": "Small peptide", "sign": true }, { "id": "t49", - "source": "KLKB1", + "source": "PROC", "target": "Small peptide", "sign": true }, { "id": "t50", - "source": "F9a", + "source": "Thrombin_blood_active", "target": "Small peptide", "sign": true }, { "id": "t51", - "source": "Thrombin_blood_active", + "source": "Antithrombin", "target": "Small peptide", "sign": true }, { "id": "t52", - "source": "Bradykinin", + "source": "F9a", "target": "Small peptide", "sign": true }, { "id": "t53", - "source": "Thrombin_blood_active", + "source": "F12a", "target": "F11", "sign": true }, { "id": "t54", - "source": "F12a", + "source": "Thrombin_blood_active", "target": "F11", "sign": true }, { "id": "t55", - "source": "Thrombin_blood_active", + "source": "F12a", "target": "F11a", "sign": true }, { "id": "t56", - "source": "F12a", + "source": "Thrombin_blood_active", "target": "F11a", "sign": true }, @@ -1815,13 +1815,13 @@ }, { "id": "t60", - "source": "F10", + "source": "Antithrombin", "target": "F10a", "sign": true }, { "id": "t61", - "source": "Antithrombin", + "source": "F10", "target": "F10a", "sign": true }, @@ -1869,19 +1869,19 @@ }, { "id": "t69", - "source": "SARS-CoV-2 infection_phenotype", + "source": "ACE", "target": "angiotensin II_simple_molecule", "sign": true }, { "id": "t70", - "source": "ACE", + "source": "angiotensin I_simple_molecule", "target": "angiotensin II_simple_molecule", "sign": true }, { "id": "t71", - "source": "angiotensin I_simple_molecule", + "source": "SARS-CoV-2 infection_phenotype", "target": "angiotensin II_simple_molecule", "sign": true }, @@ -1923,13 +1923,13 @@ }, { "id": "t78", - "source": "Thrombin:Thrombomodulin_complex", + "source": "PROC", "target": "F5a", "sign": true }, { "id": "t79", - "source": "PROC", + "source": "Thrombin:Thrombomodulin_complex", "target": "F5a", "sign": true }, @@ -1965,19 +1965,19 @@ }, { "id": "t85", - "source": "Fibrin polymer", + "source": "Plasmin", "target": "D-dimer", "sign": true }, { "id": "t86", - "source": "Plasmin", + "source": "TAFI", "target": "D-dimer", "sign": true }, { "id": "t87", - "source": "TAFI", + "source": "Fibrin polymer", "target": "D-dimer", "sign": true }, @@ -1989,43 +1989,43 @@ }, { "id": "t89", - "source": "PLAU", + "source": "F11a", "target": "Plasmin", "sign": true }, { "id": "t90", - "source": "F11a", + "source": "Plasminogen", "target": "Plasmin", "sign": true }, { "id": "t91", - "source": "Plasminogen", + "source": "PLAT_blood_active", "target": "Plasmin", "sign": true }, { "id": "t92", - "source": "KLKB1", + "source": "PLAU", "target": "Plasmin", "sign": true }, { "id": "t93", - "source": "PLAT_blood_active", + "source": "KLKB1", "target": "Plasmin", "sign": true }, { "id": "t94", - "source": "PROC", + "source": "Bradykinin", "target": "PLAT_blood_active", "sign": true }, { "id": "t95", - "source": "angiotensin I-7_simple_molecule", + "source": "SERPINE1", "target": "PLAT_blood_active", "sign": true }, @@ -2037,25 +2037,25 @@ }, { "id": "t97", - "source": "PLAT_blood", + "source": "angiotensin I-7_simple_molecule", "target": "PLAT_blood_active", "sign": true }, { "id": "t98", - "source": "SERPINE1", + "source": "PLAT_blood", "target": "PLAT_blood_active", "sign": true }, { "id": "t99", - "source": "Bradykinin", + "source": "PROC", "target": "PLAT_blood_active", "sign": true }, { "id": "t100", - "source": "AGTR1_blood", + "source": "angiotensin II_simple_molecule", "target": "SERPINE1", "sign": true }, @@ -2067,19 +2067,19 @@ }, { "id": "t102", - "source": "angiotensin II_simple_molecule", + "source": "IL6", "target": "SERPINE1", "sign": true }, { "id": "t103", - "source": "aldosterone_simple_molecule_blood", + "source": "AGTR1_blood", "target": "SERPINE1", "sign": true }, { "id": "t104", - "source": "IL6", + "source": "aldosterone_simple_molecule_blood", "target": "SERPINE1", "sign": true }, @@ -2139,13 +2139,13 @@ }, { "id": "t114", - "source": "KLKB1", + "source": "F12a", "target": "Kallikrein", "sign": true }, { "id": "t115", - "source": "F12a", + "source": "KLKB1", "target": "Kallikrein", "sign": true }, @@ -2163,31 +2163,31 @@ }, { "id": "t118", - "source": "C2a:C4b_complex", + "source": "SARS-CoV-2 infection_phenotype", "target": "C5a", "sign": true }, { "id": "t119", - "source": "SARS-CoV-2 infection_phenotype", + "source": "C5", "target": "C5a", "sign": true }, { "id": "t120", - "source": "C5", + "source": "Plasmin", "target": "C5a", "sign": true }, { "id": "t121", - "source": "Plasmin", + "source": "C2a:C4b_complex", "target": "C5a", "sign": true }, { "id": "t122", - "source": "VWF", + "source": "C5b-9_complex_endothelium, vascular", "target": "Thrombosis_phenotype_blood", "sign": true }, @@ -2205,13 +2205,13 @@ }, { "id": "t125", - "source": "CRP", + "source": "IL1B", "target": "Thrombosis_phenotype_blood", "sign": true }, { "id": "t126", - "source": "C5b-9_complex_endothelium, vascular", + "source": "C4d", "target": "Thrombosis_phenotype_blood", "sign": true }, @@ -2223,19 +2223,19 @@ }, { "id": "t128", - "source": "IL2RA", + "source": "CRP", "target": "Thrombosis_phenotype_blood", "sign": true }, { "id": "t129", - "source": "C4d", + "source": "IL2RA", "target": "Thrombosis_phenotype_blood", "sign": true }, { "id": "t130", - "source": "IL1B", + "source": "VWF", "target": "Thrombosis_phenotype_blood", "sign": true }, @@ -2313,7 +2313,7 @@ }, { "id": "t143", - "source": "C2a:C4b_complex", + "source": "C3b:Bb:C3b_complex", "target": "C5b", "sign": true }, @@ -2325,7 +2325,7 @@ }, { "id": "t145", - "source": "C3b:Bb:C3b_complex", + "source": "C2a:C4b_complex", "target": "C5b", "sign": true }, @@ -2361,37 +2361,37 @@ }, { "id": "t151", - "source": "C2", + "source": "MASP1", "target": "C2a", "sign": true }, { "id": "t152", - "source": "MASP1", + "source": "C2", "target": "C2a", "sign": true }, { "id": "t153", - "source": "C2", + "source": "MASP1", "target": "C2b", "sign": true }, { "id": "t154", - "source": "MASP1", + "source": "C2", "target": "C2b", "sign": true }, { "id": "t155", - "source": "CFI", + "source": "SARS-CoV-2 infection_phenotype", "target": "C4d", "sign": true }, { "id": "t156", - "source": "SARS-CoV-2 infection_phenotype", + "source": "CFI", "target": "C4d", "sign": true }, @@ -2481,13 +2481,13 @@ }, { "id": "t171", - "source": "ACE", + "source": "Bradykinin", "target": "Bradykinin(1-5)", "sign": true }, { "id": "t172", - "source": "Bradykinin", + "source": "ACE", "target": "Bradykinin(1-5)", "sign": true }, @@ -2589,25 +2589,25 @@ }, { "id": "t189", - "source": "AGTR1_blood", + "source": "SARS-CoV-2 infection_phenotype", "target": "aldosterone_simple_molecule_blood", "sign": true }, { "id": "t190", - "source": "K+_ion", + "source": "angiotensin II_simple_molecule", "target": "aldosterone_simple_molecule_blood", "sign": true }, { "id": "t191", - "source": "angiotensin II_simple_molecule", + "source": "K+_ion", "target": "aldosterone_simple_molecule_blood", "sign": true }, { "id": "t192", - "source": "SARS-CoV-2 infection_phenotype", + "source": "AGTR1_blood", "target": "aldosterone_simple_molecule_blood", "sign": true }, @@ -2655,13 +2655,13 @@ }, { "id": "t200", - "source": "NR3C2", + "source": "AGTR1_blood", "target": "Thrombosis_phenotype_human host", "sign": true }, { "id": "t201", - "source": "AGTR1_blood", + "source": "NR3C2", "target": "Thrombosis_phenotype_human host", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json index 2f5c20eff..509484473 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/ER_Stress.json @@ -1957,73 +1957,73 @@ }, { "id": "t2", - "source": "EIF2S1_phosphorylated", + "source": "EIF2S2", "target": "EIF2-P:GDP_complex", "sign": true }, { "id": "t3", - "source": "EIF2S2", + "source": "EIF2S1_phosphorylated", "target": "EIF2-P:GDP_complex", "sign": true }, { "id": "t4", - "source": "BAX_endoplasmic reticulum", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t5", - "source": "BAX:ERN1_complex", + "source": "BCL2", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t6", - "source": "BCL2L1", + "source": "ERN1:Unfolded_space_protein_complex", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t7", - "source": "ERN1:Unfolded_space_protein_complex", + "source": "BCL2L1", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t8", - "source": "BCL2", + "source": "TRAF2", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t9", - "source": "TRAF2", + "source": "BAK1", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t10", - "source": "BAK1", + "source": "BAX:ERN1_complex", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t11", - "source": "BAK1:ERN1_complex", + "source": "BAX_endoplasmic reticulum", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t12", - "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "source": "BAK1:ERN1_complex", "target": "TRAF2:ERN1_complex", "sign": true }, { "id": "t13", - "source": "Ca2+space_ER_space_depletion_phenotype", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", "target": "SIGMAR1:ITPR3_complex", "sign": true }, @@ -2035,31 +2035,31 @@ }, { "id": "t15", - "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "source": "ER_space_stress_phenotype", "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t16", - "source": "ER_space_stress_phenotype", + "source": "Ca2+space_ER_space_depletion_phenotype", "target": "SIGMAR1:ITPR3_complex", "sign": true }, { "id": "t17", - "source": "Met-tRNA_rna", + "source": "Ternary_space_Complex_complex", "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t18", - "source": "Ternary_space_Complex_complex", + "source": "GDP_simple_molecule", "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, { "id": "t19", - "source": "GDP_simple_molecule", + "source": "Met-tRNA_rna", "target": "EIF2:GDP:Met-tRNA_complex", "sign": true }, @@ -2071,13 +2071,13 @@ }, { "id": "t21", - "source": "SQSTM1_space_", + "source": "CASP8:CASP8-ubq:FADD_complex", "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t22", - "source": "MAP1LC3A", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, @@ -2089,19 +2089,19 @@ }, { "id": "t24", - "source": "CASP8:CASP8-ubq:FADD_complex", + "source": "TRIM13", "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t25", - "source": "TRIM13", + "source": "MAP1LC3A", "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, { "id": "t26", - "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "source": "SQSTM1_space_", "target": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "sign": true }, @@ -2119,13 +2119,13 @@ }, { "id": "t29", - "source": "SIGMAR1_endoplasmic reticulum", + "source": "HSPA5_endoplasmic reticulum", "target": "SIGMAR1:HSPA5_complex", "sign": true }, { "id": "t30", - "source": "HSPA5_endoplasmic reticulum", + "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1:HSPA5_complex", "sign": true }, @@ -2143,7 +2143,7 @@ }, { "id": "t33", - "source": "EIF2B_complex", + "source": "EIF2:GDP:Met-tRNA_complex", "target": "Ternary_space_Complex_complex", "sign": true }, @@ -2155,19 +2155,19 @@ }, { "id": "t35", - "source": "EIF2:GDP:Met-tRNA_complex", + "source": "EIF2B_complex", "target": "Ternary_space_Complex_complex", "sign": true }, { "id": "t36", - "source": "PACS2_early_space_endosome", + "source": "ADAM17_early_space_endosome", "target": "PACS2-ADAM17_space_interaction_complex", "sign": true }, { "id": "t37", - "source": "ADAM17_early_space_endosome", + "source": "PACS2_early_space_endosome", "target": "PACS2-ADAM17_space_interaction_complex", "sign": true }, @@ -2185,19 +2185,19 @@ }, { "id": "t40", - "source": "MFN2_endoplasmic reticulum", + "source": "MFN2_mitochondrion", "target": "MFN2:MFN2_complex", "sign": true }, { "id": "t41", - "source": "MFN2_mitochondrion", + "source": "MFN2_endoplasmic reticulum", "target": "MFN2:MFN2_complex", "sign": true }, { "id": "t42", - "source": "BBC3", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", "target": "ERN1:BBC3_complex", "sign": true }, @@ -2209,7 +2209,7 @@ }, { "id": "t44", - "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "source": "BBC3", "target": "ERN1:BBC3_complex", "sign": true }, @@ -2233,43 +2233,43 @@ }, { "id": "t48", - "source": "MFN2_endoplasmic reticulum", + "source": "MFN1", "target": "MFN1:MFN2_complex", "sign": true }, { "id": "t49", - "source": "MFN1", + "source": "MFN2_endoplasmic reticulum", "target": "MFN1:MFN2_complex", "sign": true }, { "id": "t50", - "source": "MCU2", + "source": "MCU1", "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t51", - "source": "SMDT1", + "source": "MCU2", "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t52", - "source": "MCU1", + "source": "MCU", "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t53", - "source": "MCU", + "source": "SMDT1", "target": "MCU:MICU1:MICU2:SMDT1_complex", "sign": true }, { "id": "t54", - "source": "BCL2L11_endoplasmic reticulum", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", "target": "ERN1:BCL2L11_complex", "sign": true }, @@ -2281,19 +2281,19 @@ }, { "id": "t56", - "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "source": "BCL2L11_endoplasmic reticulum", "target": "ERN1:BCL2L11_complex", "sign": true }, { "id": "t57", - "source": "CAPN1", + "source": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", "target": "CAPN1:Ca2+_complex", "sign": true }, { "id": "t58", - "source": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", + "source": "CAPN1", "target": "CAPN1:Ca2+_complex", "sign": true }, @@ -2305,19 +2305,19 @@ }, { "id": "t60", - "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", + "source": "EIF2AK3", "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, { "id": "t61", - "source": "Unfolded_space_protein", + "source": "Persistant_space_ER_space_Stress_phenotype_endoplasmic reticulum", "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, { "id": "t62", - "source": "EIF2AK3", + "source": "Unfolded_space_protein", "target": "EIF2AK3:EIF2AK3_complex", "sign": true }, @@ -2329,25 +2329,25 @@ }, { "id": "t64", - "source": "ACE2", + "source": "S", "target": "ACE2:Spike_complex", "sign": true }, { "id": "t65", - "source": "S", + "source": "ACE2", "target": "ACE2:Spike_complex", "sign": true }, { "id": "t66", - "source": "HSPA5_default_compartment", + "source": "S", "target": "HSPA5-Spike interaction_complex", "sign": true }, { "id": "t67", - "source": "S", + "source": "HSPA5_default_compartment", "target": "HSPA5-Spike interaction_complex", "sign": true }, @@ -2371,13 +2371,13 @@ }, { "id": "t71", - "source": "ATF4", + "source": "DDIT3", "target": "PPP1R15A_rna", "sign": true }, { "id": "t72", - "source": "DDIT3", + "source": "ATF4", "target": "PPP1R15A_rna", "sign": true }, @@ -2401,7 +2401,7 @@ }, { "id": "t76", - "source": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", + "source": "MBTPS2", "target": "ATF6_Golgi apparatus", "sign": true }, @@ -2413,13 +2413,13 @@ }, { "id": "t78", - "source": "MBTPS2", + "source": "ATF6_endoplasmic reticulum", "target": "ATF6_Golgi apparatus", "sign": true }, { "id": "t79", - "source": "ATF6_endoplasmic reticulum", + "source": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", "target": "ATF6_Golgi apparatus", "sign": true }, @@ -2449,55 +2449,55 @@ }, { "id": "t84", - "source": "ER_space_stress_phenotype", + "source": "Ca2+space_ER_space_depletion_phenotype", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t85", - "source": "SIGMAR1:HSPA5_complex", + "source": "Unfolded_space_protein", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t86", - "source": "ACE2", + "source": "SIGMAR1:HSPA5_complex", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t87", - "source": "Ca2+space_ER_space_depletion_phenotype", + "source": "ATF6:HSPA5_complex", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t88", - "source": "Unfolded_space_protein", + "source": "HSPA5_rna", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t89", - "source": "ATF6:HSPA5_complex", + "source": "ER_space_stress_phenotype", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t90", - "source": "HSPA5_rna", + "source": "ACE2", "target": "HSPA5_endoplasmic reticulum", "sign": true }, { "id": "t91", - "source": "TMBIM6", + "source": "ERO1A_endoplasmic reticulum", "target": "ITPR", "sign": true }, { "id": "t92", - "source": "ERO1A_endoplasmic reticulum", + "source": "TMBIM6", "target": "ITPR", "sign": true }, @@ -2521,43 +2521,43 @@ }, { "id": "t96", - "source": "ACE2", + "source": "S", "target": "HSPA5_rna", "sign": true }, { "id": "t97", - "source": "S", + "source": "ACE2", "target": "HSPA5_rna", "sign": true }, { "id": "t98", - "source": "ATF6_Golgi apparatus", + "source": "EIF2AK3:EIF2AK3_complex", "target": "UPR_phenotype", "sign": true }, { "id": "t99", - "source": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", + "source": "XBP1", "target": "UPR_phenotype", "sign": true }, { "id": "t100", - "source": "XBP1", + "source": "ATF6_Golgi apparatus", "target": "UPR_phenotype", "sign": true }, { "id": "t101", - "source": "EIF2AK3:EIF2AK3_complex", + "source": "TRAF2:ERN1_complex", "target": "UPR_phenotype", "sign": true }, { "id": "t102", - "source": "TRAF2:ERN1_complex", + "source": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", "target": "UPR_phenotype", "sign": true }, @@ -2569,13 +2569,13 @@ }, { "id": "t104", - "source": "FIS1", + "source": "VAPB", "target": "Ca2+space_mitochondrial_space_concentration_phenotype", "sign": true }, { "id": "t105", - "source": "VAPB", + "source": "FIS1", "target": "Ca2+space_mitochondrial_space_concentration_phenotype", "sign": true }, @@ -2611,31 +2611,31 @@ }, { "id": "t111", - "source": "ATF4", + "source": "DDIT3_gene", "target": "DDIT3_rna", "sign": true }, { "id": "t112", - "source": "Persistant_space_ER_space_Stress_phenotype_cell", + "source": "XBP1", "target": "DDIT3_rna", "sign": true }, { "id": "t113", - "source": "XBP1", + "source": "ATF4", "target": "DDIT3_rna", "sign": true }, { "id": "t114", - "source": "ATF6_nucleus", + "source": "Persistant_space_ER_space_Stress_phenotype_cell", "target": "DDIT3_rna", "sign": true }, { "id": "t115", - "source": "DDIT3_gene", + "source": "ATF6_nucleus", "target": "DDIT3_rna", "sign": true }, @@ -2665,19 +2665,19 @@ }, { "id": "t120", - "source": "DDIT3", + "source": "TRIB3_gene", "target": "TRIB3_rna", "sign": true }, { "id": "t121", - "source": "TRIB3_gene", + "source": "DDIT3", "target": "TRIB3_rna", "sign": true }, { "id": "t122", - "source": "ITPR3:HSPA9:VDAC1_complex", + "source": "SIGMAR1:ITPR3_complex", "target": "Ca2+_ion_mitochondrion", "sign": true }, @@ -2689,7 +2689,7 @@ }, { "id": "t124", - "source": "SIGMAR1:ITPR3_complex", + "source": "ITPR3:HSPA9:VDAC1_complex", "target": "Ca2+_ion_mitochondrion", "sign": true }, @@ -2701,49 +2701,49 @@ }, { "id": "t126", - "source": "PPP1R15A", + "source": "EIF2S1_phosphorylated", "target": "EIF2S1", "sign": true }, { "id": "t127", - "source": "EIF2S1_phosphorylated", + "source": "EIF2AK1", "target": "EIF2S1", "sign": true }, { "id": "t128", - "source": "EIF2AK1", + "source": "PPP1R15A", "target": "EIF2S1", "sign": true }, { "id": "t129", - "source": "cleaved~CASP4", + "source": "CASP9", "target": "cleaved~CASP9", "sign": true }, { "id": "t130", - "source": "CASP9", + "source": "cleaved~CASP4", "target": "cleaved~CASP9", "sign": true }, { "id": "t131", - "source": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", + "source": "ITPR3", "target": "RMDN3", "sign": false }, { "id": "t132", - "source": "ITPR3", + "source": "VAPB", "target": "RMDN3", "sign": false }, { "id": "t133", - "source": "VAPB", + "source": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "target": "RMDN3", "sign": false }, @@ -2767,13 +2767,13 @@ }, { "id": "t137", - "source": "Ca2+space_ER_space_depletion_phenotype", + "source": "ER_space_stress_phenotype", "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", "sign": true }, { "id": "t138", - "source": "ER_space_stress_phenotype", + "source": "Ca2+space_ER_space_depletion_phenotype", "target": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", "sign": true }, @@ -2785,55 +2785,55 @@ }, { "id": "t140", - "source": "ERN1:BCL2L11_complex", + "source": "XBP1_gene", "target": "XBP1_rna", "sign": true }, { "id": "t141", - "source": "ERN1:BBC3_complex", + "source": "ERN1:BCL2L11_complex", "target": "XBP1_rna", "sign": true }, { "id": "t142", - "source": "ATF6_nucleus", + "source": "TRAF2:ERN1_complex", "target": "XBP1_rna", "sign": true }, { "id": "t143", - "source": "TRAF2:ERN1_complex", + "source": "ATF6_nucleus", "target": "XBP1_rna", "sign": true }, { "id": "t144", - "source": "XBP1_gene", + "source": "ERN1:BBC3_complex", "target": "XBP1_rna", "sign": true }, { "id": "t145", - "source": "Unfolded_space_protein", + "source": "ERAD_phenotype", "target": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", "sign": true }, { "id": "t146", - "source": "ERAD_phenotype", + "source": "Unfolded_space_protein", "target": "accumulation_space_of_space_misfolded_space_protein_space_in_space_ER_phenotype", "sign": true }, { "id": "t147", - "source": "BCL2_gene", + "source": "DDIT3_phosphorylated", "target": "BCL2_rna", "sign": true }, { "id": "t148", - "source": "DDIT3_phosphorylated", + "source": "BCL2_gene", "target": "BCL2_rna", "sign": true }, @@ -2857,13 +2857,13 @@ }, { "id": "t152", - "source": "MAPK14", + "source": "MAP3K5_phosphorylated", "target": "MAPK14_phosphorylated", "sign": true }, { "id": "t153", - "source": "MAP3K5_phosphorylated", + "source": "MAPK14", "target": "MAPK14_phosphorylated", "sign": true }, @@ -2899,13 +2899,13 @@ }, { "id": "t159", - "source": "presence_space_of_space_dsRNA_phenotype", + "source": "DNAJC3", "target": "EIF2AK2", "sign": true }, { "id": "t160", - "source": "DNAJC3", + "source": "presence_space_of_space_dsRNA_phenotype", "target": "EIF2AK2", "sign": true }, @@ -2929,43 +2929,43 @@ }, { "id": "t164", - "source": "MAPK8_phosphorylated", + "source": "MAPK14_phosphorylated", "target": "BAX_phosphorylated", "sign": true }, { "id": "t165", - "source": "MAPK14_phosphorylated", + "source": "MAPK8_phosphorylated", "target": "BAX_phosphorylated", "sign": true }, { "id": "t166", - "source": "EIF2AK3:EIF2AK3_complex", + "source": "ATF6_endoplasmic reticulum", "target": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", "sign": true }, { "id": "t167", - "source": "ATF6_endoplasmic reticulum", + "source": "EIF2AK3:EIF2AK3_complex", "target": "retrograde_space_transport_space_from_space_ER_space_to_space_cytosol_phenotype", "sign": true }, { "id": "t168", - "source": "MAP3K4_phosphorylated", + "source": "MAPK8", "target": "MAPK8_phosphorylated", "sign": true }, { "id": "t169", - "source": "MAPK8", + "source": "MAP3K5_phosphorylated", "target": "MAPK8_phosphorylated", "sign": true }, { "id": "t170", - "source": "MAP3K5_phosphorylated", + "source": "MAP3K4_phosphorylated", "target": "MAPK8_phosphorylated", "sign": true }, @@ -3013,7 +3013,7 @@ }, { "id": "t178", - "source": "ACE2", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", "target": "ER_space_stress_phenotype", "sign": true }, @@ -3025,7 +3025,7 @@ }, { "id": "t180", - "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "source": "ACE2", "target": "ER_space_stress_phenotype", "sign": true }, @@ -3037,97 +3037,97 @@ }, { "id": "t182", - "source": "cleaved~CASP4", + "source": "CASP3", "target": "cleaved~CASP3", "sign": true }, { "id": "t183", - "source": "CASP3", + "source": "cleaved~CASP4", "target": "cleaved~CASP3", "sign": true }, { "id": "t184", - "source": "EIF2S1", + "source": "EIF2AK3:EIF2AK3_complex", "target": "EIF2S1_phosphorylated", "sign": true }, { "id": "t185", - "source": "GCN2:ATP_complex", + "source": "EIF2AK2", "target": "EIF2S1_phosphorylated", "sign": true }, { "id": "t186", - "source": "EIF2AK2", + "source": "DNAJC3", "target": "EIF2S1_phosphorylated", "sign": true }, { "id": "t187", - "source": "DNAJC3", + "source": "EIF2S1", "target": "EIF2S1_phosphorylated", "sign": true }, { "id": "t188", - "source": "EIF2AK3:EIF2AK3_complex", + "source": "GCN2:ATP_complex", "target": "EIF2S1_phosphorylated", "sign": true }, { "id": "t189", - "source": "PACS2_endoplasmic reticulum", + "source": "MFN1:MFN2_complex", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { "id": "t190", - "source": "MFN1:MFN2_complex", + "source": "VAPB:RMDN3_complex", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { "id": "t191", - "source": "FIS1:BCAP31_complex", + "source": "PACS2_endoplasmic reticulum", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { "id": "t192", - "source": "MFN2:MFN2_complex", + "source": "FIS1:BCAP31_complex", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { "id": "t193", - "source": "VAPB:RMDN3_complex", + "source": "MFN2:MFN2_complex", "target": "mitochondrion-endoplasmic_space_reticulum_space_membrane_space_tethering_space__phenotype", "sign": true }, { "id": "t194", - "source": "DDIT3", + "source": "AP-1", "target": "AP-1_phosphorylated_phosphorylated", "sign": true }, { "id": "t195", - "source": "MAPK8_phosphorylated", + "source": "DDIT3", "target": "AP-1_phosphorylated_phosphorylated", "sign": true }, { "id": "t196", - "source": "AP-1", + "source": "MAPK8_phosphorylated", "target": "AP-1_phosphorylated_phosphorylated", "sign": true }, { "id": "t197", - "source": "EIF2B_complex", + "source": "EIF2:GDP:Met-tRNA_complex", "target": "GDP_simple_molecule", "sign": true }, @@ -3139,7 +3139,7 @@ }, { "id": "t199", - "source": "EIF2:GDP:Met-tRNA_complex", + "source": "EIF2B_complex", "target": "GDP_simple_molecule", "sign": true }, @@ -3193,25 +3193,25 @@ }, { "id": "t208", - "source": "TRAF2:ERN1_complex", + "source": "MAP3K5", "target": "MAP3K5_phosphorylated", "sign": true }, { "id": "t209", - "source": "MAP3K5", + "source": "TRAF2", "target": "MAP3K5_phosphorylated", "sign": true }, { "id": "t210", - "source": "TRAF2", + "source": "TRAF2:ERN1_complex", "target": "MAP3K5_phosphorylated", "sign": true }, { "id": "t211", - "source": "MFN2_endoplasmic reticulum", + "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", "target": "Apoptosis_phenotype_endoplasmic reticulum", "sign": true }, @@ -3223,19 +3223,19 @@ }, { "id": "t213", - "source": "SIGMAR1_mitochondria-associated endoplasmic reticulum membrane", + "source": "MFN2_endoplasmic reticulum", "target": "Apoptosis_phenotype_endoplasmic reticulum", "sign": true }, { "id": "t214", - "source": "DNAJC3_gene", + "source": "ATF6_nucleus", "target": "DNAJC3_rna", "sign": true }, { "id": "t215", - "source": "ATF6_nucleus", + "source": "DNAJC3_gene", "target": "DNAJC3_rna", "sign": true }, @@ -3277,7 +3277,7 @@ }, { "id": "t222", - "source": "DDIT3_phosphorylated", + "source": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", "target": "Apoptosis_phenotype_cell", "sign": true }, @@ -3289,37 +3289,37 @@ }, { "id": "t224", - "source": "MAPK14_phosphorylated", + "source": "DDIT3_phosphorylated", "target": "Apoptosis_phenotype_cell", "sign": true }, { "id": "t225", - "source": "BAX_phosphorylated", + "source": "BID_phosphorylated", "target": "Apoptosis_phenotype_cell", "sign": true }, { "id": "t226", - "source": "CASP8:FADD:MAP1LC3A:SQSTM1:ATG5_complex", + "source": "BAX_phosphorylated", "target": "Apoptosis_phenotype_cell", "sign": true }, { "id": "t227", - "source": "cleaved~CASP3", + "source": "TRIB3", "target": "Apoptosis_phenotype_cell", "sign": true }, { "id": "t228", - "source": "BID_phosphorylated", + "source": "MAPK14_phosphorylated", "target": "Apoptosis_phenotype_cell", "sign": true }, { "id": "t229", - "source": "TRIB3", + "source": "cleaved~CASP3", "target": "Apoptosis_phenotype_cell", "sign": true }, @@ -3361,13 +3361,13 @@ }, { "id": "t236", - "source": "Ca2+_ion_cell", + "source": "release_space_of_space_ER_space_Ca2+_phenotype", "target": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", "sign": true }, { "id": "t237", - "source": "release_space_of_space_ER_space_Ca2+_phenotype", + "source": "Ca2+_ion_cell", "target": "high_space_Ca2+space_cytosolic_space_concentration_phenotype", "sign": true }, @@ -3379,13 +3379,13 @@ }, { "id": "t239", - "source": "MFN2_endoplasmic reticulum", + "source": "HSPA5_endoplasmic reticulum", "target": "endoplasmic_space_reticulum_space_calcium_space_ion_space_homeostasis_phenotype", "sign": true }, { "id": "t240", - "source": "HSPA5_endoplasmic reticulum", + "source": "MFN2_endoplasmic reticulum", "target": "endoplasmic_space_reticulum_space_calcium_space_ion_space_homeostasis_phenotype", "sign": true }, @@ -3439,13 +3439,13 @@ }, { "id": "t249", - "source": "DDIT3", + "source": "ATF6_nucleus", "target": "ERO1A_rna", "sign": true }, { "id": "t250", - "source": "ATF6_nucleus", + "source": "DDIT3", "target": "ERO1A_rna", "sign": true }, @@ -3469,25 +3469,25 @@ }, { "id": "t254", - "source": "HSPA5-Spike interaction_complex", + "source": "SARS-CoV infection_phenotype", "target": "viral entry into host cell_phenotype", "sign": true }, { "id": "t255", - "source": "ACE2,_space_soluble", + "source": "ACE2-SARS-CoV interaction_complex", "target": "viral entry into host cell_phenotype", "sign": true }, { "id": "t256", - "source": "ACE2-SARS-CoV interaction_complex", + "source": "ACE2,_space_soluble", "target": "viral entry into host cell_phenotype", "sign": true }, { "id": "t257", - "source": "SARS-CoV infection_phenotype", + "source": "HSPA5-Spike interaction_complex", "target": "viral entry into host cell_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json index 6811ee491..746958cc9 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/ETC.json @@ -922,13 +922,13 @@ }, { "id": "t4", - "source": "F-ATPase_complex_mitochondrial matrix", + "source": "H+_ion_mitochondrion", "target": "ATP_space_Synthase_complex", "sign": true }, { "id": "t5", - "source": "H+_ion_mitochondrion", + "source": "F-ATPase_complex_mitochondrial matrix", "target": "ATP_space_Synthase_complex", "sign": true }, @@ -940,19 +940,19 @@ }, { "id": "t7", - "source": "Mt_space_translation_complex", + "source": "mt_space_mRNA_rna", "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t8", - "source": "Nsp8-affected Mt ribosomal proteins_complex", + "source": "Mt_space_translation_complex", "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, { "id": "t9", - "source": "mt_space_mRNA_rna", + "source": "Nsp8-affected Mt ribosomal proteins_complex", "target": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "sign": true }, @@ -964,13 +964,13 @@ }, { "id": "t11", - "source": "NDUFB9", + "source": "OXPHOS_space_factors_complex", "target": "Complex_space_1_complex", "sign": true }, { "id": "t12", - "source": "NDUFA1", + "source": "NDUFB9", "target": "Complex_space_1_complex", "sign": true }, @@ -982,7 +982,7 @@ }, { "id": "t14", - "source": "OXPHOS_space_factors_complex", + "source": "NDUFA1", "target": "Complex_space_1_complex", "sign": true }, @@ -1000,19 +1000,19 @@ }, { "id": "t17", - "source": "ACAD9", + "source": "NDUFAF7", "target": "OXPHOS_space_factors_complex", "sign": true }, { "id": "t18", - "source": "NDUFAF7", + "source": "ECSIT", "target": "OXPHOS_space_factors_complex", "sign": true }, { "id": "t19", - "source": "ECSIT", + "source": "ACAD9", "target": "OXPHOS_space_factors_complex", "sign": true }, @@ -1024,19 +1024,19 @@ }, { "id": "t21", - "source": "Q_simple_molecule_mitochondrial matrix", + "source": "SIRT3", "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t22", - "source": "SIRT3", + "source": "OXPHOS_space_factors_complex", "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, { "id": "t23", - "source": "OXPHOS_space_factors_complex", + "source": "Q_simple_molecule_mitochondrial matrix", "target": "complex_space_2_complex_mitochondrial matrix", "sign": true }, @@ -1048,19 +1048,19 @@ }, { "id": "t25", - "source": "Q_simple_molecule_mitochondrial matrix", + "source": "OXPHOS_space_factors_complex", "target": "complex_space_3_complex", "sign": true }, { "id": "t26", - "source": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", + "source": "Q_simple_molecule_mitochondrial matrix", "target": "complex_space_3_complex", "sign": true }, { "id": "t27", - "source": "OXPHOS_space_factors_complex", + "source": "mtDNA_space_encoded_space_OXPHOS_space_units_complex_mitochondrial matrix", "target": "complex_space_3_complex", "sign": true }, @@ -1144,25 +1144,25 @@ }, { "id": "t41", - "source": "Nsp6", + "source": "ATP5MG", "target": "F-ATPase:Nsp6_complex", "sign": true }, { "id": "t42", - "source": "ATP5MG", + "source": "Nsp6", "target": "F-ATPase:Nsp6_complex", "sign": true }, { "id": "t43", - "source": "H2O2_simple_molecule", + "source": "Fe2+_ion", "target": "Fe3+_ion", "sign": true }, { "id": "t44", - "source": "Fe2+_ion", + "source": "H2O2_simple_molecule", "target": "Fe3+_ion", "sign": true }, @@ -1174,7 +1174,7 @@ }, { "id": "t46", - "source": "paraquat_space_dication_complex", + "source": "superoxide_simple_molecule", "target": "paraquat_simple_molecule", "sign": true }, @@ -1186,7 +1186,7 @@ }, { "id": "t48", - "source": "superoxide_simple_molecule", + "source": "paraquat_space_dication_complex", "target": "paraquat_simple_molecule", "sign": true }, @@ -1222,13 +1222,13 @@ }, { "id": "t54", - "source": "H+_ion_mitochondrial matrix", + "source": "superoxide_simple_molecule", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t55", - "source": "superoxide_simple_molecule", + "source": "SOD2", "target": "H2O2_simple_molecule", "sign": true }, @@ -1240,19 +1240,19 @@ }, { "id": "t57", - "source": "SOD2", + "source": "H+_ion_mitochondrial matrix", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t58", - "source": "Fe3+_ion", + "source": "H2O2_simple_molecule", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t59", - "source": "H2O2_simple_molecule", + "source": "hydroxide_simple_molecule", "target": "H+_ion_mitochondrial matrix", "sign": true }, @@ -1264,7 +1264,7 @@ }, { "id": "t61", - "source": "hydroxide_simple_molecule", + "source": "Fe3+_ion", "target": "H+_ion_mitochondrial matrix", "sign": true }, @@ -1276,109 +1276,109 @@ }, { "id": "t63", - "source": "Complex_space_1_complex", + "source": "NADH_simple_molecule", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t64", - "source": "NADH_simple_molecule", + "source": "Complex_space_1_complex", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t65", - "source": "Mt-dNTP_space_pool_complex", + "source": "TFAM", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t66", - "source": "TFAM", + "source": "Mt-DNA_space_repair_complex", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t67", - "source": "Mt-DNA_space_repair_complex", + "source": "mt_space_DNA_space_replication_phenotype", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t68", - "source": "mt_space_DNA_space_damage_phenotype", + "source": "damaged_space_mt_space_DNA_gene", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t69", - "source": "damaged_space_mt_space_DNA_gene", + "source": "Mt-dNTP_space_pool_complex", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t70", - "source": "mt_space_DNA_space_replication_phenotype", + "source": "mt_space_DNA_space_damage_phenotype", "target": "mt_space_DNA_gene", "sign": true }, { "id": "t71", - "source": "Fe3+_ion", + "source": "superoxide_simple_molecule", "target": "Fe2+_ion", "sign": true }, { "id": "t72", - "source": "superoxide_simple_molecule", + "source": "Fe3+_ion", "target": "Fe2+_ion", "sign": true }, { "id": "t73", - "source": "GPX1", + "source": "TXN2", "target": "H2O_simple_molecule", "sign": true }, { "id": "t74", - "source": "GPX4", + "source": "PRDX_complex", "target": "H2O_simple_molecule", "sign": true }, { "id": "t75", - "source": "H2O2_simple_molecule", + "source": "GPX1", "target": "H2O_simple_molecule", "sign": true }, { "id": "t76", - "source": "CAT", + "source": "H2O2_simple_molecule", "target": "H2O_simple_molecule", "sign": true }, { "id": "t77", - "source": "TXN2", + "source": "hydroxide_simple_molecule", "target": "H2O_simple_molecule", "sign": true }, { "id": "t78", - "source": "hydroxide_simple_molecule", + "source": "glutathione_simple_molecule", "target": "H2O_simple_molecule", "sign": true }, { "id": "t79", - "source": "glutathione_simple_molecule", + "source": "GPX4", "target": "H2O_simple_molecule", "sign": true }, { "id": "t80", - "source": "PRDX_complex", + "source": "CAT", "target": "H2O_simple_molecule", "sign": true }, @@ -1390,13 +1390,13 @@ }, { "id": "t82", - "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "source": "H+_ion_mitochondrial matrix", "target": "Q_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t83", - "source": "H+_ion_mitochondrial matrix", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", "target": "Q_simple_molecule_mitochondrial matrix", "sign": true }, @@ -1414,37 +1414,37 @@ }, { "id": "t86", - "source": "H2O2_simple_molecule", + "source": "superoxide_simple_molecule", "target": "ROS_simple_molecule", "sign": true }, { "id": "t87", - "source": "hydroxide_simple_molecule", + "source": "H2O2_simple_molecule", "target": "ROS_simple_molecule", "sign": true }, { "id": "t88", - "source": "superoxide_simple_molecule", + "source": "hydroxide_simple_molecule", "target": "ROS_simple_molecule", "sign": true }, { "id": "t89", - "source": "NADPH_simple_molecule", + "source": "TXNRD2", "target": "TXN2", "sign": true }, { "id": "t90", - "source": "H2O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "TXN2", "sign": true }, { "id": "t91", - "source": "TXNRD2", + "source": "H2O2_simple_molecule", "target": "TXN2", "sign": true }, @@ -1456,43 +1456,43 @@ }, { "id": "t93", - "source": "GSR", + "source": "TXN2", "target": "NADP(+)_simple_molecule", "sign": true }, { "id": "t94", - "source": "TXNRD2", + "source": "glutathione_space_disulfide_simple_molecule", "target": "NADP(+)_simple_molecule", "sign": true }, { "id": "t95", - "source": "TXN2", + "source": "NADPH_simple_molecule", "target": "NADP(+)_simple_molecule", "sign": true }, { "id": "t96", - "source": "NADPH_simple_molecule", + "source": "TXNRD2", "target": "NADP(+)_simple_molecule", "sign": true }, { "id": "t97", - "source": "glutathione_space_disulfide_simple_molecule", + "source": "GSR", "target": "NADP(+)_simple_molecule", "sign": true }, { "id": "t98", - "source": "H2O2_simple_molecule", + "source": "Fe2+_ion", "target": "HO_simple_molecule", "sign": true }, { "id": "t99", - "source": "Fe2+_ion", + "source": "H2O2_simple_molecule", "target": "HO_simple_molecule", "sign": true }, @@ -1504,13 +1504,13 @@ }, { "id": "t101", - "source": "Fe3+_ion", + "source": "superoxide_simple_molecule", "target": "O2_simple_molecule", "sign": true }, { "id": "t102", - "source": "superoxide_simple_molecule", + "source": "Fe3+_ion", "target": "O2_simple_molecule", "sign": true }, @@ -1522,13 +1522,13 @@ }, { "id": "t104", - "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "source": "H+_ion_mitochondrial matrix", "target": "H+_ion_mitochondrion", "sign": true }, { "id": "t105", - "source": "H+_ion_mitochondrial matrix", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", "target": "H+_ion_mitochondrion", "sign": true }, @@ -1540,13 +1540,13 @@ }, { "id": "t107", - "source": "Complex_space_1_complex", + "source": "CYCS_mitochondrial matrix", "target": "H+_ion_mitochondrion", "sign": true }, { "id": "t108", - "source": "CYCS_mitochondrial matrix", + "source": "Complex_space_1_complex", "target": "H+_ion_mitochondrion", "sign": true }, @@ -1582,31 +1582,31 @@ }, { "id": "t114", - "source": "mt_space_DNA_gene", + "source": "mt_space_DNA_space_damage_phenotype", "target": "damaged_space_mt_space_DNA_gene", "sign": true }, { "id": "t115", - "source": "mt_space_DNA_space_damage_phenotype", + "source": "mt_space_DNA_gene", "target": "damaged_space_mt_space_DNA_gene", "sign": true }, { "id": "t116", - "source": "H2O2_simple_molecule", + "source": "Fe2+_ion", "target": "hydroxide_simple_molecule", "sign": true }, { "id": "t117", - "source": "Fe2+_ion", + "source": "H2O2_simple_molecule", "target": "hydroxide_simple_molecule", "sign": true }, { "id": "t118", - "source": "ATP_space_Synthase_complex", + "source": "H+_ion_mitochondrial matrix", "target": "ATP_simple_molecule", "sign": true }, @@ -1624,25 +1624,25 @@ }, { "id": "t121", - "source": "H+_ion_mitochondrial matrix", + "source": "ATP_space_Synthase_complex", "target": "ATP_simple_molecule", "sign": true }, { "id": "t122", - "source": "complex_space_2_complex_mitochondrial matrix", + "source": "Complex_space_1_complex", "target": "ubiquinol_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t123", - "source": "Q_simple_molecule_mitochondrial matrix", + "source": "complex_space_2_complex_mitochondrial matrix", "target": "ubiquinol_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t124", - "source": "Complex_space_1_complex", + "source": "Q_simple_molecule_mitochondrial matrix", "target": "ubiquinol_simple_molecule_mitochondrial matrix", "sign": true }, @@ -1666,13 +1666,13 @@ }, { "id": "t128", - "source": "NADPH_simple_molecule", + "source": "glutathione_space_disulfide_simple_molecule", "target": "glutathione_simple_molecule", "sign": true }, { "id": "t129", - "source": "glutathione_space_disulfide_simple_molecule", + "source": "NADPH_simple_molecule", "target": "glutathione_simple_molecule", "sign": true }, @@ -1690,49 +1690,49 @@ }, { "id": "t132", - "source": "GPX1", + "source": "H2O2_simple_molecule", "target": "glutathione_space_disulfide_simple_molecule", "sign": true }, { "id": "t133", - "source": "H2O2_simple_molecule", + "source": "glutathione_simple_molecule", "target": "glutathione_space_disulfide_simple_molecule", "sign": true }, { "id": "t134", - "source": "glutathione_simple_molecule", + "source": "GPX4", "target": "glutathione_space_disulfide_simple_molecule", "sign": true }, { "id": "t135", - "source": "GPX4", + "source": "GPX1", "target": "glutathione_space_disulfide_simple_molecule", "sign": true }, { "id": "t136", - "source": "TIM_space_complex:Nsp4_complex", + "source": "TOM_space_complex_complex_mitochondrion", "target": "precursor_space_protein_space_N-terminus_space_binding", "sign": true }, { "id": "t137", - "source": "TIM_space_complex_complex", + "source": "TIM23_space_complex_complex", "target": "precursor_space_protein_space_N-terminus_space_binding", "sign": true }, { "id": "t138", - "source": "TOM_space_complex_complex_mitochondrion", + "source": "TIM_space_complex:Nsp4_complex", "target": "precursor_space_protein_space_N-terminus_space_binding", "sign": true }, { "id": "t139", - "source": "TIM23_space_complex_complex", + "source": "TIM_space_complex_complex", "target": "precursor_space_protein_space_N-terminus_space_binding", "sign": true }, @@ -1756,13 +1756,13 @@ }, { "id": "t143", - "source": "Complex_space_1_complex", + "source": "NADH_simple_molecule", "target": "NAD+_simple_molecule", "sign": true }, { "id": "t144", - "source": "NADH_simple_molecule", + "source": "Complex_space_1_complex", "target": "NAD+_simple_molecule", "sign": true }, @@ -1774,13 +1774,13 @@ }, { "id": "t146", - "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "source": "H+_ion_mitochondrial matrix", "target": "O2-_simple_molecule", "sign": true }, { "id": "t147", - "source": "H+_ion_mitochondrial matrix", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", "target": "O2-_simple_molecule", "sign": true }, @@ -1816,25 +1816,25 @@ }, { "id": "t153", - "source": "O2_simple_molecule", + "source": "complex_space_3_complex", "target": "CYCS_mitochondrial matrix", "sign": true }, { "id": "t154", - "source": "ubiquinol_simple_molecule_mitochondrial matrix", + "source": "H+_ion_mitochondrial matrix", "target": "CYCS_mitochondrial matrix", "sign": true }, { "id": "t155", - "source": "complex_space_3_complex", + "source": "O2_simple_molecule", "target": "CYCS_mitochondrial matrix", "sign": true }, { "id": "t156", - "source": "H+_ion_mitochondrial matrix", + "source": "ubiquinol_simple_molecule_mitochondrial matrix", "target": "CYCS_mitochondrial matrix", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json index 0cf6529d1..bea08f12a 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/E_protein.json @@ -335,43 +335,43 @@ }, { "id": "t3", - "source": "H2BC21", + "source": "H4-16", "target": "histone_complex_nucleus", "sign": true }, { "id": "t4", - "source": "H4C14", + "source": "H2BC21", "target": "histone_complex_nucleus", "sign": true }, { "id": "t5", - "source": "H4C9", + "source": "H4C1", "target": "histone_complex_nucleus", "sign": true }, { "id": "t6", - "source": "H3C15", + "source": "H4C14", "target": "histone_complex_nucleus", "sign": true }, { "id": "t7", - "source": "H4-16", + "source": "H4C9", "target": "histone_complex_nucleus", "sign": true }, { "id": "t8", - "source": "H4C1", + "source": "H3C1", "target": "histone_complex_nucleus", "sign": true }, { "id": "t9", - "source": "H3C1", + "source": "H3C15", "target": "histone_complex_nucleus", "sign": true }, @@ -383,37 +383,37 @@ }, { "id": "t11", - "source": "CRB3", + "source": "PATJ", "target": "CRB3:PALS1:PATJ complex_complex", "sign": true }, { "id": "t12", - "source": "MPP5", + "source": "CRB3", "target": "CRB3:PALS1:PATJ complex_complex", "sign": true }, { "id": "t13", - "source": "PATJ", + "source": "MPP5", "target": "CRB3:PALS1:PATJ complex_complex", "sign": true }, { "id": "t14", - "source": "E_cell", + "source": "ASIC1", "target": "ASIC1 trimer:H+:STOML3_complex", "sign": true }, { "id": "t15", - "source": "ASIC1", + "source": "STOML3", "target": "ASIC1 trimer:H+:STOML3_complex", "sign": true }, { "id": "t16", - "source": "STOML3", + "source": "E_cell", "target": "ASIC1 trimer:H+:STOML3_complex", "sign": true }, @@ -473,13 +473,13 @@ }, { "id": "t26", - "source": "JQ-1_simple_molecule", + "source": "E_nucleus", "target": "BRD2", "sign": true }, { "id": "t27", - "source": "E_nucleus", + "source": "JQ-1_simple_molecule", "target": "BRD2", "sign": true }, @@ -503,19 +503,19 @@ }, { "id": "t31", - "source": "ATP1A:ATP1B:FXYDs_complex", + "source": "ASIC1 trimer:H+:STOML3_complex", "target": "Activity of sodium channels_phenotype", "sign": true }, { "id": "t32", - "source": "ASIC1 trimer:H+:STOML3_complex", + "source": "STOML3", "target": "Activity of sodium channels_phenotype", "sign": true }, { "id": "t33", - "source": "STOML3", + "source": "ATP1A:ATP1B:FXYDs_complex", "target": "Activity of sodium channels_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json index 3f4f7cb4c..5689054f9 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/HMOX1_Pathway.json @@ -1703,13 +1703,13 @@ "edges": [ { "id": "t1", - "source": "MAF", + "source": "NRF2_phosphorylated_nucleus", "target": "Nrf2/Maf_complex", "sign": true }, { "id": "t2", - "source": "NRF2_phosphorylated_nucleus", + "source": "MAF", "target": "Nrf2/Maf_complex", "sign": true }, @@ -1775,13 +1775,13 @@ }, { "id": "t13", - "source": "Neddylated CUL3:RBX1_complex", + "source": "CAND1", "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, { "id": "t14", - "source": "CAND1", + "source": "Neddylated CUL3:RBX1_complex", "target": "Ubiquitin Ligase Complex_complex_cell", "sign": true }, @@ -1835,25 +1835,25 @@ }, { "id": "t23", - "source": "TXNIP", + "source": "NLRP3_cell", "target": "TXNIP:NLRP3_complex", "sign": true }, { "id": "t24", - "source": "NLRP3_cell", + "source": "TXNIP", "target": "TXNIP:NLRP3_complex", "sign": true }, { "id": "t25", - "source": "SUGT1:HSP90AB1_complex", + "source": "NLRP3_cell", "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { "id": "t26", - "source": "NLRP3_cell", + "source": "SUGT1:HSP90AB1_complex", "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, @@ -1871,13 +1871,13 @@ }, { "id": "t29", - "source": "TXN_cell", + "source": "TXNIP", "target": "Thioredoxin:TXNIP_complex", "sign": true }, { "id": "t30", - "source": "TXNIP", + "source": "TXN_cell", "target": "Thioredoxin:TXNIP_complex", "sign": true }, @@ -1895,7 +1895,7 @@ }, { "id": "t33", - "source": "CTSG", + "source": "ASC", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, @@ -1907,13 +1907,13 @@ }, { "id": "t35", - "source": "ASC", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t36", - "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "CTSG", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, @@ -1991,79 +1991,79 @@ }, { "id": "t49", - "source": "Heme_simple_molecule_cell", + "source": "NADPH_simple_molecule", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t50", - "source": "HMOX1_cell_active", + "source": "O2_simple_molecule_cell", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t51", - "source": "O2_simple_molecule_cell", + "source": "Heme_simple_molecule_cell", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t52", - "source": "NADPH_simple_molecule", + "source": "HMOX1_cell_active", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t53", - "source": "Fe2+_ion_mitochondrial matrix", + "source": "FECH", "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t54", - "source": "FECH", + "source": "Fe2+_ion_mitochondrial matrix", "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t55", - "source": "PRIN9_simple_molecule_mitochondrial matrix", + "source": "Pb2+_ion", "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t56", - "source": "Pb2+_ion", + "source": "PRIN9_simple_molecule_mitochondrial matrix", "target": "Heme_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t57", - "source": "Heme_simple_molecule_cell", + "source": "dALA_simple_molecule_cell", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t58", - "source": "O2_simple_molecule_cell", + "source": "Heme_simple_molecule_cell", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t59", - "source": "NADPH_simple_molecule", + "source": "O2_simple_molecule_cell", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t60", - "source": "HMOX1_cell_active", + "source": "NADPH_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t61", - "source": "dALA_simple_molecule_cell", + "source": "HMOX1_cell_active", "target": "H2O_simple_molecule_cell", "sign": true }, @@ -2075,91 +2075,91 @@ }, { "id": "t63", - "source": "Heme_simple_molecule_cell", + "source": "Biliverdin_simple_molecule", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t64", - "source": "BLVRB", + "source": "BLVRA:Zn2+_complex", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t65", - "source": "O2_simple_molecule_cell", + "source": "Heme_simple_molecule_cell", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t66", - "source": "NADPH_simple_molecule", + "source": "O2_simple_molecule_cell", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t67", - "source": "HMOX1_cell_active", + "source": "NADPH_simple_molecule", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t68", - "source": "BLVRA:Zn2+_complex", + "source": "BLVRB", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t69", - "source": "Biliverdin_simple_molecule", + "source": "HMOX1_cell_active", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t70", - "source": "Heme_simple_molecule_cell", + "source": "SLC11A2", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t71", - "source": "O2_simple_molecule_cell", + "source": "Heme_simple_molecule_cell", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t72", - "source": "NADPH_simple_molecule", + "source": "Fe2+_ion_default_compartment", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t73", - "source": "HMOX1_cell_active", + "source": "O2_simple_molecule_cell", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t74", - "source": "MCOLN1", + "source": "Fe2+_ion_endosome", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t75", - "source": "SLC11A2", + "source": "NADPH_simple_molecule", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t76", - "source": "Fe2+_ion_default_compartment", + "source": "MCOLN1", "target": "Fe2+_ion_cell", "sign": true }, { "id": "t77", - "source": "Fe2+_ion_endosome", + "source": "HMOX1_cell_active", "target": "Fe2+_ion_cell", "sign": true }, @@ -2171,49 +2171,49 @@ }, { "id": "t79", - "source": "Heme_simple_molecule_cell", + "source": "NADPH_simple_molecule", "target": "CO_simple_molecule", "sign": true }, { "id": "t80", - "source": "HMOX1_cell_active", + "source": "O2_simple_molecule_cell", "target": "CO_simple_molecule", "sign": true }, { "id": "t81", - "source": "O2_simple_molecule_cell", + "source": "Heme_simple_molecule_cell", "target": "CO_simple_molecule", "sign": true }, { "id": "t82", - "source": "NADPH_simple_molecule", + "source": "HMOX1_cell_active", "target": "CO_simple_molecule", "sign": true }, { "id": "t83", - "source": "NADPH_simple_molecule", + "source": "Biliverdin_simple_molecule", "target": "Bilirubin_simple_molecule_cell", "sign": true }, { "id": "t84", - "source": "Biliverdin_simple_molecule", + "source": "NADPH_simple_molecule", "target": "Bilirubin_simple_molecule_cell", "sign": true }, { "id": "t85", - "source": "BLVRA:Zn2+_complex", + "source": "BLVRB", "target": "Bilirubin_simple_molecule_cell", "sign": true }, { "id": "t86", - "source": "BLVRB", + "source": "BLVRA:Zn2+_complex", "target": "Bilirubin_simple_molecule_cell", "sign": true }, @@ -2279,55 +2279,55 @@ }, { "id": "t97", - "source": "Fe2+_ion_mitochondrial matrix", + "source": "FECH", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t98", - "source": "FECH", + "source": "Fe2+_ion_mitochondrial matrix", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t99", - "source": "PRIN9_simple_molecule_mitochondrial matrix", + "source": "Pb2+_ion", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t100", - "source": "Pb2+_ion", + "source": "PRIN9_simple_molecule_mitochondrial matrix", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t101", - "source": "H+_ion_mitochondrial matrix", + "source": "Panhematin_drug", "target": "dALA_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t102", - "source": "Panhematin_drug", + "source": "Heme_simple_molecule_mitochondrial matrix", "target": "dALA_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t103", - "source": "Gly_simple_molecule", + "source": "H+_ion_mitochondrial matrix", "target": "dALA_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t104", - "source": "ALAS1:ALAS2_complex", + "source": "Gly_simple_molecule", "target": "dALA_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t105", - "source": "Heme_simple_molecule_mitochondrial matrix", + "source": "ALAS1:ALAS2_complex", "target": "dALA_simple_molecule_mitochondrial matrix", "sign": true }, @@ -2339,31 +2339,31 @@ }, { "id": "t107", - "source": "H+_ion_mitochondrial matrix", + "source": "Panhematin_drug", "target": "CO2_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t108", - "source": "Panhematin_drug", + "source": "Heme_simple_molecule_mitochondrial matrix", "target": "CO2_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t109", - "source": "Gly_simple_molecule", + "source": "H+_ion_mitochondrial matrix", "target": "CO2_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t110", - "source": "ALAS1:ALAS2_complex", + "source": "Gly_simple_molecule", "target": "CO2_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t111", - "source": "Heme_simple_molecule_mitochondrial matrix", + "source": "ALAS1:ALAS2_complex", "target": "CO2_simple_molecule_mitochondrial matrix", "sign": true }, @@ -2375,31 +2375,31 @@ }, { "id": "t113", - "source": "H+_ion_mitochondrial matrix", + "source": "Panhematin_drug", "target": "CoA-SH_simple_molecule", "sign": true }, { "id": "t114", - "source": "Panhematin_drug", + "source": "Heme_simple_molecule_mitochondrial matrix", "target": "CoA-SH_simple_molecule", "sign": true }, { "id": "t115", - "source": "Gly_simple_molecule", + "source": "H+_ion_mitochondrial matrix", "target": "CoA-SH_simple_molecule", "sign": true }, { "id": "t116", - "source": "ALAS1:ALAS2_complex", + "source": "Gly_simple_molecule", "target": "CoA-SH_simple_molecule", "sign": true }, { "id": "t117", - "source": "Heme_simple_molecule_mitochondrial matrix", + "source": "ALAS1:ALAS2_complex", "target": "CoA-SH_simple_molecule", "sign": true }, @@ -2417,31 +2417,31 @@ }, { "id": "t120", - "source": "dALA_simple_molecule_cell", + "source": "ALAD:Zn2+_complex", "target": "PBG_simple_molecule", "sign": true }, { "id": "t121", - "source": "ALAD:Zn2+_complex", + "source": "dALA_simple_molecule_cell", "target": "PBG_simple_molecule", "sign": true }, { "id": "t122", - "source": "dALA_simple_molecule_cell", + "source": "ALAD:Zn2+_complex", "target": "H+_ion_cell", "sign": true }, { "id": "t123", - "source": "ALAD:Zn2+_complex", + "source": "dALA_simple_molecule_cell", "target": "H+_ion_cell", "sign": true }, { "id": "t124", - "source": "PBG_simple_molecule", + "source": "HMBS:DIPY_complex", "target": "HMBL_simple_molecule", "sign": true }, @@ -2453,13 +2453,13 @@ }, { "id": "t126", - "source": "HMBS:DIPY_complex", + "source": "PBG_simple_molecule", "target": "HMBL_simple_molecule", "sign": true }, { "id": "t127", - "source": "PBG_simple_molecule", + "source": "HMBS:DIPY_complex", "target": "NH4+_ion", "sign": true }, @@ -2471,19 +2471,19 @@ }, { "id": "t129", - "source": "HMBS:DIPY_complex", + "source": "PBG_simple_molecule", "target": "NH4+_ion", "sign": true }, { "id": "t130", - "source": "UROS", + "source": "HMBL_simple_molecule", "target": "URO3_simple_molecule", "sign": true }, { "id": "t131", - "source": "HMBL_simple_molecule", + "source": "UROS", "target": "URO3_simple_molecule", "sign": true }, @@ -2507,73 +2507,73 @@ }, { "id": "t135", - "source": "O2_simple_molecule_mitochondrion", + "source": "CPOX", "target": "PPGEN9_simple_molecule", "sign": true }, { "id": "t136", - "source": "CPOX", + "source": "COPRO3_simple_molecule_mitochondrion", "target": "PPGEN9_simple_molecule", "sign": true }, { "id": "t137", - "source": "COPRO3_simple_molecule_mitochondrion", + "source": "O2_simple_molecule_mitochondrion", "target": "PPGEN9_simple_molecule", "sign": true }, { "id": "t138", - "source": "PPGEN9_simple_molecule", + "source": "PPO:FAD_complex", "target": "PRIN9_simple_molecule_mitochondrion", "sign": true }, { "id": "t139", - "source": "O2_simple_molecule_mitochondrion", + "source": "PPGEN9_simple_molecule", "target": "PRIN9_simple_molecule_mitochondrion", "sign": true }, { "id": "t140", - "source": "PPO:FAD_complex", + "source": "O2_simple_molecule_mitochondrion", "target": "PRIN9_simple_molecule_mitochondrion", "sign": true }, { "id": "t141", - "source": "O2_simple_molecule_mitochondrion", + "source": "CPOX", "target": "CO2_simple_molecule_mitochondrion", "sign": true }, { "id": "t142", - "source": "CPOX", + "source": "COPRO3_simple_molecule_mitochondrion", "target": "CO2_simple_molecule_mitochondrion", "sign": true }, { "id": "t143", - "source": "COPRO3_simple_molecule_mitochondrion", + "source": "O2_simple_molecule_mitochondrion", "target": "CO2_simple_molecule_mitochondrion", "sign": true }, { "id": "t144", - "source": "PPGEN9_simple_molecule", + "source": "CPOX", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t145", - "source": "O2_simple_molecule_mitochondrion", + "source": "PPO:FAD_complex", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t146", - "source": "PPO:FAD_complex", + "source": "PPGEN9_simple_molecule", "target": "H2O2_simple_molecule", "sign": true }, @@ -2585,7 +2585,7 @@ }, { "id": "t148", - "source": "CPOX", + "source": "O2_simple_molecule_mitochondrion", "target": "H2O2_simple_molecule", "sign": true }, @@ -2615,61 +2615,61 @@ }, { "id": "t153", - "source": "Fe3+_ion_default_compartment", + "source": "Fe2+_ion_cell", "target": "Fe2+_ion_default_compartment", "sign": true }, { "id": "t154", - "source": "SLC40A1:HEPH:Cu2+_complex", + "source": "SLC40A1:CP:Cu2+_complex", "target": "Fe2+_ion_default_compartment", "sign": true }, { "id": "t155", - "source": "CYBRD1:Heme_complex", + "source": "SLC40A1:HEPH:Cu2+_complex", "target": "Fe2+_ion_default_compartment", "sign": true }, { "id": "t156", - "source": "Fe2+_ion_cell", + "source": "CYBRD1:Heme_complex", "target": "Fe2+_ion_default_compartment", "sign": true }, { "id": "t157", - "source": "SLC40A1:CP:Cu2+_complex", + "source": "Fe3+_ion_default_compartment", "target": "Fe2+_ion_default_compartment", "sign": true }, { "id": "t158", - "source": "H+_ion_default_compartment", + "source": "O2_simple_molecule_default_compartment", "target": "Fe3+_ion_default_compartment", "sign": true }, { "id": "t159", - "source": "SLC40A1:HEPH:Cu2+_complex", + "source": "Fe2+_ion_default_compartment", "target": "Fe3+_ion_default_compartment", "sign": true }, { "id": "t160", - "source": "Fe2+_ion_default_compartment", + "source": "SLC40A1:CP:Cu2+_complex", "target": "Fe3+_ion_default_compartment", "sign": true }, { "id": "t161", - "source": "O2_simple_molecule_default_compartment", + "source": "SLC40A1:HEPH:Cu2+_complex", "target": "Fe3+_ion_default_compartment", "sign": true }, { "id": "t162", - "source": "SLC40A1:CP:Cu2+_complex", + "source": "H+_ion_default_compartment", "target": "Fe3+_ion_default_compartment", "sign": true }, @@ -2735,31 +2735,31 @@ }, { "id": "t173", - "source": "H+_ion_default_compartment", + "source": "O2_simple_molecule_default_compartment", "target": "H2O_simple_molecule_default_compartment", "sign": true }, { "id": "t174", - "source": "SLC40A1:HEPH:Cu2+_complex", + "source": "Fe2+_ion_default_compartment", "target": "H2O_simple_molecule_default_compartment", "sign": true }, { "id": "t175", - "source": "Fe2+_ion_default_compartment", + "source": "SLC40A1:CP:Cu2+_complex", "target": "H2O_simple_molecule_default_compartment", "sign": true }, { "id": "t176", - "source": "O2_simple_molecule_default_compartment", + "source": "SLC40A1:HEPH:Cu2+_complex", "target": "H2O_simple_molecule_default_compartment", "sign": true }, { "id": "t177", - "source": "SLC40A1:CP:Cu2+_complex", + "source": "H+_ion_default_compartment", "target": "H2O_simple_molecule_default_compartment", "sign": true }, @@ -2807,55 +2807,55 @@ }, { "id": "t185", - "source": "PKC", + "source": "CK2", "target": "NRF2_phosphorylated_cell", "sign": true }, { "id": "t186", - "source": "CK2", + "source": "PKC", "target": "NRF2_phosphorylated_cell", "sign": true }, { "id": "t187", - "source": "Heme_simple_molecule_cell", + "source": "ATP_simple_molecule", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { "id": "t188", - "source": "ATP_simple_molecule", + "source": "Heme_simple_molecule_cell", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { "id": "t189", - "source": "ABCG2", + "source": "H2O_simple_molecule_cell", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { "id": "t190", - "source": "H2O_simple_molecule_cell", + "source": "FLVCR1-1", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { "id": "t191", - "source": "FLVCR1-1", + "source": "ABCG2", "target": "Heme_simple_molecule_default_compartment", "sign": true }, { "id": "t192", - "source": "Heme_simple_molecule_cell", + "source": "ABCG2", "target": "ADP_simple_molecule", "sign": true }, { "id": "t193", - "source": "ABCG2", + "source": "ATP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, @@ -2867,19 +2867,19 @@ }, { "id": "t195", - "source": "ATP_simple_molecule", + "source": "Heme_simple_molecule_cell", "target": "ADP_simple_molecule", "sign": true }, { "id": "t196", - "source": "Heme_simple_molecule_cell", + "source": "ABCG2", "target": "Pi_simple_molecule", "sign": true }, { "id": "t197", - "source": "ABCG2", + "source": "ATP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, @@ -2891,7 +2891,7 @@ }, { "id": "t199", - "source": "ATP_simple_molecule", + "source": "Heme_simple_molecule_cell", "target": "Pi_simple_molecule", "sign": true }, @@ -2915,19 +2915,19 @@ }, { "id": "t203", - "source": "Fe3+_ion_endosome", + "source": "e-_ion_endosome", "target": "Fe2+_ion_endosome", "sign": true }, { "id": "t204", - "source": "e-_ion_endosome", + "source": "STEAP3", "target": "Fe2+_ion_endosome", "sign": true }, { "id": "t205", - "source": "STEAP3", + "source": "Fe3+_ion_endosome", "target": "Fe2+_ion_endosome", "sign": true }, @@ -2939,13 +2939,13 @@ }, { "id": "t207", - "source": "NLRP3:SUGT1:HSP90_complex", + "source": "NLRP3_rna", "target": "NLRP3_cell", "sign": true }, { "id": "t208", - "source": "NLRP3_rna", + "source": "NLRP3:SUGT1:HSP90_complex", "target": "NLRP3_cell", "sign": true }, @@ -2981,49 +2981,49 @@ }, { "id": "t214", - "source": "CTSG", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", "target": "CASP1_cell", "sign": true }, { "id": "t215", - "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "CTSG", "target": "CASP1_cell", "sign": true }, { "id": "t216", - "source": "CTSG", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", "target": "CASP1_cell", "sign": true }, { "id": "t217", - "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "CTSG", "target": "CASP1_cell", "sign": true }, { "id": "t218", - "source": "CTSG", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", "target": "CASP1_cell", "sign": true }, { "id": "t219", - "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "CTSG", "target": "CASP1_cell", "sign": true }, { "id": "t220", - "source": "CTSG", + "source": "NLRP3 oligomer:ASC:Caspase1_complex", "target": "CASP1_cell", "sign": true }, { "id": "t221", - "source": "NLRP3 oligomer:ASC:Caspase1_complex", + "source": "CTSG", "target": "CASP1_cell", "sign": true }, @@ -3041,13 +3041,13 @@ }, { "id": "t224", - "source": "proIL-1B_cell", + "source": "Caspase-1 Tetramer_complex", "target": "IL-1B_cell", "sign": true }, { "id": "t225", - "source": "Caspase-1 Tetramer_complex", + "source": "proIL-1B_cell", "target": "IL-1B_cell", "sign": true }, @@ -3083,49 +3083,49 @@ }, { "id": "t231", - "source": "SARS Orf3a", + "source": "DAMPs_phenotype", "target": "NLRP3_cell_active", "sign": true }, { "id": "t232", - "source": "NLRP3_cell", + "source": "PAMPs_phenotype", "target": "NLRP3_cell_active", "sign": true }, { "id": "t233", - "source": "SARS E", + "source": "Reactive Oxygen Species_simple_molecule", "target": "NLRP3_cell_active", "sign": true }, { "id": "t234", - "source": "PAMPs_phenotype", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", "target": "NLRP3_cell_active", "sign": true }, { "id": "t235", - "source": "Reactive Oxygen Species_simple_molecule", + "source": "SARS E", "target": "NLRP3_cell_active", "sign": true }, { "id": "t236", - "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "source": "NLRP3_cell", "target": "NLRP3_cell_active", "sign": true }, { "id": "t237", - "source": "DAMPs_phenotype", + "source": "TXNIP:NLRP3_complex", "target": "NLRP3_cell_active", "sign": true }, { "id": "t238", - "source": "TXNIP:NLRP3_complex", + "source": "SARS Orf3a", "target": "NLRP3_cell_active", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json index f0e732dc7..41a0b06c5 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/IFN-lambda.json @@ -484,13 +484,13 @@ }, { "id": "t12", - "source": "RIG-I-mitoMAVS_complex", + "source": "IKK-TBK1_complex", "target": "RIG-I-MAVS_complex_mitochondrion", "sign": true }, { "id": "t13", - "source": "IKK-TBK1_complex", + "source": "RIG-I-mitoMAVS_complex", "target": "RIG-I-MAVS_complex_mitochondrion", "sign": true }, @@ -538,31 +538,31 @@ }, { "id": "t21", - "source": "M", + "source": "RIG-I", "target": "RIG-1 M-Protein_complex", "sign": true }, { "id": "t22", - "source": "RIG-I", + "source": "M", "target": "RIG-1 M-Protein_complex", "sign": true }, { "id": "t23", - "source": "dsRNA_rna", + "source": "RIG-I", "target": "RIG-I:dsRNA_complex_mitochondrion", "sign": true }, { "id": "t24", - "source": "RIG-I", + "source": "PLPro", "target": "RIG-I:dsRNA_complex_mitochondrion", "sign": true }, { "id": "t25", - "source": "PLPro", + "source": "dsRNA_rna", "target": "RIG-I:dsRNA_complex_mitochondrion", "sign": true }, @@ -664,13 +664,13 @@ }, { "id": "t42", - "source": "dsRNA_vesicle_rna", + "source": "RNA_rna", "target": "dsRNA_rna", "sign": true }, { "id": "t43", - "source": "RNA_rna", + "source": "dsRNA_vesicle_rna", "target": "dsRNA_rna", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json index 1d592bcd2..337e373b3 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Interferon1.json @@ -1295,85 +1295,85 @@ }, { "id": "t9", - "source": "JAK1_TYK2_complex", + "source": "IRF9", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t10", - "source": "TREML4", + "source": "STAT2_phosphorylated", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t11", - "source": "STAT1_phosphorylated", + "source": "Orf6", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t12", - "source": "IRF9", + "source": "Nsp5", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t13", - "source": "STAT2_phosphorylated", + "source": "JAK1_TYK2_complex", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t14", - "source": "Nsp5", + "source": "TREML4", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t15", - "source": "Orf6", + "source": "STAT1_phosphorylated", "target": "STAT1/2_IRF9_complex", "sign": true }, { "id": "t16", - "source": "Orf6", + "source": "STAT1/2_IRF9_complex", "target": "ISRE_complex", "sign": true }, { "id": "t17", - "source": "STAT1/2_IRF9_complex", + "source": "Orf6", "target": "ISRE_complex", "sign": true }, { "id": "t18", - "source": "TYK2", + "source": "JAK1", "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t19", - "source": "IFNB1_IFNAR_complex", + "source": "TYK2", "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t20", - "source": "IFNA1_IFNAR_complex", + "source": "IFNB1_IFNAR_complex", "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t21", - "source": "JAK1", + "source": "IFNA1_IFNAR_complex", "target": "JAK1_TYK2_complex", "sign": true }, { "id": "t22", - "source": "JUN", + "source": "MAPK8/14_complex", "target": "AP-1_complex_cell", "sign": true }, @@ -1385,13 +1385,13 @@ }, { "id": "t24", - "source": "E", + "source": "JUN", "target": "AP-1_complex_cell", "sign": true }, { "id": "t25", - "source": "MAPK8/14_complex", + "source": "E", "target": "AP-1_complex_cell", "sign": true }, @@ -1409,19 +1409,19 @@ }, { "id": "t28", - "source": "OAS2_cell_active", + "source": "EIF2AK", "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t29", - "source": "EIF2AK", + "source": "OAS3_cell_active", "target": "OAS1_EIF2AK_complex", "sign": true }, { "id": "t30", - "source": "OAS3_cell_active", + "source": "OAS2_cell_active", "target": "OAS1_EIF2AK_complex", "sign": true }, @@ -1433,13 +1433,13 @@ }, { "id": "t32", - "source": "Nsp3", + "source": "TRAF3", "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t33", - "source": "TRAF3", + "source": "NAP1", "target": "TBK1_IKBKE_complex", "sign": true }, @@ -1451,19 +1451,19 @@ }, { "id": "t35", - "source": "NAP1", + "source": "TBK1", "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t36", - "source": "TBK1", + "source": "Nsp3", "target": "TBK1_IKBKE_complex", "sign": true }, { "id": "t37", - "source": "TREML4", + "source": "TLR7", "target": "MYD88_TRAM_complex", "sign": true }, @@ -1475,7 +1475,7 @@ }, { "id": "t39", - "source": "TLR7", + "source": "Viral dsRNA_rna_endosome", "target": "MYD88_TRAM_complex", "sign": true }, @@ -1493,43 +1493,43 @@ }, { "id": "t42", - "source": "Viral dsRNA_rna_endosome", + "source": "TREML4", "target": "MYD88_TRAM_complex", "sign": true }, { "id": "t43", - "source": "TANK", + "source": "TRAF3_TBK1_IKBKE_complex_cell_active", "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t44", - "source": "MAVS", + "source": "M", "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t45", - "source": "M", + "source": "MAVS", "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t46", - "source": "TLR3_TRIF_complex", + "source": "TANK", "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t47", - "source": "TRAF3_TBK1_IKBKE_complex_cell_active", + "source": "TLR3_TRIF_complex", "target": "TRAF3_TANK_TBK1_IKKepsilon_complex", "sign": true }, { "id": "t48", - "source": "TRAF3", + "source": "TBK1_IKBKE_complex", "target": "TRAF3_TBK1_IKBKE_complex_cell", "sign": true }, @@ -1541,109 +1541,109 @@ }, { "id": "t50", - "source": "TBK1_IKBKE_complex", + "source": "TRAF3", "target": "TRAF3_TBK1_IKBKE_complex_cell", "sign": true }, { "id": "t51", - "source": "TRAF3_TBK1_IKBKE_complex_cell", + "source": "pp1ab", "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t52", - "source": "pp1ab", + "source": "STING1_ubiquitinated", "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t53", - "source": "STING1_ubiquitinated", + "source": "TRAF3_TBK1_IKBKE_complex_cell", "target": "TRAF3_TBK1_IKBKE_complex_cell_active", "sign": true }, { "id": "t54", - "source": "Nsp10", + "source": "Nsp16", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t55", - "source": "Nsp15", + "source": "M", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t56", - "source": "N", + "source": "Nsp14", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t57", - "source": "Nsp14", + "source": "DDX58_ubiquitinated", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t58", - "source": "Nsp16", + "source": "IFIH1", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t59", - "source": "IFIH1", + "source": "Nsp10", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t60", - "source": "M", + "source": "Viral dsRNA_rna_cell", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t61", - "source": "DDX58_ubiquitinated", + "source": "Nsp15", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t62", - "source": "Viral dsRNA_rna_cell", + "source": "N", "target": "RIG1_MDA5_complex", "sign": true }, { "id": "t63", - "source": "E", + "source": "MNS_drug", "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t64", - "source": "MNS_drug", + "source": "p50_p65_complex_nucleus", "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t65", - "source": "p50_p65_complex_nucleus", + "source": "E", "target": "NLRP3_inflammasome_complex", "sign": true }, { "id": "t66", - "source": "MAPK8", + "source": "MAPK14", "target": "MAPK8/14_complex", "sign": true }, { "id": "t67", - "source": "MAPK14", + "source": "MAP3K7", "target": "MAPK8/14_complex", "sign": true }, @@ -1655,7 +1655,7 @@ }, { "id": "t69", - "source": "MAP3K7", + "source": "MAPK8", "target": "MAPK8/14_complex", "sign": true }, @@ -1673,13 +1673,13 @@ }, { "id": "t72", - "source": "TRIF", + "source": "Viral dsRNA_rna_endosome", "target": "TLR3_TRIF_complex", "sign": true }, { "id": "t73", - "source": "Viral dsRNA_rna_endosome", + "source": "TRIF", "target": "TLR3_TRIF_complex", "sign": true }, @@ -1691,13 +1691,13 @@ }, { "id": "t75", - "source": "TLR3_TRIF_complex", + "source": "RIP1", "target": "TLR3_TRIF_RIPK1_complex", "sign": true }, { "id": "t76", - "source": "RIP1", + "source": "TLR3_TRIF_complex", "target": "TLR3_TRIF_RIPK1_complex", "sign": true }, @@ -1721,13 +1721,13 @@ }, { "id": "t80", - "source": "TAB1", + "source": "TAK1", "target": "TAB1/2_TRAF6_TAK1_complex", "sign": true }, { "id": "t81", - "source": "TAK1", + "source": "TAB1", "target": "TAB1/2_TRAF6_TAK1_complex", "sign": true }, @@ -1805,13 +1805,13 @@ }, { "id": "t94", - "source": "ISG15", + "source": "GRL0617_drug", "target": "ISG15_Nsp3_complex", "sign": true }, { "id": "t95", - "source": "GRL0617_drug", + "source": "ISG15", "target": "ISG15_Nsp3_complex", "sign": true }, @@ -1847,7 +1847,7 @@ }, { "id": "t101", - "source": "Azithromycin_drug", + "source": "IRF7_homodimer_complex", "target": "IFNB1_rna", "sign": true }, @@ -1859,19 +1859,19 @@ }, { "id": "t103", - "source": "IRF7_homodimer_complex", + "source": "Azithromycin_drug", "target": "IFNB1_rna", "sign": true }, { "id": "t104", - "source": "IRF3_homodimer_complex_nucleus", + "source": "AP-1_complex_nucleus", "target": "IFNB1_rna", "sign": true }, { "id": "t105", - "source": "AP-1_complex_nucleus", + "source": "IRF3_homodimer_complex_nucleus", "target": "IFNB1_rna", "sign": true }, @@ -1931,103 +1931,103 @@ }, { "id": "t115", - "source": "Nsp15", + "source": "EIF2AK_rna", "target": "EIF2AK", "sign": true }, { "id": "t116", - "source": "EIF2AK_rna", + "source": "Nsp15", "target": "EIF2AK", "sign": true }, { "id": "t117", - "source": "Nsp3", + "source": "ITCH", "target": "TRAF6_ubiquitinated", "sign": true }, { "id": "t118", - "source": "ITCH", + "source": "MYD88_TRAM_complex", "target": "TRAF6_ubiquitinated", "sign": true }, { "id": "t119", - "source": "MYD88_TRAM_complex", + "source": "Nsp3", "target": "TRAF6_ubiquitinated", "sign": true }, { "id": "t120", - "source": "STING1_ubiquitinated", + "source": "Nsp13", "target": "TBK1", "sign": true }, { "id": "t121", - "source": "MAVS", + "source": "STING1_ubiquitinated", "target": "TBK1", "sign": true }, { "id": "t122", - "source": "IKBKE", + "source": "MAVS", "target": "TBK1", "sign": true }, { "id": "t123", - "source": "Nsp13", + "source": "IKBKE", "target": "TBK1", "sign": true }, { "id": "t124", - "source": "Nsp6", + "source": "M", "target": "Nsp1", "sign": false }, { "id": "t125", - "source": "Orf7b", + "source": "Orf3a", "target": "Nsp1", "sign": false }, { "id": "t126", - "source": "Nsp13", + "source": "Nsp6", "target": "Nsp1", "sign": false }, { "id": "t127", - "source": "M", + "source": "Nsp13", "target": "Nsp1", "sign": false }, { "id": "t128", - "source": "Orf3a", + "source": "Orf7b", "target": "Nsp1", "sign": false }, { "id": "t129", - "source": "Nsp6", + "source": "Nsp13", "target": "Orf7a", "sign": false }, { "id": "t130", - "source": "Orf7b", + "source": "Nsp6", "target": "Orf7a", "sign": false }, { "id": "t131", - "source": "Nsp13", + "source": "Orf7b", "target": "Orf7a", "sign": false }, @@ -2069,55 +2069,55 @@ }, { "id": "t138", - "source": "Nsp15", + "source": "OAS3_cell", "target": "OAS3_cell_active", "sign": true }, { "id": "t139", - "source": "OAS3_cell", + "source": "Nsp15", "target": "OAS3_cell_active", "sign": true }, { "id": "t140", - "source": "ISG15", + "source": "OAS1_EIF2AK_complex", "target": "ISG expression_antiviral response_phenotype", "sign": true }, { "id": "t141", - "source": "Azithromycin_drug", + "source": "ISG15", "target": "ISG expression_antiviral response_phenotype", "sign": true }, { "id": "t142", - "source": "Nsp3", + "source": "p50_p65_complex_nucleus", "target": "ISG expression_antiviral response_phenotype", "sign": true }, { "id": "t143", - "source": "p50_p65_complex_nucleus", + "source": "Azithromycin_drug", "target": "ISG expression_antiviral response_phenotype", "sign": true }, { "id": "t144", - "source": "OAS1_EIF2AK_complex", + "source": "Nsp3", "target": "ISG expression_antiviral response_phenotype", "sign": true }, { "id": "t145", - "source": "Nsp3", + "source": "MYD88_TRAM_complex", "target": "TRAF3", "sign": true }, { "id": "t146", - "source": "MYD88_TRAM_complex", + "source": "Nsp3", "target": "TRAF3", "sign": true }, @@ -2129,13 +2129,13 @@ }, { "id": "t148", - "source": "Nsp3", + "source": "TBK1", "target": "IKBKE", "sign": true }, { "id": "t149", - "source": "TBK1", + "source": "Nsp3", "target": "IKBKE", "sign": true }, @@ -2147,19 +2147,19 @@ }, { "id": "t151", - "source": "TRAF3_TANK_TBK1_IKKepsilon_complex", + "source": "MAVS", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t152", - "source": "Nsp15", + "source": "Orf8_complex", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t153", - "source": "N", + "source": "TRAF3_TANK_TBK1_IKKepsilon_complex", "target": "IRF3_phosphorylated", "sign": true }, @@ -2171,43 +2171,43 @@ }, { "id": "t155", - "source": "Orf8_complex", + "source": "Orf6", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t156", - "source": "pp1ab", + "source": "N", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t157", - "source": "Orf6", + "source": "Nsp15", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t158", - "source": "MAVS", + "source": "pp1ab", "target": "IRF3_phosphorylated", "sign": true }, { "id": "t159", - "source": "RIG1_MDA5_complex", + "source": "ITCH", "target": "MAVS", "sign": true }, { "id": "t160", - "source": "ITCH", + "source": "Orf9b", "target": "MAVS", "sign": true }, { "id": "t161", - "source": "Orf9b", + "source": "RIG1_MDA5_complex", "target": "MAVS", "sign": true }, @@ -2225,31 +2225,31 @@ }, { "id": "t164", - "source": "N", + "source": "Azithromycin_drug", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t165", - "source": "Azithromycin_drug", + "source": "RNF135", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t166", - "source": "TRIM25", + "source": "Nsp5", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t167", - "source": "Nsp5", + "source": "N", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t168", - "source": "RNF135", + "source": "TRIM25", "target": "DDX58_ubiquitinated", "sign": true }, @@ -2285,7 +2285,7 @@ }, { "id": "t174", - "source": "IFNB1_extracellular space", + "source": "IFNA1_extracellular space", "target": "Viral dsRNA_rna_cell", "sign": true }, @@ -2297,7 +2297,7 @@ }, { "id": "t176", - "source": "IFNA1_extracellular space", + "source": "IFNB1_extracellular space", "target": "Viral dsRNA_rna_cell", "sign": true }, @@ -2327,13 +2327,13 @@ }, { "id": "t181", - "source": "IFNB1_extracellular space", + "source": "IFNA1_extracellular space", "target": "type I IFN response_phenotype", "sign": true }, { "id": "t182", - "source": "IFNA1_extracellular space", + "source": "IFNB1_extracellular space", "target": "type I IFN response_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json index c10ea6587..a4e95e32d 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/JNK_pathway.json @@ -171,31 +171,31 @@ "edges": [ { "id": "t1", - "source": "7a", + "source": "MAP2K7_phosphorylated", "target": "JNK_complex_cell", "sign": true }, { "id": "t2", - "source": "MAP2K7_phosphorylated", + "source": "S", "target": "JNK_complex_cell", "sign": true }, { "id": "t3", - "source": "S", + "source": "7a", "target": "JNK_complex_cell", "sign": true }, { "id": "t4", - "source": "3a", + "source": "MAP2K4_phosphorylated", "target": "JNK_complex_cell", "sign": true }, { "id": "t5", - "source": "MAP2K4_phosphorylated", + "source": "3a", "target": "JNK_complex_cell", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json index 79e95b290..635343c4f 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Kynurenine_pathway.json @@ -1653,13 +1653,13 @@ }, { "id": "t4", - "source": "apo-IDO1", + "source": "Heme_simple_molecule", "target": "IDO1_complex", "sign": true }, { "id": "t5", - "source": "Heme_simple_molecule", + "source": "apo-IDO1", "target": "IDO1_complex", "sign": true }, @@ -1689,67 +1689,67 @@ }, { "id": "t10", - "source": "QUIN_simple_molecule", + "source": "O2_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t11", - "source": "Heme_simple_molecule", + "source": "QUIN_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t12", - "source": "ACS_simple_molecule", + "source": "Heme_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t13", - "source": "H+_ion_cell", + "source": "L-Kynurenine_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t14", - "source": "O2_simple_molecule", + "source": "ACS_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t15", - "source": "AP-DOBu_simple_molecule", + "source": "PRPP_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t16", - "source": "HMOX1_cell", + "source": "QPRT", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t17", - "source": "PRPP_simple_molecule", + "source": "NADPH_simple_molecule_cell", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t18", - "source": "NADPH_simple_molecule_cell", + "source": "AP-DOBu_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t19", - "source": "L-Kynurenine_simple_molecule", + "source": "H+_ion_cell", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t20", - "source": "QPRT", + "source": "HMOX1_cell", "target": "H2O_simple_molecule_cell", "sign": true }, @@ -1761,13 +1761,13 @@ }, { "id": "t22", - "source": "L-Tryptophan_simple_molecule_cell", + "source": "IDO2", "target": "NFK_simple_molecule", "sign": true }, { "id": "t23", - "source": "IDO2", + "source": "L-Tryptophan_simple_molecule_cell", "target": "NFK_simple_molecule", "sign": true }, @@ -1785,37 +1785,37 @@ }, { "id": "t26", - "source": "I3LACT", + "source": "PYR_simple_molecule", "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t27", - "source": "I3PROPA", + "source": "L-Kynurenine_simple_molecule", "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t28", - "source": "L-Kynurenine_simple_molecule", + "source": "L-Phe_simple_molecule", "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t29", - "source": "L-Phe_simple_molecule", + "source": "I3PROPA", "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t30", - "source": "PYR_simple_molecule", + "source": "PXLP-KYAT1_complex", "target": "AP-DOBu_simple_molecule", "sign": true }, { "id": "t31", - "source": "PXLP-KYAT1_complex", + "source": "I3LACT", "target": "AP-DOBu_simple_molecule", "sign": true }, @@ -1863,7 +1863,7 @@ }, { "id": "t39", - "source": "ATP_simple_molecule_cell", + "source": "O2_simple_molecule", "target": "NADP+_simple_molecule_cell", "sign": true }, @@ -1875,85 +1875,85 @@ }, { "id": "t41", - "source": "NAD+_simple_molecule_cell", + "source": "NADK:Zn2+ tetramer_complex", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t42", - "source": "H+_ion_cell", + "source": "NAD+_simple_molecule_cell", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t43", - "source": "O2_simple_molecule", + "source": "L-Kynurenine_simple_molecule", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t44", - "source": "HMOX1_cell", + "source": "L-Arginine_simple_molecule", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t45", - "source": "NADPH_simple_molecule_cell", + "source": "iNOS", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t46", - "source": "L-Kynurenine_simple_molecule", + "source": "NADPH_simple_molecule_cell", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t47", - "source": "NADK:Zn2+ tetramer_complex", + "source": "ATP_simple_molecule_cell", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t48", - "source": "L-Arginine_simple_molecule", + "source": "H+_ion_cell", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t49", - "source": "iNOS", + "source": "HMOX1_cell", "target": "NADP+_simple_molecule_cell", "sign": true }, { "id": "t50", - "source": "ATP_simple_molecule_cell", + "source": "NMRK2", "target": "H+_ion_cell", "sign": true }, { "id": "t51", - "source": "NAD+_simple_molecule_cell", + "source": "O2_simple_molecule", "target": "H+_ion_cell", "sign": true }, { "id": "t52", - "source": "2AMA_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "H+_ion_cell", "sign": true }, { "id": "t53", - "source": "NAR_simple_molecule", + "source": "NMRK1", "target": "H+_ion_cell", "sign": true }, { "id": "t54", - "source": "O2_simple_molecule", + "source": "L-Arginine_simple_molecule", "target": "H+_ion_cell", "sign": true }, @@ -1965,37 +1965,37 @@ }, { "id": "t56", - "source": "NADPH_simple_molecule_cell", + "source": "NR_simple_molecule", "target": "H+_ion_cell", "sign": true }, { "id": "t57", - "source": "NMRK1", + "source": "iNOS", "target": "H+_ion_cell", "sign": true }, { "id": "t58", - "source": "NR_simple_molecule", + "source": "ATP_simple_molecule_cell", "target": "H+_ion_cell", "sign": true }, { "id": "t59", - "source": "L-Arginine_simple_molecule", + "source": "NAR_simple_molecule", "target": "H+_ion_cell", "sign": true }, { "id": "t60", - "source": "NMRK2", + "source": "NADPH_simple_molecule_cell", "target": "H+_ion_cell", "sign": true }, { "id": "t61", - "source": "iNOS", + "source": "2AMA_simple_molecule", "target": "H+_ion_cell", "sign": true }, @@ -2007,79 +2007,79 @@ }, { "id": "t63", - "source": "I3LACT", + "source": "3HKYN_simple_molecule", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t64", - "source": "CCBL2", + "source": "PYR_simple_molecule", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t65", - "source": "I3PROPA", + "source": "L-Kynurenine_simple_molecule", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t66", - "source": "H2O_simple_molecule_cell", + "source": "L-Phe_simple_molecule", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t67", - "source": "KYNU", + "source": "H2O_simple_molecule_cell", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t68", - "source": "L-Kynurenine_simple_molecule", + "source": "I3PROPA", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t69", - "source": "L-Phe_simple_molecule", + "source": "PXLP-KYAT1_complex", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t70", - "source": "PYR_simple_molecule", + "source": "I3LACT", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t71", - "source": "PXLP-KYAT1_complex", + "source": "KYNU", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t72", - "source": "3HKYN_simple_molecule", + "source": "CCBL2", "target": "L-Ala_simple_molecule", "sign": true }, { "id": "t73", - "source": "H2O_simple_molecule_cell", + "source": "3HKYN_simple_molecule", "target": "3HAA_simple_molecule", "sign": true }, { "id": "t74", - "source": "KYNU", + "source": "H2O_simple_molecule_cell", "target": "3HAA_simple_molecule", "sign": true }, { "id": "t75", - "source": "3HKYN_simple_molecule", + "source": "KYNU", "target": "3HAA_simple_molecule", "sign": true }, @@ -2091,13 +2091,13 @@ }, { "id": "t77", - "source": "H+_ion_cell", + "source": "O2_simple_molecule", "target": "3HKYN_simple_molecule", "sign": true }, { "id": "t78", - "source": "O2_simple_molecule", + "source": "L-Kynurenine_simple_molecule", "target": "3HKYN_simple_molecule", "sign": true }, @@ -2109,37 +2109,37 @@ }, { "id": "t80", - "source": "L-Kynurenine_simple_molecule", + "source": "H+_ion_cell", "target": "3HKYN_simple_molecule", "sign": true }, { "id": "t81", - "source": "AHR/L-KYN_complex", + "source": "3HAA_simple_molecule", "target": "Regulatory T-cell generation_phenotype", "sign": true }, { "id": "t82", - "source": "3HAA_simple_molecule", + "source": "AHR/L-KYN_complex", "target": "Regulatory T-cell generation_phenotype", "sign": true }, { "id": "t83", - "source": "O2_simple_molecule", + "source": "3HAA_simple_molecule", "target": "ACS_simple_molecule", "sign": true }, { "id": "t84", - "source": "HAAO", + "source": "O2_simple_molecule", "target": "ACS_simple_molecule", "sign": true }, { "id": "t85", - "source": "3HAA_simple_molecule", + "source": "HAAO", "target": "ACS_simple_molecule", "sign": true }, @@ -2157,13 +2157,13 @@ }, { "id": "t88", - "source": "H+_ion_cell", + "source": "PRPP_simple_molecule", "target": "CO2_simple_molecule", "sign": true }, { "id": "t89", - "source": "PRPP_simple_molecule", + "source": "QPRT", "target": "CO2_simple_molecule", "sign": true }, @@ -2175,7 +2175,7 @@ }, { "id": "t91", - "source": "QPRT", + "source": "H+_ion_cell", "target": "CO2_simple_molecule", "sign": true }, @@ -2187,25 +2187,25 @@ }, { "id": "t93", - "source": "2AMA_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "NADH_simple_molecule_cell", "sign": true }, { "id": "t94", - "source": "H2O_simple_molecule_cell", + "source": "2AMA_simple_molecule", "target": "NADH_simple_molecule_cell", "sign": true }, { "id": "t95", - "source": "NAD+_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "NADH_simple_molecule_cell", "sign": true }, { "id": "t96", - "source": "ATP_simple_molecule_cell", + "source": "NAAD_simple_molecule_cell", "target": "NAD+_simple_molecule_cell", "sign": true }, @@ -2217,19 +2217,19 @@ }, { "id": "t98", - "source": "NAAD_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "NAD+_simple_molecule_cell", "sign": true }, { "id": "t99", - "source": "NMNAT2:Mg2+_complex", + "source": "NADSYN1 hexamer", "target": "NAD+_simple_molecule_cell", "sign": true }, { "id": "t100", - "source": "NADSYN1 hexamer", + "source": "ATP_simple_molecule_cell", "target": "NAD+_simple_molecule_cell", "sign": true }, @@ -2241,7 +2241,7 @@ }, { "id": "t102", - "source": "H2O_simple_molecule_cell", + "source": "NMNAT2:Mg2+_complex", "target": "NAD+_simple_molecule_cell", "sign": true }, @@ -2259,37 +2259,37 @@ }, { "id": "t105", - "source": "2AMA_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "2AM_simple_molecule", "sign": true }, { "id": "t106", - "source": "H2O_simple_molecule_cell", + "source": "2AMA_simple_molecule", "target": "2AM_simple_molecule", "sign": true }, { "id": "t107", - "source": "NAD+_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "2AM_simple_molecule", "sign": true }, { "id": "t108", - "source": "IFN-G", + "source": "CO_simple_molecule", "target": "iNOS_rna", "sign": true }, { "id": "t109", - "source": "CO_simple_molecule", + "source": "Nf-KB Complex_complex", "target": "iNOS_rna", "sign": true }, { "id": "t110", - "source": "Nf-KB Complex_complex", + "source": "IFN-G", "target": "iNOS_rna", "sign": true }, @@ -2325,61 +2325,61 @@ }, { "id": "t116", - "source": "IFN-G", + "source": "NO_simple_molecule", "target": "IDO1_rna", "sign": true }, { "id": "t117", - "source": "NO_simple_molecule", + "source": "IFN-G", "target": "IDO1_rna", "sign": true }, { "id": "t118", - "source": "ATP_simple_molecule_mitochondrial matrix", + "source": "NAMN_simple_molecule_mitochondrial matrix", "target": "PPi (3-)_simple_molecule", "sign": true }, { "id": "t119", - "source": "NMNAT3:Mg2+_complex", + "source": "ATP_simple_molecule_mitochondrial matrix", "target": "PPi (3-)_simple_molecule", "sign": true }, { "id": "t120", - "source": "NAMN_simple_molecule_mitochondrial matrix", + "source": "NMNAT3:Mg2+_complex", "target": "PPi (3-)_simple_molecule", "sign": true }, { "id": "t121", - "source": "ATP_simple_molecule_mitochondrial matrix", + "source": "NAMN_simple_molecule_mitochondrial matrix", "target": "NAAD_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t122", - "source": "NMNAT3:Mg2+_complex", + "source": "ATP_simple_molecule_mitochondrial matrix", "target": "NAAD_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t123", - "source": "NAMN_simple_molecule_mitochondrial matrix", + "source": "NMNAT3:Mg2+_complex", "target": "NAAD_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t124", - "source": "NAD+_simple_molecule_mitochondrial matrix", + "source": "CARKD", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t125", - "source": "S-NADPHX_simple_molecule", + "source": "NAD+_simple_molecule_mitochondrial matrix", "target": "H+_ion_mitochondrial matrix", "sign": true }, @@ -2391,25 +2391,25 @@ }, { "id": "t127", - "source": "NADK2", + "source": "S-NADPHX_simple_molecule", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t128", - "source": "CARKD", + "source": "NADK2", "target": "H+_ion_mitochondrial matrix", "sign": true }, { "id": "t129", - "source": "NAD+_simple_molecule_mitochondrial matrix", + "source": "CARKD", "target": "ADP_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t130", - "source": "S-NADPHX_simple_molecule", + "source": "NAD+_simple_molecule_mitochondrial matrix", "target": "ADP_simple_molecule_mitochondrial matrix", "sign": true }, @@ -2421,13 +2421,13 @@ }, { "id": "t132", - "source": "NADK2", + "source": "S-NADPHX_simple_molecule", "target": "ADP_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t133", - "source": "CARKD", + "source": "NADK2", "target": "ADP_simple_molecule_mitochondrial matrix", "sign": true }, @@ -2463,13 +2463,13 @@ }, { "id": "t139", - "source": "NAD+_simple_molecule_mitochondrial matrix", + "source": "ATP_simple_molecule_mitochondrial matrix", "target": "NADP+_simple_molecule_mitochondrial matrix", "sign": true }, { "id": "t140", - "source": "ATP_simple_molecule_mitochondrial matrix", + "source": "NAD+_simple_molecule_mitochondrial matrix", "target": "NADP+_simple_molecule_mitochondrial matrix", "sign": true }, @@ -2505,43 +2505,43 @@ }, { "id": "t146", - "source": "ATP_simple_molecule_cell", + "source": "Mg2+_ion", "target": "PPi_simple_molecule", "sign": true }, { "id": "t147", - "source": "L-Gln_simple_molecule", + "source": "NAAD_simple_molecule_cell", "target": "PPi_simple_molecule", "sign": true }, { "id": "t148", - "source": "H+_ion_cell", + "source": "L-Gln_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t149", - "source": "NAM_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "PPi_simple_molecule", "sign": true }, { "id": "t150", - "source": "NAAD_simple_molecule_cell", + "source": "NAMPT", "target": "PPi_simple_molecule", "sign": true }, { "id": "t151", - "source": "Mg2+_ion", + "source": "PRPP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t152", - "source": "NADSYN1 hexamer", + "source": "NCA_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, @@ -2553,103 +2553,103 @@ }, { "id": "t154", - "source": "PRPP_simple_molecule", + "source": "ATP_simple_molecule_cell", "target": "PPi_simple_molecule", "sign": true }, { "id": "t155", - "source": "H2O_simple_molecule_cell", + "source": "NADSYN1 hexamer", "target": "PPi_simple_molecule", "sign": true }, { "id": "t156", - "source": "NCA_simple_molecule", + "source": "H+_ion_cell", "target": "PPi_simple_molecule", "sign": true }, { "id": "t157", - "source": "NAMPT", + "source": "NAM_simple_molecule_cell", "target": "PPi_simple_molecule", "sign": true }, { "id": "t158", - "source": "ATP_simple_molecule_cell", + "source": "NMRK2", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t159", - "source": "QUIN_simple_molecule", + "source": "Mg2+_ion", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t160", - "source": "H+_ion_cell", + "source": "QUIN_simple_molecule", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t161", - "source": "NAM_simple_molecule_cell", + "source": "NMRK1", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t162", - "source": "NAR_simple_molecule", + "source": "NAMPT", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t163", - "source": "Mg2+_ion", + "source": "PRPP_simple_molecule", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t164", - "source": "NAPRT1", + "source": "NCA_simple_molecule", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t165", - "source": "PRPP_simple_molecule", + "source": "QPRT", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t166", - "source": "NMRK1", + "source": "ATP_simple_molecule_cell", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t167", - "source": "NCA_simple_molecule", + "source": "NAR_simple_molecule", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t168", - "source": "QPRT", + "source": "NAPRT1", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t169", - "source": "NAMPT", + "source": "H+_ion_cell", "target": "NAMN_simple_molecule_cell", "sign": true }, { "id": "t170", - "source": "NMRK2", + "source": "NAM_simple_molecule_cell", "target": "NAMN_simple_molecule_cell", "sign": true }, @@ -2667,31 +2667,31 @@ }, { "id": "t173", - "source": "ATP_simple_molecule_cell", + "source": "NMN_simple_molecule_cell", "target": "PPi(3-)_simple_molecule_cell", "sign": true }, { "id": "t174", - "source": "NMN_simple_molecule_cell", + "source": "NMNAT2:Mg2+_complex", "target": "PPi(3-)_simple_molecule_cell", "sign": true }, { "id": "t175", - "source": "NMNAT2:Mg2+_complex", + "source": "NAMN_simple_molecule_cell", "target": "PPi(3-)_simple_molecule_cell", "sign": true }, { "id": "t176", - "source": "NAMN_simple_molecule_cell", + "source": "ATP_simple_molecule_cell", "target": "PPi(3-)_simple_molecule_cell", "sign": true }, { "id": "t177", - "source": "ATP_simple_molecule_cell", + "source": "NAAD_simple_molecule_cell", "target": "L-Glu_simple_molecule", "sign": true }, @@ -2703,25 +2703,25 @@ }, { "id": "t179", - "source": "NAAD_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "L-Glu_simple_molecule", "sign": true }, { "id": "t180", - "source": "NADSYN1 hexamer", + "source": "ATP_simple_molecule_cell", "target": "L-Glu_simple_molecule", "sign": true }, { "id": "t181", - "source": "H2O_simple_molecule_cell", + "source": "NADSYN1 hexamer", "target": "L-Glu_simple_molecule", "sign": true }, { "id": "t182", - "source": "ATP_simple_molecule_cell", + "source": "NAAD_simple_molecule_cell", "target": "AMP_simple_molecule_cell", "sign": true }, @@ -2733,37 +2733,37 @@ }, { "id": "t184", - "source": "NAAD_simple_molecule_cell", + "source": "H2O_simple_molecule_cell", "target": "AMP_simple_molecule_cell", "sign": true }, { "id": "t185", - "source": "NADSYN1 hexamer", + "source": "ATP_simple_molecule_cell", "target": "AMP_simple_molecule_cell", "sign": true }, { "id": "t186", - "source": "H2O_simple_molecule_cell", + "source": "NADSYN1 hexamer", "target": "AMP_simple_molecule_cell", "sign": true }, { "id": "t187", - "source": "ATP_simple_molecule_cell", + "source": "NMRK2", "target": "ADP_simple_molecule_cell", "sign": true }, { "id": "t188", - "source": "NAD+_simple_molecule_cell", + "source": "NADK:Zn2+ tetramer_complex", "target": "ADP_simple_molecule_cell", "sign": true }, { "id": "t189", - "source": "NAR_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "ADP_simple_molecule_cell", "sign": true }, @@ -2781,13 +2781,13 @@ }, { "id": "t192", - "source": "NMRK2", + "source": "ATP_simple_molecule_cell", "target": "ADP_simple_molecule_cell", "sign": true }, { "id": "t193", - "source": "NADK:Zn2+ tetramer_complex", + "source": "NAR_simple_molecule", "target": "ADP_simple_molecule_cell", "sign": true }, @@ -2811,37 +2811,37 @@ }, { "id": "t197", - "source": "PARPs", + "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", "target": "NAM_simple_molecule_cell", "sign": true }, { "id": "t198", - "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "NAM_simple_molecule_cell", "sign": true }, { "id": "t199", - "source": "NAD+_simple_molecule_cell", + "source": "PARPs", "target": "NAM_simple_molecule_cell", "sign": true }, { "id": "t200", - "source": "NR_simple_molecule", + "source": "NMRK2", "target": "NMN_simple_molecule_cell", "sign": true }, { "id": "t201", - "source": "ATP_simple_molecule_cell", + "source": "NR_simple_molecule", "target": "NMN_simple_molecule_cell", "sign": true }, { "id": "t202", - "source": "NMRK2", + "source": "ATP_simple_molecule_cell", "target": "NMN_simple_molecule_cell", "sign": true }, @@ -2871,151 +2871,151 @@ }, { "id": "t207", - "source": "PARPs", + "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", "sign": true }, { "id": "t208", - "source": "(ADP-D-ribosyl)(n)-acceptor_simple_molecule", + "source": "NAD+_simple_molecule_cell", "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", "sign": true }, { "id": "t209", - "source": "NAD+_simple_molecule_cell", + "source": "PARPs", "target": "(ADP-D-ribosyl)(n+1)-acceptor_simple_molecule", "sign": true }, { "id": "t210", - "source": "CD38", + "source": "NAD+_simple_molecule_human host", "target": "H+_ion_human host", "sign": true }, { "id": "t211", - "source": "NAD+_simple_molecule_human host", + "source": "H2O_simple_molecule_human host", "target": "H+_ion_human host", "sign": true }, { "id": "t212", - "source": "BST1", + "source": "CD38", "target": "H+_ion_human host", "sign": true }, { "id": "t213", - "source": "H2O_simple_molecule_human host", + "source": "BST1", "target": "H+_ion_human host", "sign": true }, { "id": "t214", - "source": "CD38", + "source": "NAD+_simple_molecule_human host", "target": "NAM_simple_molecule_human host", "sign": true }, { "id": "t215", - "source": "NAD+_simple_molecule_human host", + "source": "H2O_simple_molecule_human host", "target": "NAM_simple_molecule_human host", "sign": true }, { "id": "t216", - "source": "BST1", + "source": "CD38", "target": "NAM_simple_molecule_human host", "sign": true }, { "id": "t217", - "source": "H2O_simple_molecule_human host", + "source": "BST1", "target": "NAM_simple_molecule_human host", "sign": true }, { "id": "t218", - "source": "H+_ion_human host", + "source": "RNLS:FAD_complex", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t219", - "source": "O2_ion", + "source": "dh-beta-NAD_simple_molecule", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t220", - "source": "dh-beta-NAD_simple_molecule", + "source": "O2_ion", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t221", - "source": "RNLS:FAD_complex", + "source": "H+_ion_human host", "target": "H2O2_simple_molecule", "sign": true }, { "id": "t222", - "source": "H+_ion_human host", + "source": "RNLS:FAD_complex", "target": "NAD+_simple_molecule_human host", "sign": true }, { "id": "t223", - "source": "O2_ion", + "source": "dh-beta-NAD_simple_molecule", "target": "NAD+_simple_molecule_human host", "sign": true }, { "id": "t224", - "source": "dh-beta-NAD_simple_molecule", + "source": "O2_ion", "target": "NAD+_simple_molecule_human host", "sign": true }, { "id": "t225", - "source": "RNLS:FAD_complex", + "source": "H+_ion_human host", "target": "NAD+_simple_molecule_human host", "sign": true }, { "id": "t226", - "source": "CD38", + "source": "NAD+_simple_molecule_human host", "target": "ADP-ribose_simple_molecule", "sign": true }, { "id": "t227", - "source": "NAD+_simple_molecule_human host", + "source": "H2O_simple_molecule_human host", "target": "ADP-ribose_simple_molecule", "sign": true }, { "id": "t228", - "source": "BST1", + "source": "CD38", "target": "ADP-ribose_simple_molecule", "sign": true }, { "id": "t229", - "source": "H2O_simple_molecule_human host", + "source": "BST1", "target": "ADP-ribose_simple_molecule", "sign": true }, { "id": "t230", - "source": "NMN_simple_molecule_human host", + "source": "NAD+_simple_molecule_human host", "target": "Pi_ion", "sign": true }, { "id": "t231", - "source": "NAD+_simple_molecule_human host", + "source": "H2O_simple_molecule_human host", "target": "Pi_ion", "sign": true }, @@ -3027,7 +3027,7 @@ }, { "id": "t233", - "source": "H2O_simple_molecule_human host", + "source": "NMN_simple_molecule_human host", "target": "Pi_ion", "sign": true }, @@ -3039,31 +3039,31 @@ }, { "id": "t235", - "source": "NT5E:Zn2+_complex", + "source": "H2O_simple_molecule_human host", "target": "NMN_simple_molecule_human host", "sign": true }, { "id": "t236", - "source": "H2O_simple_molecule_human host", + "source": "NT5E:Zn2+_complex", "target": "NMN_simple_molecule_human host", "sign": true }, { "id": "t237", - "source": "NMN_simple_molecule_human host", + "source": "NT5E:Zn2+_complex", "target": "NRNAM_simple_molecule", "sign": true }, { "id": "t238", - "source": "NT5E:Zn2+_complex", + "source": "H2O_simple_molecule_human host", "target": "NRNAM_simple_molecule", "sign": true }, { "id": "t239", - "source": "H2O_simple_molecule_human host", + "source": "NMN_simple_molecule_human host", "target": "NRNAM_simple_molecule", "sign": true }, @@ -3117,13 +3117,13 @@ }, { "id": "t248", - "source": "NAMN_simple_molecule_nucleus", + "source": "NMNAT1:Zn2+_complex", "target": "NAAD_simple_molecule_nucleus", "sign": true }, { "id": "t249", - "source": "NMNAT1:Zn2+_complex", + "source": "NAMN_simple_molecule_nucleus", "target": "NAAD_simple_molecule_nucleus", "sign": true }, @@ -3135,13 +3135,13 @@ }, { "id": "t251", - "source": "NAMN_simple_molecule_nucleus", + "source": "NMNAT1:Zn2+_complex", "target": "PPi(3-)_simple_molecule_nucleus", "sign": true }, { "id": "t252", - "source": "NMNAT1:Zn2+_complex", + "source": "NAMN_simple_molecule_nucleus", "target": "PPi(3-)_simple_molecule_nucleus", "sign": true }, @@ -3165,73 +3165,73 @@ }, { "id": "t256", - "source": "H+_ion_endoplasmic reticulum", + "source": "PGG2_simple_molecule", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t257", - "source": "PGG2_simple_molecule", + "source": "e-_ion", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t258", - "source": "e-_ion", + "source": "MNA_simple_molecule", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t259", - "source": "PTGS2", + "source": "PTCS2:celecoxib_complex", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t260", - "source": "PTCS2:celecoxib_complex", + "source": "H+_ion_endoplasmic reticulum", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t261", - "source": "MNA_simple_molecule", + "source": "PTGS2", "target": "PGH2_simple_molecule", "sign": true }, { "id": "t262", - "source": "H+_ion_endoplasmic reticulum", + "source": "PGG2_simple_molecule", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, { "id": "t263", - "source": "PGG2_simple_molecule", + "source": "e-_ion", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, { "id": "t264", - "source": "e-_ion", + "source": "MNA_simple_molecule", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, { "id": "t265", - "source": "PTGS2", + "source": "PTCS2:celecoxib_complex", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, { "id": "t266", - "source": "PTCS2:celecoxib_complex", + "source": "H+_ion_endoplasmic reticulum", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, { "id": "t267", - "source": "MNA_simple_molecule", + "source": "PTGS2", "target": "H2O_simple_molecule_endoplasmic reticulum", "sign": true }, @@ -3243,13 +3243,13 @@ }, { "id": "t269", - "source": "SLC5A8", + "source": "Na+_ion_human host", "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", "sign": true }, { "id": "t270", - "source": "Na+_ion_human host", + "source": "SLC5A8", "target": "monocarboxylates transported by SLC5A8_simple_molecule_cell", "sign": true }, @@ -3261,19 +3261,19 @@ }, { "id": "t272", - "source": "SLC5A8", + "source": "Na+_ion_human host", "target": "Na+_ion_cell", "sign": true }, { "id": "t273", - "source": "Na+_ion_human host", + "source": "SLC5A8", "target": "Na+_ion_cell", "sign": true }, { "id": "t274", - "source": "IFN-G", + "source": "3HAA_simple_molecule", "target": "HMOX1_rna", "sign": true }, @@ -3285,7 +3285,7 @@ }, { "id": "t276", - "source": "3HAA_simple_molecule", + "source": "IFN-G", "target": "HMOX1_rna", "sign": true }, @@ -3309,13 +3309,13 @@ }, { "id": "t280", - "source": "HMOX1_cell", + "source": "Heme_simple_molecule", "target": "Fe2+_ion", "sign": true }, { "id": "t281", - "source": "Heme_simple_molecule", + "source": "HMOX1_cell", "target": "Fe2+_ion", "sign": true }, @@ -3333,13 +3333,13 @@ }, { "id": "t284", - "source": "HMOX1_cell", + "source": "Heme_simple_molecule", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t285", - "source": "Heme_simple_molecule", + "source": "HMOX1_cell", "target": "Biliverdin_simple_molecule", "sign": true }, @@ -3357,13 +3357,13 @@ }, { "id": "t288", - "source": "HMOX1_cell", + "source": "Heme_simple_molecule", "target": "CO_simple_molecule", "sign": true }, { "id": "t289", - "source": "Heme_simple_molecule", + "source": "HMOX1_cell", "target": "CO_simple_molecule", "sign": true }, @@ -3405,13 +3405,13 @@ }, { "id": "t296", - "source": "CA_simple_molecule", + "source": "3HKYN_simple_molecule", "target": "T-cell apoptosis_phenotype", "sign": true }, { "id": "t297", - "source": "3HKYN_simple_molecule", + "source": "CA_simple_molecule", "target": "T-cell apoptosis_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json index 2c8959bf5..94f06207d 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/NLRP3_Activation.json @@ -644,49 +644,49 @@ }, { "id": "t3", - "source": "SUGT1:HSP90AB1_complex", + "source": "NLRP3_cell", "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { "id": "t4", - "source": "NLRP3_cell", + "source": "SUGT1:HSP90AB1_complex", "target": "NLRP3:SUGT1:HSP90_complex", "sign": true }, { "id": "t5", - "source": "CASP1_cell", + "source": "NLRP3 oligomer:ASC_complex", "target": "NLRP3 oligomer:ASC:proCaspase1_complex", "sign": true }, { "id": "t6", - "source": "NLRP3 oligomer:ASC_complex", + "source": "CASP1_cell", "target": "NLRP3 oligomer:ASC:proCaspase1_complex", "sign": true }, { "id": "t7", - "source": "CTSG", + "source": "NLRP3 oligomer:ASC:proCaspase1_complex", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t8", - "source": "NLRP3 oligomer:ASC:proCaspase1_complex", + "source": "NLRP3_cell", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t9", - "source": "ASC_ubiquitinated", + "source": "CTSG", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, { "id": "t10", - "source": "NLRP3_cell", + "source": "ASC_ubiquitinated", "target": "NLRP3 oligomer:ASC_complex", "sign": true }, @@ -698,13 +698,13 @@ }, { "id": "t12", - "source": "TXNIP", + "source": "NLRP3_cell", "target": "TXNIP:NLRP3_complex", "sign": true }, { "id": "t13", - "source": "NLRP3_cell", + "source": "TXNIP", "target": "TXNIP:NLRP3_complex", "sign": true }, @@ -734,13 +734,13 @@ }, { "id": "t18", - "source": "p50", + "source": "p65", "target": "Nf-KB Complex_complex_cell", "sign": true }, { "id": "t19", - "source": "p65", + "source": "p50", "target": "Nf-KB Complex_complex_cell", "sign": true }, @@ -758,13 +758,13 @@ }, { "id": "t22", - "source": "TXN_cell", + "source": "TXNIP", "target": "Thioredoxin:TXNIP_complex", "sign": true }, { "id": "t23", - "source": "TXNIP", + "source": "TXN_cell", "target": "Thioredoxin:TXNIP_complex", "sign": true }, @@ -794,49 +794,49 @@ }, { "id": "t28", - "source": "Ca2+_ion", + "source": "NLRP3 Elicitor Proteins", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t29", - "source": "NLRP3 Elicitor Proteins", + "source": "DAMPs_phenotype", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t30", - "source": "NLRP3:SUGT1:HSP90_complex", + "source": "PAMPs_phenotype", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t31", - "source": "PAMPs_phenotype", + "source": "Reactive Oxygen Species_simple_molecule", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t32", - "source": "Reactive Oxygen Species_simple_molecule", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t33", - "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "source": "TXNIP:NLRP3_complex", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t34", - "source": "DAMPs_phenotype", + "source": "Ca2+_ion", "target": "SUGT1:HSP90AB1_complex", "sign": true }, { "id": "t35", - "source": "TXNIP:NLRP3_complex", + "source": "NLRP3:SUGT1:HSP90_complex", "target": "SUGT1:HSP90AB1_complex", "sign": true }, @@ -878,13 +878,13 @@ }, { "id": "t42", - "source": "proIL-1B_cell", + "source": "Caspase-1 Tetramer_complex", "target": "IL-1B_cell", "sign": true }, { "id": "t43", - "source": "Caspase-1 Tetramer_complex", + "source": "proIL-1B_cell", "target": "IL-1B_cell", "sign": true }, @@ -938,49 +938,49 @@ }, { "id": "t52", - "source": "Ca2+_ion", + "source": "NLRP3 Elicitor Proteins", "target": "NLRP3_cell", "sign": true }, { "id": "t53", - "source": "NLRP3 Elicitor Proteins", + "source": "DAMPs_phenotype", "target": "NLRP3_cell", "sign": true }, { "id": "t54", - "source": "NLRP3:SUGT1:HSP90_complex", + "source": "PAMPs_phenotype", "target": "NLRP3_cell", "sign": true }, { "id": "t55", - "source": "PAMPs_phenotype", + "source": "Reactive Oxygen Species_simple_molecule", "target": "NLRP3_cell", "sign": true }, { "id": "t56", - "source": "Reactive Oxygen Species_simple_molecule", + "source": "NLRP3 Elicitor Small Molecules_simple_molecule", "target": "NLRP3_cell", "sign": true }, { "id": "t57", - "source": "NLRP3 Elicitor Small Molecules_simple_molecule", + "source": "TXNIP:NLRP3_complex", "target": "NLRP3_cell", "sign": true }, { "id": "t58", - "source": "DAMPs_phenotype", + "source": "Ca2+_ion", "target": "NLRP3_cell", "sign": true }, { "id": "t59", - "source": "TXNIP:NLRP3_complex", + "source": "NLRP3:SUGT1:HSP90_complex", "target": "NLRP3_cell", "sign": true }, @@ -1010,13 +1010,13 @@ }, { "id": "t64", - "source": "O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t65", - "source": "HMOX1", + "source": "O2_simple_molecule", "target": "NADP+_simple_molecule", "sign": true }, @@ -1028,19 +1028,19 @@ }, { "id": "t67", - "source": "NADPH_simple_molecule", + "source": "HMOX1", "target": "NADP+_simple_molecule", "sign": true }, { "id": "t68", - "source": "O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t69", - "source": "HMOX1", + "source": "O2_simple_molecule", "target": "Biliverdin_simple_molecule", "sign": true }, @@ -1052,19 +1052,19 @@ }, { "id": "t71", - "source": "NADPH_simple_molecule", + "source": "HMOX1", "target": "Biliverdin_simple_molecule", "sign": true }, { "id": "t72", - "source": "O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "H2O_simple_molecule", "sign": true }, { "id": "t73", - "source": "HMOX1", + "source": "O2_simple_molecule", "target": "H2O_simple_molecule", "sign": true }, @@ -1076,19 +1076,19 @@ }, { "id": "t75", - "source": "NADPH_simple_molecule", + "source": "HMOX1", "target": "H2O_simple_molecule", "sign": true }, { "id": "t76", - "source": "O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "CO_simple_molecule", "sign": true }, { "id": "t77", - "source": "HMOX1", + "source": "O2_simple_molecule", "target": "CO_simple_molecule", "sign": true }, @@ -1100,19 +1100,19 @@ }, { "id": "t79", - "source": "NADPH_simple_molecule", + "source": "HMOX1", "target": "CO_simple_molecule", "sign": true }, { "id": "t80", - "source": "O2_simple_molecule", + "source": "NADPH_simple_molecule", "target": "Fe2+_ion", "sign": true }, { "id": "t81", - "source": "HMOX1", + "source": "O2_simple_molecule", "target": "Fe2+_ion", "sign": true }, @@ -1124,7 +1124,7 @@ }, { "id": "t83", - "source": "NADPH_simple_molecule", + "source": "HMOX1", "target": "Fe2+_ion", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json index 6a98c0d47..08b98449b 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp14.json @@ -1807,109 +1807,109 @@ "edges": [ { "id": "t1", - "source": "SIRT5", + "source": "Nsp14_mitochondrion", "target": "SIRT5:Nsp14_complex", "sign": true }, { "id": "t2", - "source": "Nsp14_mitochondrion", + "source": "SIRT5", "target": "SIRT5:Nsp14_complex", "sign": true }, { "id": "t3", - "source": "GLA", + "source": "Nsp14_cell", "target": "GLA:Nsp14_complex", "sign": true }, { "id": "t4", - "source": "Nsp14_cell", + "source": "GLA", "target": "GLA:Nsp14_complex", "sign": true }, { "id": "t5", - "source": "IMPDH2", + "source": "Nsp14_cell", "target": "IMPDH2:Nsp14_complex", "sign": true }, { "id": "t6", - "source": "Nsp14_cell", + "source": "IMPDH2", "target": "IMPDH2:Nsp14_complex", "sign": true }, { "id": "t7", - "source": "NADP_simple_molecule", + "source": "Raffinose_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t8", - "source": "LCT", + "source": "Stachyose_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t9", - "source": "AKR1B1", + "source": "GLA", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t10", - "source": "Galacitol_simple_molecule", + "source": "Lactose_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t11", - "source": "Melibiose_simple_molecule", + "source": "NADP_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t12", - "source": "GLA:Nsp14_complex", + "source": "GLB1", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t13", - "source": "Migalastat_drug", + "source": "LCT", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t14", - "source": "Lactose_simple_molecule", + "source": "Melibiose_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t15", - "source": "GLB1", + "source": "GLA:Nsp14_complex", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t16", - "source": "GLA", + "source": "Migalastat_drug", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t17", - "source": "Raffinose_simple_molecule", + "source": "AKR1B1", "target": "D-Galactose_simple_molecule", "sign": true }, { "id": "t18", - "source": "Stachyose_simple_molecule", + "source": "Galacitol_simple_molecule", "target": "D-Galactose_simple_molecule", "sign": true }, @@ -1921,79 +1921,79 @@ }, { "id": "t20", - "source": "D-Galactose_simple_molecule", + "source": "GALM", "target": "_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t21", - "source": "GALM", + "source": "D-Galactose_simple_molecule", "target": "_alpha_-D-Galactose_simple_molecule", "sign": true }, { "id": "t22", - "source": "_alpha_-D-Galactose_simple_molecule", + "source": "ATP_simple_molecule", "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t23", - "source": "ATP_simple_molecule", + "source": "GALK1", "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t24", - "source": "GALK1", + "source": "_alpha_-D-Galactose_simple_molecule", "target": "_alpha_-D-Galactose-1P_simple_molecule", "sign": true }, { "id": "t25", - "source": "DCK", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t26", - "source": "NME6", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t27", - "source": "GMP_simple_molecule", + "source": "NME7", "target": "ADP_simple_molecule", "sign": true }, { "id": "t28", - "source": "AK1", + "source": "ADK", "target": "ADP_simple_molecule", "sign": true }, { "id": "t29", - "source": "ADK", + "source": "NRK1", "target": "ADP_simple_molecule", "sign": true }, { "id": "t30", - "source": "GUK1", + "source": "Deoxyadenosine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t31", - "source": "NAD_simple_molecule", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t32", - "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "source": "GUK1", "target": "ADP_simple_molecule", "sign": true }, @@ -2005,223 +2005,223 @@ }, { "id": "t34", - "source": "Adenosine_simple_molecule", + "source": "GALK1", "target": "ADP_simple_molecule", "sign": true }, { "id": "t35", - "source": "GALK1", + "source": "_alpha_-D-Galactose_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t36", - "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "source": "AK7", "target": "ADP_simple_molecule", "sign": true }, { "id": "t37", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "Deamino-NAD_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t38", - "source": "dAMP_simple_molecule", + "source": "L-Aspartate_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t39", - "source": "NADK", + "source": "AMP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t40", - "source": "L-Aspartate_simple_molecule", + "source": "Glycine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t41", - "source": "AMP_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t42", - "source": "L-Glutamine_simple_molecule", + "source": "NADK", "target": "ADP_simple_molecule", "sign": true }, { "id": "t43", - "source": "NME7", + "source": "L-Glutamine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t44", - "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "source": "GMP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t45", - "source": "PFAS", + "source": "AK8", "target": "ADP_simple_molecule", "sign": true }, { "id": "t46", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "source": "Adenosine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t47", - "source": "AK5", + "source": "NAPRT1", "target": "ADP_simple_molecule", "sign": true }, { "id": "t48", - "source": "H2O_simple_molecule_cell", + "source": "dGDP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t49", - "source": "dADP_simple_molecule", + "source": "NME5", "target": "ADP_simple_molecule", "sign": true }, { "id": "t50", - "source": "NME5", + "source": "Nicotinate_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t51", - "source": "NAPRT1", + "source": "PAICS", "target": "ADP_simple_molecule", "sign": true }, { "id": "t52", - "source": "Nicotinate_simple_molecule", + "source": "NME3", "target": "ADP_simple_molecule", "sign": true }, { "id": "t53", - "source": "GART", + "source": "NADSYN1", "target": "ADP_simple_molecule", "sign": true }, { "id": "t54", - "source": "dGDP_simple_molecule", + "source": "Nucleoside diphosphate kinase_complex_cell", "target": "ADP_simple_molecule", "sign": true }, { "id": "t55", - "source": "NME3", + "source": "ATP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t56", - "source": "N-Ribosyl-nicotinamide_simple_molecule", + "source": "dAMP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t57", - "source": "AK7", + "source": "NME6", "target": "ADP_simple_molecule", "sign": true }, { "id": "t58", - "source": "ATP_simple_molecule", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t59", - "source": "Deoxyguanosine_simple_molecule", + "source": "PFAS", "target": "ADP_simple_molecule", "sign": true }, { "id": "t60", - "source": "PAICS", + "source": "GDP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t61", - "source": "Nucleoside diphosphate kinase_complex_cell", + "source": "DCK", "target": "ADP_simple_molecule", "sign": true }, { "id": "t62", - "source": "NADSYN1", + "source": "dADP_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t63", - "source": "AK8", + "source": "Deoxyguanosine_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t64", - "source": "Deoxyadenosine_simple_molecule", + "source": "NAD_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t65", - "source": "_alpha_-D-Galactose_simple_molecule", + "source": "AK5", "target": "ADP_simple_molecule", "sign": true }, { "id": "t66", - "source": "NRK1", + "source": "N-Ribosyl-nicotinamide_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t67", - "source": "Glycine_simple_molecule", + "source": "GART", "target": "ADP_simple_molecule", "sign": true }, { "id": "t68", - "source": "GDP_simple_molecule", + "source": "H2O_simple_molecule_cell", "target": "ADP_simple_molecule", "sign": true }, { "id": "t69", - "source": "Deamino-NAD_simple_molecule", + "source": "AK1", "target": "ADP_simple_molecule", "sign": true }, { "id": "t70", - "source": "_alpha_-D-Galactose-1P_simple_molecule", + "source": "GALE", "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, @@ -2239,7 +2239,7 @@ }, { "id": "t73", - "source": "GALE", + "source": "_alpha_-D-Galactose-1P_simple_molecule", "target": "UDP-_alpha_-D-Galactose_simple_molecule", "sign": true }, @@ -2251,103 +2251,103 @@ }, { "id": "t75", - "source": "UGP2", + "source": "GALT", "target": "_alpha_-D-Glucose-1-P_simple_molecule", "sign": true }, { "id": "t76", - "source": "_alpha_-D-Galactose-1P_simple_molecule", + "source": "PPi_simple_molecule", "target": "_alpha_-D-Glucose-1-P_simple_molecule", "sign": true }, { "id": "t77", - "source": "GALT", + "source": "UGP2", "target": "_alpha_-D-Glucose-1-P_simple_molecule", "sign": true }, { "id": "t78", - "source": "PPi_simple_molecule", + "source": "_alpha_-D-Galactose-1P_simple_molecule", "target": "_alpha_-D-Glucose-1-P_simple_molecule", "sign": true }, { "id": "t79", - "source": "PPi_simple_molecule", + "source": "UDP-_alpha_-D-Glucose_simple_molecule", "target": "UTP_simple_molecule", "sign": true }, { "id": "t80", - "source": "UDP-_alpha_-D-Glucose_simple_molecule", + "source": "UGP2", "target": "UTP_simple_molecule", "sign": true }, { "id": "t81", - "source": "UGP2", + "source": "PPi_simple_molecule", "target": "UTP_simple_molecule", "sign": true }, { "id": "t82", - "source": "Nicotinamide_simple_molecule", + "source": "HPRT1", "target": "PPi_simple_molecule", "sign": true }, { "id": "t83", - "source": "NMNAT3", + "source": "ITPA", "target": "PPi_simple_molecule", "sign": true }, { "id": "t84", - "source": "NAPRT1", + "source": "APRT", "target": "PPi_simple_molecule", "sign": true }, { "id": "t85", - "source": "Guanine_simple_molecule", + "source": "NMNAT1", "target": "PPi_simple_molecule", "sign": true }, { "id": "t86", - "source": "Nicotinate_simple_molecule", + "source": "GMPS", "target": "PPi_simple_molecule", "sign": true }, { "id": "t87", - "source": "HPRT1", + "source": "Hypoxanthine_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t88", - "source": "GMPS", + "source": "QPRT", "target": "PPi_simple_molecule", "sign": true }, { "id": "t89", - "source": "dGTP_simple_molecule", + "source": "PPAT", "target": "PPi_simple_molecule", "sign": true }, { "id": "t90", - "source": "PPAT", + "source": "Nicotinate_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t91", - "source": "APRT", + "source": "dGTP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, @@ -2359,91 +2359,91 @@ }, { "id": "t93", - "source": "QPRT", + "source": "NAMPT", "target": "PPi_simple_molecule", "sign": true }, { "id": "t94", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "NMNAT3", "target": "PPi_simple_molecule", "sign": true }, { "id": "t95", - "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "source": "Quinolinate_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t96", - "source": "Hypoxanthine_simple_molecule", + "source": "Guanine_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t97", - "source": "NMNAT2", + "source": "Nicotinate D-ribonucleotide_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t98", - "source": "Adenine_simple_molecule", + "source": "H_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t99", - "source": "H_simple_molecule", + "source": "Nicotinamide_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t100", - "source": "L-Glutamine_simple_molecule", + "source": "XMP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t101", - "source": "NMNAT1", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t102", - "source": "Quinolinate_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t103", - "source": "ENPP1", + "source": "ENPP3", "target": "PPi_simple_molecule", "sign": true }, { "id": "t104", - "source": "ENPP3", + "source": "Adenine_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t105", - "source": "XMP_simple_molecule", + "source": "L-Glutamine_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t106", - "source": "NAMPT", + "source": "ENPP1", "target": "PPi_simple_molecule", "sign": true }, { "id": "t107", - "source": "Nicotinate D-ribonucleotide_simple_molecule", + "source": "NAPRT1", "target": "PPi_simple_molecule", "sign": true }, @@ -2455,7 +2455,7 @@ }, { "id": "t109", - "source": "ITPA", + "source": "NMNAT2", "target": "PPi_simple_molecule", "sign": true }, @@ -2467,25 +2467,25 @@ }, { "id": "t111", - "source": "UDP-_alpha_-D-Galactose_simple_molecule", + "source": "lactose synthetase_complex", "target": "Lactose_simple_molecule", "sign": true }, { "id": "t112", - "source": "lactose synthetase_complex", + "source": "UDP-_alpha_-D-Galactose_simple_molecule", "target": "Lactose_simple_molecule", "sign": true }, { "id": "t113", - "source": "Melibiose_simple_molecule", + "source": "GLA", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, { "id": "t114", - "source": "LCT", + "source": "Lactose_simple_molecule", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, @@ -2497,25 +2497,25 @@ }, { "id": "t116", - "source": "Migalastat_drug", + "source": "GLB1", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, { "id": "t117", - "source": "Lactose_simple_molecule", + "source": "LCT", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, { "id": "t118", - "source": "GLB1", + "source": "Melibiose_simple_molecule", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, { "id": "t119", - "source": "GLA", + "source": "Migalastat_drug", "target": "_alpha_-D-Glucose_simple_molecule", "sign": true }, @@ -2533,13 +2533,13 @@ }, { "id": "t122", - "source": "UDP-_alpha_-D-Galactose_simple_molecule", + "source": "lactose synthetase_complex", "target": "UDP_simple_molecule", "sign": true }, { "id": "t123", - "source": "lactose synthetase_complex", + "source": "UDP-_alpha_-D-Galactose_simple_molecule", "target": "UDP_simple_molecule", "sign": true }, @@ -2551,13 +2551,13 @@ }, { "id": "t125", - "source": "ATIC", + "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t126", - "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "source": "ADP_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, @@ -2569,37 +2569,37 @@ }, { "id": "t128", - "source": "Thioredoxin_simple_molecule", + "source": "ATIC", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t129", - "source": "ADP_simple_molecule", + "source": "Thioredoxin_simple_molecule", "target": "H2O_simple_molecule_cell", "sign": true }, { "id": "t130", - "source": "NADK", + "source": "NADPH_simple_molecule", "target": "NADP_simple_molecule", "sign": true }, { "id": "t131", - "source": "NADPH_simple_molecule", + "source": "NADK", "target": "NADP_simple_molecule", "sign": true }, { "id": "t132", - "source": "NNT", + "source": "NAD_simple_molecule", "target": "NADP_simple_molecule", "sign": true }, { "id": "t133", - "source": "NAD_simple_molecule", + "source": "NNT", "target": "NADP_simple_molecule", "sign": true }, @@ -2611,295 +2611,295 @@ }, { "id": "t135", - "source": "NADP_simple_molecule", + "source": "IMP_simple_molecule", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t136", - "source": "AKR1B1", + "source": "NADP_simple_molecule", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t137", - "source": "Galacitol_simple_molecule", + "source": "Ammonium_simple_molecule", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t138", - "source": "GMPR2", + "source": "GMPR", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t139", - "source": "Ammonium_simple_molecule", + "source": "AKR1B1", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t140", - "source": "GMPR", + "source": "GMPR2", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t141", - "source": "IMP_simple_molecule", + "source": "Galacitol_simple_molecule", "target": "NADPH_simple_molecule", "sign": true }, { "id": "t142", - "source": "DCK", + "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t143", - "source": "NADP_simple_molecule", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t144", - "source": "GTP_simple_molecule", + "source": "ENTPD5", "target": "H_simple_molecule", "sign": true }, { "id": "t145", - "source": "Ribavirin_drug", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t146", - "source": "Merimepodib_drug", + "source": "IMP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t147", - "source": "ENTPD5", + "source": "GMPS", "target": "H_simple_molecule", "sign": true }, { "id": "t148", - "source": "ADK", + "source": "Hypoxanthine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t149", - "source": "NAD_simple_molecule", + "source": "NRK1", "target": "H_simple_molecule", "sign": true }, { "id": "t150", - "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "source": "ADK", "target": "H_simple_molecule", "sign": true }, { "id": "t151", - "source": "10-Formyltetrahydrofolate_simple_molecule", + "source": "Deoxyadenosine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t152", - "source": "Adenosine_simple_molecule", + "source": "Ammonium_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t153", - "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "source": "IMPDH2:Nsp14_complex", "target": "H_simple_molecule", "sign": true }, { "id": "t154", - "source": "NADK", + "source": "Ribavirin_drug", "target": "H_simple_molecule", "sign": true }, { "id": "t155", - "source": "CD38", + "source": "CANT1", "target": "H_simple_molecule", "sign": true }, { "id": "t156", - "source": "L-Aspartate_simple_molecule", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t157", - "source": "IMPDH1", + "source": "Mycophenolic acid_drug", "target": "H_simple_molecule", "sign": true }, { "id": "t158", - "source": "AKR1B1", + "source": "GMPR2", "target": "H_simple_molecule", "sign": true }, { "id": "t159", - "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "source": "ENTPD2", "target": "H_simple_molecule", "sign": true }, { "id": "t160", - "source": "CANT1", + "source": "Merimepodib_drug", "target": "H_simple_molecule", "sign": true }, { "id": "t161", - "source": "L-Glutamine_simple_molecule", + "source": "Deamino-NAD_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t162", - "source": "GMPR2", + "source": "CD38", "target": "H_simple_molecule", "sign": true }, { "id": "t163", - "source": "Hypoxanthine_simple_molecule", + "source": "L-Aspartate_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t164", - "source": "XDH", + "source": "XMP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t165", - "source": "CO2_simple_molecule", + "source": "Glycine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t166", - "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "source": "ENPP3", "target": "H_simple_molecule", "sign": true }, { "id": "t167", - "source": "ENPP3", + "source": "NADK", "target": "H_simple_molecule", "sign": true }, { "id": "t168", - "source": "Aminoimidazole ribotide_simple_molecule", + "source": "L-Glutamine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t169", - "source": "PFAS", + "source": "IMPDH2", "target": "H_simple_molecule", "sign": true }, { "id": "t170", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "source": "GTP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t171", - "source": "IMPDH2", + "source": "ENPP1", "target": "H_simple_molecule", "sign": true }, { "id": "t172", - "source": "H2O_simple_molecule_cell", + "source": "Adenosine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t173", - "source": "ENTPD4", + "source": "AKR1B1", "target": "H_simple_molecule", "sign": true }, { "id": "t174", - "source": "IMPDH2:Nsp14_complex", + "source": "Aminoimidazole ribotide_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t175", - "source": "ENTPD6", + "source": "CO2_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t176", - "source": "GART", + "source": "ITPA", "target": "H_simple_molecule", "sign": true }, { "id": "t177", - "source": "Ammonium_simple_molecule", + "source": "NTPCR", "target": "H_simple_molecule", "sign": true }, { "id": "t178", - "source": "N-Ribosyl-nicotinamide_simple_molecule", + "source": "NADP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t179", - "source": "GMPS", + "source": "IMPDH1", "target": "H_simple_molecule", "sign": true }, { "id": "t180", - "source": "dGTP_simple_molecule", + "source": "PAICS", "target": "H_simple_molecule", "sign": true }, { "id": "t181", - "source": "ATP_simple_molecule", + "source": "NADSYN1", "target": "H_simple_molecule", "sign": true }, { "id": "t182", - "source": "Mycophenolic acid_drug", + "source": "dGTP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t183", - "source": "Deoxyguanosine_simple_molecule", + "source": "ATP_simple_molecule", "target": "H_simple_molecule", "sign": true }, @@ -2911,109 +2911,109 @@ }, { "id": "t185", - "source": "PAICS", + "source": "XDH", "target": "H_simple_molecule", "sign": true }, { "id": "t186", - "source": "ENTPD2", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t187", - "source": "NADSYN1", + "source": "PFAS", "target": "H_simple_molecule", "sign": true }, { "id": "t188", - "source": "ENPP1", + "source": "ENTPD4", "target": "H_simple_molecule", "sign": true }, { "id": "t189", - "source": "Deoxyadenosine_simple_molecule", + "source": "GDP_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t190", - "source": "NRK1", + "source": "DCK", "target": "H_simple_molecule", "sign": true }, { "id": "t191", - "source": "Glycine_simple_molecule", + "source": "ENTPD6", "target": "H_simple_molecule", "sign": true }, { "id": "t192", - "source": "XMP_simple_molecule", + "source": "Deoxyguanosine_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t193", - "source": "GMPR", + "source": "NAD_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t194", - "source": "GDP_simple_molecule", + "source": "GMPR", "target": "H_simple_molecule", "sign": true }, { "id": "t195", - "source": "IMP_simple_molecule", + "source": "N-Ribosyl-nicotinamide_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t196", - "source": "NTPCR", + "source": "10-Formyltetrahydrofolate_simple_molecule", "target": "H_simple_molecule", "sign": true }, { "id": "t197", - "source": "Deamino-NAD_simple_molecule", + "source": "GART", "target": "H_simple_molecule", "sign": true }, { "id": "t198", - "source": "ITPA", + "source": "H2O_simple_molecule_cell", "target": "H_simple_molecule", "sign": true }, { "id": "t199", - "source": "GLA:Nsp14_complex", + "source": "Stachyose_simple_molecule", "target": "Raffinose_simple_molecule", "sign": true }, { "id": "t200", - "source": "Migalastat_drug", + "source": "GLA", "target": "Raffinose_simple_molecule", "sign": true }, { "id": "t201", - "source": "GLA", + "source": "Migalastat_drug", "target": "Raffinose_simple_molecule", "sign": true }, { "id": "t202", - "source": "Stachyose_simple_molecule", + "source": "GLA:Nsp14_complex", "target": "Raffinose_simple_molecule", "sign": true }, @@ -3025,25 +3025,25 @@ }, { "id": "t204", - "source": "GLA:Nsp14_complex", + "source": "Raffinose_simple_molecule", "target": "Sucrose_simple_molecule", "sign": true }, { "id": "t205", - "source": "Migalastat_drug", + "source": "GLA", "target": "Sucrose_simple_molecule", "sign": true }, { "id": "t206", - "source": "GLA", + "source": "GLA:Nsp14_complex", "target": "Sucrose_simple_molecule", "sign": true }, { "id": "t207", - "source": "Raffinose_simple_molecule", + "source": "Migalastat_drug", "target": "Sucrose_simple_molecule", "sign": true }, @@ -3055,13 +3055,13 @@ }, { "id": "t209", - "source": "PNP", + "source": "CD38", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t210", - "source": "CD38", + "source": "H2O_simple_molecule_mitochondrion", "target": "Nicotinamide_simple_molecule", "sign": true }, @@ -3073,37 +3073,37 @@ }, { "id": "t212", - "source": "Pi_simple_molecule", + "source": "SIRT5:Nsp14_complex", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t213", - "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "source": "Pi_simple_molecule", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t214", - "source": "H2O_simple_molecule_mitochondrion", + "source": "NAD_simple_molecule", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t215", - "source": "Nicotinate_simple_molecule", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t216", - "source": "NAD_simple_molecule", + "source": "SIRT5", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t217", - "source": "SIRT5", + "source": "Nicotinate_simple_molecule", "target": "Nicotinamide_simple_molecule", "sign": true }, @@ -3115,13 +3115,13 @@ }, { "id": "t219", - "source": "SIRT5:Nsp14_complex", + "source": "H2O_simple_molecule_cell", "target": "Nicotinamide_simple_molecule", "sign": true }, { "id": "t220", - "source": "H2O_simple_molecule_cell", + "source": "PNP", "target": "Nicotinamide_simple_molecule", "sign": true }, @@ -3151,37 +3151,37 @@ }, { "id": "t225", - "source": "NAD_simple_molecule", + "source": "ENPP3", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t226", - "source": "ENPP1", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t227", - "source": "N-Ribosyl-nicotinamide_simple_molecule", + "source": "NRK1", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t228", - "source": "ENPP3", + "source": "NAD_simple_molecule", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t229", - "source": "NRK1", + "source": "ENPP1", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t230", - "source": "NAMPT", + "source": "N-Ribosyl-nicotinamide_simple_molecule", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, @@ -3193,37 +3193,37 @@ }, { "id": "t232", - "source": "H2O_simple_molecule_cell", + "source": "NAMPT", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t233", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "H2O_simple_molecule_cell", "target": "Nicotinamide D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t234", - "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "source": "Deamino-NAD_simple_molecule", "target": "NAD_simple_molecule", "sign": true }, { "id": "t235", - "source": "NMNAT2", + "source": "H_simple_molecule", "target": "NAD_simple_molecule", "sign": true }, { "id": "t236", - "source": "H_simple_molecule", + "source": "NMNAT1", "target": "NAD_simple_molecule", "sign": true }, { "id": "t237", - "source": "L-Glutamine_simple_molecule", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", "target": "NAD_simple_molecule", "sign": true }, @@ -3235,7 +3235,7 @@ }, { "id": "t239", - "source": "NMNAT1", + "source": "L-Glutamine_simple_molecule", "target": "NAD_simple_molecule", "sign": true }, @@ -3259,13 +3259,13 @@ }, { "id": "t243", - "source": "Deamino-NAD_simple_molecule", + "source": "NMNAT2", "target": "NAD_simple_molecule", "sign": true }, { "id": "t244", - "source": "NMNAT2", + "source": "Nicotinate D-ribonucleotide_simple_molecule", "target": "Deamino-NAD_simple_molecule", "sign": true }, @@ -3277,25 +3277,25 @@ }, { "id": "t246", - "source": "NMNAT3", + "source": "NMNAT1", "target": "Deamino-NAD_simple_molecule", "sign": true }, { "id": "t247", - "source": "NMNAT1", + "source": "ATP_simple_molecule", "target": "Deamino-NAD_simple_molecule", "sign": true }, { "id": "t248", - "source": "Nicotinate D-ribonucleotide_simple_molecule", + "source": "NMNAT3", "target": "Deamino-NAD_simple_molecule", "sign": true }, { "id": "t249", - "source": "ATP_simple_molecule", + "source": "NMNAT2", "target": "Deamino-NAD_simple_molecule", "sign": true }, @@ -3307,31 +3307,31 @@ }, { "id": "t251", - "source": "NAPRT1", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t252", - "source": "Nicotinate_simple_molecule", + "source": "QPRT", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t253", - "source": "Quinolinate_simple_molecule", + "source": "Nicotinate_simple_molecule", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t254", - "source": "ATP_simple_molecule", + "source": "NAPRT1", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t255", - "source": "QPRT", + "source": "ATP_simple_molecule", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, @@ -3343,25 +3343,25 @@ }, { "id": "t257", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "Quinolinate_simple_molecule", "target": "Nicotinate D-ribonucleotide_simple_molecule", "sign": true }, { "id": "t258", - "source": "Mycophenolic acid_drug", + "source": "Merimepodib_drug", "target": "NADH_simple_molecule", "sign": true }, { "id": "t259", - "source": "IMPDH1", + "source": "NADPH_simple_molecule", "target": "NADH_simple_molecule", "sign": true }, { "id": "t260", - "source": "NADPH_simple_molecule", + "source": "IMP_simple_molecule", "target": "NADH_simple_molecule", "sign": true }, @@ -3373,49 +3373,49 @@ }, { "id": "t262", - "source": "Ribavirin_drug", + "source": "NAD_simple_molecule", "target": "NADH_simple_molecule", "sign": true }, { "id": "t263", - "source": "NNT", + "source": "IMPDH2", "target": "NADH_simple_molecule", "sign": true }, { "id": "t264", - "source": "IMPDH2:Nsp14_complex", + "source": "IMPDH1", "target": "NADH_simple_molecule", "sign": true }, { "id": "t265", - "source": "XDH", + "source": "IMPDH2:Nsp14_complex", "target": "NADH_simple_molecule", "sign": true }, { "id": "t266", - "source": "Merimepodib_drug", + "source": "NNT", "target": "NADH_simple_molecule", "sign": true }, { "id": "t267", - "source": "NAD_simple_molecule", + "source": "Ribavirin_drug", "target": "NADH_simple_molecule", "sign": true }, { "id": "t268", - "source": "IMPDH2", + "source": "Mycophenolic acid_drug", "target": "NADH_simple_molecule", "sign": true }, { "id": "t269", - "source": "IMP_simple_molecule", + "source": "XDH", "target": "NADH_simple_molecule", "sign": true }, @@ -3427,49 +3427,49 @@ }, { "id": "t271", - "source": "L-Glutamine_simple_molecule", + "source": "PFAS", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t272", - "source": "NADSYN1", + "source": "Deamino-NAD_simple_molecule", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t273", - "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "source": "XMP_simple_molecule", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t274", - "source": "XMP_simple_molecule", + "source": "GMPS", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t275", - "source": "PPAT", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t276", - "source": "PFAS", + "source": "L-Glutamine_simple_molecule", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t277", - "source": "GMPS", + "source": "PPAT", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t278", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "NADSYN1", "target": "L-Glutamate_simple_molecule", "sign": true }, @@ -3487,37 +3487,37 @@ }, { "id": "t281", - "source": "Deamino-NAD_simple_molecule", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "target": "L-Glutamate_simple_molecule", "sign": true }, { "id": "t282", - "source": "ADK", + "source": "APRT", "target": "AMP_simple_molecule", "sign": true }, { "id": "t283", - "source": "NAD_simple_molecule", + "source": "PRPS1L1", "target": "AMP_simple_molecule", "sign": true }, { "id": "t284", - "source": "Adenosine_simple_molecule", + "source": "GMPS", "target": "AMP_simple_molecule", "sign": true }, { "id": "t285", - "source": "GMPS", + "source": "ADK", "target": "AMP_simple_molecule", "sign": true }, { "id": "t286", - "source": "APRT", + "source": "D-Ribose 5P_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, @@ -3529,31 +3529,31 @@ }, { "id": "t288", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "XMP_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t289", - "source": "PRPS2", + "source": "ENPP3", "target": "AMP_simple_molecule", "sign": true }, { "id": "t290", - "source": "Adenine_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t291", - "source": "D-Ribose 5P_simple_molecule", + "source": "Adenine_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t292", - "source": "PRPS1", + "source": "NAD_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, @@ -3571,19 +3571,19 @@ }, { "id": "t295", - "source": "ENPP3", + "source": "Adenosine_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t296", - "source": "XMP_simple_molecule", + "source": "PRPS1", "target": "AMP_simple_molecule", "sign": true }, { "id": "t297", - "source": "PRPS1L1", + "source": "PRPS2", "target": "AMP_simple_molecule", "sign": true }, @@ -3595,127 +3595,127 @@ }, { "id": "t299", - "source": "PNP", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t300", - "source": "GTP_simple_molecule", + "source": "ENTPD5", "target": "Pi_simple_molecule", "sign": true }, { "id": "t301", - "source": "GMP_simple_molecule", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t302", - "source": "ENTPD5", + "source": "IMP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t303", - "source": "NT5E", + "source": "Hypoxanthine_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t304", - "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "source": "NT5E", "target": "Pi_simple_molecule", "sign": true }, { "id": "t305", - "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", + "source": "CANT1", "target": "Pi_simple_molecule", "sign": true }, { "id": "t306", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t307", - "source": "L-Aspartate_simple_molecule", + "source": "ENTPD2", "target": "Pi_simple_molecule", "sign": true }, { "id": "t308", - "source": "Hypoxanthine_simple_molecule", + "source": "L-Aspartate_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t309", - "source": "AMP_simple_molecule", + "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t310", - "source": "CANT1", + "source": "XMP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t311", - "source": "L-Glutamine_simple_molecule", + "source": "AMP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t312", - "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "source": "Glycine_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t313", - "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "source": "Nicotinamide D-ribonucleotide_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t314", - "source": "PFAS", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t315", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "source": "L-Glutamine_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t316", - "source": "H2O_simple_molecule_cell", + "source": "GMP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t317", - "source": "ENTPD4", + "source": "GTP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t318", - "source": "ENTPD6", + "source": "NAPRT1", "target": "Pi_simple_molecule", "sign": true }, { "id": "t319", - "source": "NAPRT1", + "source": "NTPCR", "target": "Pi_simple_molecule", "sign": true }, @@ -3727,7 +3727,7 @@ }, { "id": "t321", - "source": "GART", + "source": "PAICS", "target": "Pi_simple_molecule", "sign": true }, @@ -3739,61 +3739,61 @@ }, { "id": "t323", - "source": "Nicotinamide D-ribonucleotide_simple_molecule", + "source": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t324", - "source": "PAICS", + "source": "PNP", "target": "Pi_simple_molecule", "sign": true }, { "id": "t325", - "source": "ENTPD2", + "source": "PFAS", "target": "Pi_simple_molecule", "sign": true }, { "id": "t326", - "source": "Glycine_simple_molecule", + "source": "ENTPD4", "target": "Pi_simple_molecule", "sign": true }, { "id": "t327", - "source": "XMP_simple_molecule", + "source": "GDP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t328", - "source": "GDP_simple_molecule", + "source": "ENTPD6", "target": "Pi_simple_molecule", "sign": true }, { "id": "t329", - "source": "IMP_simple_molecule", + "source": "GART", "target": "Pi_simple_molecule", "sign": true }, { "id": "t330", - "source": "NTPCR", + "source": "H2O_simple_molecule_cell", "target": "Pi_simple_molecule", "sign": true }, { "id": "t331", - "source": "CD38", + "source": "NADP_simple_molecule", "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", "sign": true }, { "id": "t332", - "source": "NADP_simple_molecule", + "source": "CD38", "target": "nicotinate-adenine dinucleotide phosphate_simple_molecule", "sign": true }, @@ -3805,19 +3805,19 @@ }, { "id": "t334", - "source": "D-Ribose 5P_simple_molecule", + "source": "PRPS1L1", "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "sign": true }, { "id": "t335", - "source": "PRPS1", + "source": "D-Ribose 5P_simple_molecule", "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "sign": true }, { "id": "t336", - "source": "PRPS1L1", + "source": "PRPS1", "target": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "sign": true }, @@ -3835,25 +3835,25 @@ }, { "id": "t339", - "source": "PNP", + "source": "Xanthosine_simple_molecule", "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t340", - "source": "Pi_simple_molecule", + "source": "Guanosine_simple_molecule", "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t341", - "source": "Inosine_simple_molecule", + "source": "Pi_simple_molecule", "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t342", - "source": "Xanthosine_simple_molecule", + "source": "Inosine_simple_molecule", "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", "sign": true }, @@ -3871,67 +3871,67 @@ }, { "id": "t345", - "source": "Guanosine_simple_molecule", + "source": "PNP", "target": "_alpha_-D-Ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t346", - "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "source": "H2O_simple_molecule_mitochondrion", "target": "Histone-L-lysine_simple_molecule", "sign": true }, { "id": "t347", - "source": "H2O_simple_molecule_mitochondrion", + "source": "SIRT5:Nsp14_complex", "target": "Histone-L-lysine_simple_molecule", "sign": true }, { "id": "t348", - "source": "NAD_simple_molecule", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", "target": "Histone-L-lysine_simple_molecule", "sign": true }, { "id": "t349", - "source": "SIRT5", + "source": "NAD_simple_molecule", "target": "Histone-L-lysine_simple_molecule", "sign": true }, { "id": "t350", - "source": "SIRT5:Nsp14_complex", + "source": "SIRT5", "target": "Histone-L-lysine_simple_molecule", "sign": true }, { "id": "t351", - "source": "Histone N6-acetyl-L-lysine_simple_molecule", + "source": "H2O_simple_molecule_mitochondrion", "target": "O-Acetyl-ADP-ribose_simple_molecule", "sign": true }, { "id": "t352", - "source": "H2O_simple_molecule_mitochondrion", + "source": "SIRT5:Nsp14_complex", "target": "O-Acetyl-ADP-ribose_simple_molecule", "sign": true }, { "id": "t353", - "source": "NAD_simple_molecule", + "source": "Histone N6-acetyl-L-lysine_simple_molecule", "target": "O-Acetyl-ADP-ribose_simple_molecule", "sign": true }, { "id": "t354", - "source": "SIRT5", + "source": "NAD_simple_molecule", "target": "O-Acetyl-ADP-ribose_simple_molecule", "sign": true }, { "id": "t355", - "source": "SIRT5:Nsp14_complex", + "source": "SIRT5", "target": "O-Acetyl-ADP-ribose_simple_molecule", "sign": true }, @@ -3955,85 +3955,85 @@ }, { "id": "t359", - "source": "Quinolinate_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "CO2_simple_molecule", "sign": true }, { "id": "t360", - "source": "QPRT", + "source": "H_simple_molecule", "target": "CO2_simple_molecule", "sign": true }, { "id": "t361", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "Quinolinate_simple_molecule", "target": "CO2_simple_molecule", "sign": true }, { "id": "t362", - "source": "H_simple_molecule", + "source": "QPRT", "target": "CO2_simple_molecule", "sign": true }, { "id": "t363", - "source": "PGM2", + "source": "_alpha_D-Ribose 1P_simple_molecule", "target": "D-Ribose 5P_simple_molecule", "sign": true }, { "id": "t364", - "source": "_alpha_D-Ribose 1P_simple_molecule", + "source": "PGM2", "target": "D-Ribose 5P_simple_molecule", "sign": true }, { "id": "t365", - "source": "L-Glutamine_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "5-phospho-beta-D-ribosylamine_simple_molecule", "sign": true }, { "id": "t366", - "source": "PPAT", + "source": "H2O_simple_molecule_cell", "target": "5-phospho-beta-D-ribosylamine_simple_molecule", "sign": true }, { "id": "t367", - "source": "H2O_simple_molecule_cell", + "source": "PPAT", "target": "5-phospho-beta-D-ribosylamine_simple_molecule", "sign": true }, { "id": "t368", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "L-Glutamine_simple_molecule", "target": "5-phospho-beta-D-ribosylamine_simple_molecule", "sign": true }, { "id": "t369", - "source": "5-phospho-beta-D-ribosylamine_simple_molecule", + "source": "Glycine_simple_molecule", "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "sign": true }, { "id": "t370", - "source": "Glycine_simple_molecule", + "source": "ATP_simple_molecule", "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "sign": true }, { "id": "t371", - "source": "ATP_simple_molecule", + "source": "GART", "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "sign": true }, { "id": "t372", - "source": "GART", + "source": "5-phospho-beta-D-ribosylamine_simple_molecule", "target": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "sign": true }, @@ -4045,13 +4045,13 @@ }, { "id": "t374", - "source": "10-Formyltetrahydrofolate_simple_molecule", + "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "sign": true }, { "id": "t375", - "source": "5-phospho-beta-D-ribosylglycinamide_simple_molecule", + "source": "10-Formyltetrahydrofolate_simple_molecule", "target": "5-phosphoribosyl-N-formylglycinamide_simple_molecule", "sign": true }, @@ -4069,43 +4069,43 @@ }, { "id": "t378", - "source": "ATIC", + "source": "10-Formyltetrahydrofolate_simple_molecule", "target": "Tetrahydrofolate_simple_molecule", "sign": true }, { "id": "t379", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "source": "ATIC", "target": "Tetrahydrofolate_simple_molecule", "sign": true }, { "id": "t380", - "source": "10-Formyltetrahydrofolate_simple_molecule", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", "target": "Tetrahydrofolate_simple_molecule", "sign": true }, { "id": "t381", - "source": "L-Glutamine_simple_molecule", + "source": "PFAS", "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "sign": true }, { "id": "t382", - "source": "PFAS", + "source": "L-Glutamine_simple_molecule", "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "sign": true }, { "id": "t383", - "source": "H2O_simple_molecule_cell", + "source": "ATP_simple_molecule", "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "sign": true }, { "id": "t384", - "source": "ATP_simple_molecule", + "source": "H2O_simple_molecule_cell", "target": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "sign": true }, @@ -4117,7 +4117,7 @@ }, { "id": "t386", - "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", + "source": "ATP_simple_molecule", "target": "Aminoimidazole ribotide_simple_molecule", "sign": true }, @@ -4129,19 +4129,19 @@ }, { "id": "t388", - "source": "ATP_simple_molecule", + "source": "2-(Formamido)-N1-(5'-phosphoribosyl)acetamidine_simple_molecule", "target": "Aminoimidazole ribotide_simple_molecule", "sign": true }, { "id": "t389", - "source": "CO2_simple_molecule", + "source": "Aminoimidazole ribotide_simple_molecule", "target": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "sign": true }, { "id": "t390", - "source": "Aminoimidazole ribotide_simple_molecule", + "source": "CO2_simple_molecule", "target": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "sign": true }, @@ -4153,121 +4153,121 @@ }, { "id": "t392", - "source": "L-Aspartate_simple_molecule", + "source": "ATP_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "sign": true }, { "id": "t393", - "source": "ATP_simple_molecule", + "source": "L-Aspartate_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "sign": true }, { "id": "t394", - "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", + "source": "PAICS", "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "sign": true }, { "id": "t395", - "source": "PAICS", + "source": "1-(5-Phospho-D-ribosyl)-5-amino-4-imidazolecarboxylate_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "sign": true }, { "id": "t396", - "source": "ADSL", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", "sign": true }, { "id": "t397", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "source": "ADSL", "target": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", "sign": true }, { "id": "t398", - "source": "ADSL", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", "target": "Fumarate_simple_molecule", "sign": true }, { "id": "t399", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-(N-succinocarboxamide)-imidazole_simple_molecule", + "source": "ADSL", "target": "Fumarate_simple_molecule", "sign": true }, { "id": "t400", - "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", + "source": "ATIC", "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", "sign": true }, { "id": "t401", - "source": "10-Formyltetrahydrofolate_simple_molecule", + "source": "1-(5'-Phosphoribosyl)-5-amino-4-imidazolecarboxamide_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", "sign": true }, { "id": "t402", - "source": "ATIC", + "source": "10-Formyltetrahydrofolate_simple_molecule", "target": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", "sign": true }, { "id": "t403", - "source": "Hypoxanthine_simple_molecule", + "source": "HPRT1", "target": "IMP_simple_molecule", "sign": true }, { "id": "t404", - "source": "AMP_simple_molecule", + "source": "H_simple_molecule", "target": "IMP_simple_molecule", "sign": true }, { "id": "t405", - "source": "H_simple_molecule", + "source": "AMP_simple_molecule", "target": "IMP_simple_molecule", "sign": true }, { "id": "t406", - "source": "AMPD1", + "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", "target": "IMP_simple_molecule", "sign": true }, { "id": "t407", - "source": "AMDP2", + "source": "Hypoxanthine_simple_molecule", "target": "IMP_simple_molecule", "sign": true }, { "id": "t408", - "source": "AMPD3", + "source": "AMPD1", "target": "IMP_simple_molecule", "sign": true }, { "id": "t409", - "source": "ATIC", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "IMP_simple_molecule", "sign": true }, { "id": "t410", - "source": "HPRT1", + "source": "AMPD3", "target": "IMP_simple_molecule", "sign": true }, { "id": "t411", - "source": "1-(5'-Phosphoribosyl)-5-formamido-4-imidazolecarboxamide_simple_molecule", + "source": "ATIC", "target": "IMP_simple_molecule", "sign": true }, @@ -4279,55 +4279,55 @@ }, { "id": "t413", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "AMDP2", "target": "IMP_simple_molecule", "sign": true }, { "id": "t414", - "source": "Mycophenolic acid_drug", + "source": "Merimepodib_drug", "target": "XMP_simple_molecule", "sign": true }, { "id": "t415", - "source": "IMPDH1", + "source": "IMP_simple_molecule", "target": "XMP_simple_molecule", "sign": true }, { "id": "t416", - "source": "Ribavirin_drug", + "source": "NAD_simple_molecule", "target": "XMP_simple_molecule", "sign": true }, { "id": "t417", - "source": "IMPDH2:Nsp14_complex", + "source": "IMPDH2", "target": "XMP_simple_molecule", "sign": true }, { "id": "t418", - "source": "Merimepodib_drug", + "source": "IMPDH1", "target": "XMP_simple_molecule", "sign": true }, { "id": "t419", - "source": "NAD_simple_molecule", + "source": "IMPDH2:Nsp14_complex", "target": "XMP_simple_molecule", "sign": true }, { "id": "t420", - "source": "IMPDH2", + "source": "Ribavirin_drug", "target": "XMP_simple_molecule", "sign": true }, { "id": "t421", - "source": "IMP_simple_molecule", + "source": "Mycophenolic acid_drug", "target": "XMP_simple_molecule", "sign": true }, @@ -4339,115 +4339,115 @@ }, { "id": "t423", - "source": "NADP_simple_molecule", + "source": "HPRT1", "target": "GMP_simple_molecule", "sign": true }, { "id": "t424", - "source": "ENTPD4", + "source": "ENTPD5", "target": "GMP_simple_molecule", "sign": true }, { "id": "t425", - "source": "GTP_simple_molecule", + "source": "IMP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t426", - "source": "ENTPD6", + "source": "GMPS", "target": "GMP_simple_molecule", "sign": true }, { "id": "t427", - "source": "Guanine_simple_molecule", + "source": "NADP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t428", - "source": "ENTPD5", + "source": "Ammonium_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t429", - "source": "Ammonium_simple_molecule", + "source": "CANT1", "target": "GMP_simple_molecule", "sign": true }, { "id": "t430", - "source": "HPRT1", + "source": "GMPR2", "target": "GMP_simple_molecule", "sign": true }, { "id": "t431", - "source": "GMPS", + "source": "ATP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t432", - "source": "ATP_simple_molecule", + "source": "Guanine_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t433", - "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", + "source": "ENTPD2", "target": "GMP_simple_molecule", "sign": true }, { "id": "t434", - "source": "CANT1", + "source": "ENTPD4", "target": "GMP_simple_molecule", "sign": true }, { "id": "t435", - "source": "L-Glutamine_simple_molecule", + "source": "GDP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t436", - "source": "GMPR2", + "source": "XMP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t437", - "source": "ENTPD2", + "source": "ENTPD6", "target": "GMP_simple_molecule", "sign": true }, { "id": "t438", - "source": "XMP_simple_molecule", + "source": "5-phospho-_alpha_-D-ribose 1-diphosphate_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t439", - "source": "GMPR", + "source": "L-Glutamine_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t440", - "source": "GDP_simple_molecule", + "source": "GTP_simple_molecule", "target": "GMP_simple_molecule", "sign": true }, { "id": "t441", - "source": "IMP_simple_molecule", + "source": "GMPR", "target": "GMP_simple_molecule", "sign": true }, @@ -4459,49 +4459,49 @@ }, { "id": "t443", - "source": "GTP_simple_molecule", + "source": "ENTPD2", "target": "GDP_simple_molecule", "sign": true }, { "id": "t444", - "source": "GMP_simple_molecule", + "source": "NTPCR", "target": "GDP_simple_molecule", "sign": true }, { "id": "t445", - "source": "ENTPD2", + "source": "GTP_simple_molecule", "target": "GDP_simple_molecule", "sign": true }, { "id": "t446", - "source": "GUK1", + "source": "GMP_simple_molecule", "target": "GDP_simple_molecule", "sign": true }, { "id": "t447", - "source": "H2O_simple_molecule_cell", + "source": "ATP_simple_molecule", "target": "GDP_simple_molecule", "sign": true }, { "id": "t448", - "source": "ATP_simple_molecule", + "source": "GUK1", "target": "GDP_simple_molecule", "sign": true }, { "id": "t449", - "source": "NTPCR", + "source": "H2O_simple_molecule_cell", "target": "GDP_simple_molecule", "sign": true }, { "id": "t450", - "source": "NME6", + "source": "GDP_simple_molecule", "target": "GTP_simple_molecule", "sign": true }, @@ -4513,31 +4513,31 @@ }, { "id": "t452", - "source": "Nucleoside diphosphate kinase_complex_cell", + "source": "NME7", "target": "GTP_simple_molecule", "sign": true }, { "id": "t453", - "source": "NME7", + "source": "NME3", "target": "GTP_simple_molecule", "sign": true }, { "id": "t454", - "source": "NME3", + "source": "Nucleoside diphosphate kinase_complex_cell", "target": "GTP_simple_molecule", "sign": true }, { "id": "t455", - "source": "GDP_simple_molecule", + "source": "ATP_simple_molecule", "target": "GTP_simple_molecule", "sign": true }, { "id": "t456", - "source": "ATP_simple_molecule", + "source": "NME6", "target": "GTP_simple_molecule", "sign": true }, @@ -4549,31 +4549,31 @@ }, { "id": "t458", - "source": "GUK1", + "source": "ribonucleoside reductase_complex_cell", "target": "dGDP_simple_molecule", "sign": true }, { "id": "t459", - "source": "dGMP_simple_molecule", + "source": "ATP_simple_molecule", "target": "dGDP_simple_molecule", "sign": true }, { "id": "t460", - "source": "ribonucleoside reductase_complex_cell", + "source": "Thioredoxin_simple_molecule", "target": "dGDP_simple_molecule", "sign": true }, { "id": "t461", - "source": "ATP_simple_molecule", + "source": "GUK1", "target": "dGDP_simple_molecule", "sign": true }, { "id": "t462", - "source": "Thioredoxin_simple_molecule", + "source": "dGMP_simple_molecule", "target": "dGDP_simple_molecule", "sign": true }, @@ -4585,7 +4585,7 @@ }, { "id": "t464", - "source": "ribonucleoside reductase_complex_cell", + "source": "ADP_simple_molecule", "target": "Thioredoxin disulfide_simple_molecule", "sign": true }, @@ -4597,49 +4597,49 @@ }, { "id": "t466", - "source": "ADP_simple_molecule", + "source": "ribonucleoside reductase_complex_cell", "target": "Thioredoxin disulfide_simple_molecule", "sign": true }, { "id": "t467", - "source": "NME6", + "source": "NME5", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t468", - "source": "NME5", + "source": "NME7", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t469", - "source": "Nucleoside diphosphate kinase_complex_cell", + "source": "NME3", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t470", - "source": "NME7", + "source": "Nucleoside diphosphate kinase_complex_cell", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t471", - "source": "dGDP_simple_molecule", + "source": "ATP_simple_molecule", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t472", - "source": "NME3", + "source": "dGDP_simple_molecule", "target": "dGTP_simple_molecule", "sign": true }, { "id": "t473", - "source": "ATP_simple_molecule", + "source": "NME6", "target": "dGTP_simple_molecule", "sign": true }, @@ -4651,49 +4651,49 @@ }, { "id": "t475", - "source": "Deoxyguanosine_simple_molecule", + "source": "ITPA", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t476", - "source": "ENPP1", + "source": "ENPP3", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t477", - "source": "ENPP3", + "source": "Deoxyguanosine_simple_molecule", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t478", - "source": "dGTP_simple_molecule", + "source": "ENPP1", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t479", - "source": "ATP_simple_molecule", + "source": "dGTP_simple_molecule", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t480", - "source": "H2O_simple_molecule_cell", + "source": "ATP_simple_molecule", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t481", - "source": "ITPA", + "source": "H2O_simple_molecule_cell", "target": "dGMP_simple_molecule", "sign": true }, { "id": "t482", - "source": "PNP", + "source": "Guanosine_simple_molecule", "target": "Guanine_simple_molecule", "sign": true }, @@ -4711,7 +4711,7 @@ }, { "id": "t485", - "source": "Guanosine_simple_molecule", + "source": "PNP", "target": "Guanine_simple_molecule", "sign": true }, @@ -4735,31 +4735,31 @@ }, { "id": "t489", - "source": "PNP", + "source": "Deoxyguanosine_simple_molecule", "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t490", - "source": "Deoxyguanosine_simple_molecule", + "source": "Pi_simple_molecule", "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t491", - "source": "Pi_simple_molecule", + "source": "PNP", "target": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", "sign": true }, { "id": "t492", - "source": "AMP_simple_molecule", + "source": "Guanine_simple_molecule", "target": "Ammonium_simple_molecule", "sign": true }, { "id": "t493", - "source": "AMPD1", + "source": "GDA", "target": "Ammonium_simple_molecule", "sign": true }, @@ -4771,19 +4771,19 @@ }, { "id": "t495", - "source": "Guanine_simple_molecule", + "source": "AMP_simple_molecule", "target": "Ammonium_simple_molecule", "sign": true }, { "id": "t496", - "source": "AMDP2", + "source": "H2O_simple_molecule_cell", "target": "Ammonium_simple_molecule", "sign": true }, { "id": "t497", - "source": "AMPD3", + "source": "AMPD1", "target": "Ammonium_simple_molecule", "sign": true }, @@ -4795,19 +4795,19 @@ }, { "id": "t499", - "source": "GDA", + "source": "Adenosine_simple_molecule", "target": "Ammonium_simple_molecule", "sign": true }, { "id": "t500", - "source": "Adenosine_simple_molecule", + "source": "AMPD3", "target": "Ammonium_simple_molecule", "sign": true }, { "id": "t501", - "source": "H2O_simple_molecule_cell", + "source": "AMDP2", "target": "Ammonium_simple_molecule", "sign": true }, @@ -4837,61 +4837,61 @@ }, { "id": "t506", - "source": "PNP", + "source": "Xanthosine_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t507", - "source": "Hypoxanthine_simple_molecule", + "source": "Guanine_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t508", - "source": "Pi_simple_molecule", + "source": "GDA", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t509", - "source": "XDH", + "source": "H_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t510", - "source": "H_simple_molecule", + "source": "Hypoxanthine_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t511", - "source": "Guanine_simple_molecule", + "source": "Pi_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t512", - "source": "Xanthosine_simple_molecule", + "source": "NAD_simple_molecule", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t513", - "source": "NAD_simple_molecule", + "source": "XDH", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t514", - "source": "GDA", + "source": "H2O_simple_molecule_cell", "target": "Xanthine_simple_molecule", "sign": true }, { "id": "t515", - "source": "H2O_simple_molecule_cell", + "source": "PNP", "target": "Xanthine_simple_molecule", "sign": true }, @@ -4903,19 +4903,19 @@ }, { "id": "t517", - "source": "NT5E", + "source": "IMP_simple_molecule", "target": "Inosine_simple_molecule", "sign": true }, { "id": "t518", - "source": "Adenosine_simple_molecule", + "source": "NT5E", "target": "Inosine_simple_molecule", "sign": true }, { "id": "t519", - "source": "IMP_simple_molecule", + "source": "Adenosine_simple_molecule", "target": "Inosine_simple_molecule", "sign": true }, @@ -4933,7 +4933,7 @@ }, { "id": "t522", - "source": "PNP", + "source": "Inosine_simple_molecule", "target": "Hypoxanthine_simple_molecule", "sign": true }, @@ -4945,19 +4945,19 @@ }, { "id": "t524", - "source": "Inosine_simple_molecule", + "source": "PNP", "target": "Hypoxanthine_simple_molecule", "sign": true }, { "id": "t525", - "source": "H2O_simple_molecule_cell", + "source": "AMP_simple_molecule", "target": "Adenosine_simple_molecule", "sign": true }, { "id": "t526", - "source": "AMP_simple_molecule", + "source": "H2O_simple_molecule_cell", "target": "Adenosine_simple_molecule", "sign": true }, @@ -4969,7 +4969,7 @@ }, { "id": "t528", - "source": "PNP", + "source": "Adenosine_simple_molecule", "target": "Adenine_simple_molecule", "sign": true }, @@ -4981,55 +4981,55 @@ }, { "id": "t530", - "source": "Adenosine_simple_molecule", + "source": "PNP", "target": "Adenine_simple_molecule", "sign": true }, { "id": "t531", - "source": "Hypoxanthine_simple_molecule", + "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t532", - "source": "PNP", + "source": "H_simple_molecule", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t533", - "source": "H_simple_molecule", + "source": "Hypoxanthine_simple_molecule", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t534", - "source": "2-deoxy-_alpha_-D-ribose 1-phosphate_simple_molecule", + "source": "Deoxyadenosine_simple_molecule", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t535", - "source": "Deoxyadenosine_simple_molecule", + "source": "H2O_simple_molecule_cell", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t536", - "source": "H2O_simple_molecule_cell", + "source": "ADA", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t537", - "source": "ADA", + "source": "PNP", "target": "Deoxyinosine_simple_molecule", "sign": true }, { "id": "t538", - "source": "Deoxyadenosine_simple_molecule", + "source": "ATP_simple_molecule", "target": "dAMP_simple_molecule", "sign": true }, @@ -5041,13 +5041,13 @@ }, { "id": "t540", - "source": "ATP_simple_molecule", + "source": "Deoxyadenosine_simple_molecule", "target": "dAMP_simple_molecule", "sign": true }, { "id": "t541", - "source": "ribonucleoside reductase_complex_cell", + "source": "dAMP_simple_molecule", "target": "dADP_simple_molecule", "sign": true }, @@ -5059,67 +5059,67 @@ }, { "id": "t543", - "source": "ATP_simple_molecule", + "source": "ADP_simple_molecule", "target": "dADP_simple_molecule", "sign": true }, { "id": "t544", - "source": "Thioredoxin_simple_molecule", + "source": "ribonucleoside reductase_complex_cell", "target": "dADP_simple_molecule", "sign": true }, { "id": "t545", - "source": "dAMP_simple_molecule", + "source": "ATP_simple_molecule", "target": "dADP_simple_molecule", "sign": true }, { "id": "t546", - "source": "ADP_simple_molecule", + "source": "Thioredoxin_simple_molecule", "target": "dADP_simple_molecule", "sign": true }, { "id": "t547", - "source": "dADP_simple_molecule", + "source": "NME5", "target": "dATP_simple_molecule", "sign": true }, { "id": "t548", - "source": "NME6", + "source": "dADP_simple_molecule", "target": "dATP_simple_molecule", "sign": true }, { "id": "t549", - "source": "NME5", + "source": "NME7", "target": "dATP_simple_molecule", "sign": true }, { "id": "t550", - "source": "Nucleoside diphosphate kinase_complex_cell", + "source": "NME3", "target": "dATP_simple_molecule", "sign": true }, { "id": "t551", - "source": "NME7", + "source": "Nucleoside diphosphate kinase_complex_cell", "target": "dATP_simple_molecule", "sign": true }, { "id": "t552", - "source": "NME3", + "source": "ATP_simple_molecule", "target": "dATP_simple_molecule", "sign": true }, { "id": "t553", - "source": "ATP_simple_molecule", + "source": "NME6", "target": "dATP_simple_molecule", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json index be960294e..a3c212243 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp4_Nsp6.json @@ -712,13 +712,13 @@ }, { "id": "t4", - "source": "Nsp4_cell", + "source": "ALG11_endoplasmic reticulum", "target": "Nsp4_ALG11_complex_endoplasmic reticulum", "sign": true }, { "id": "t5", - "source": "ALG11_endoplasmic reticulum", + "source": "Nsp4_cell", "target": "Nsp4_ALG11_complex_endoplasmic reticulum", "sign": true }, @@ -730,25 +730,25 @@ }, { "id": "t7", - "source": "DNAJC11", + "source": "Nsp4_cell", "target": "Nsp4:DNAJC11_complex", "sign": true }, { "id": "t8", - "source": "Nsp4_cell", + "source": "DNAJC11", "target": "Nsp4:DNAJC11_complex", "sign": true }, { "id": "t9", - "source": "F-ATPase_complex_mitochondrial matrix", + "source": "Nsp6", "target": "F-ATPase:Nsp6_complex", "sign": true }, { "id": "t10", - "source": "Nsp6", + "source": "F-ATPase_complex_mitochondrial matrix", "target": "F-ATPase:Nsp6_complex", "sign": true }, @@ -760,13 +760,13 @@ }, { "id": "t12", - "source": "Nsp4_cell", + "source": "NUP210_endoplasmic reticulum", "target": "Nsp4:NUP210_complex_endoplasmic reticulum", "sign": true }, { "id": "t13", - "source": "NUP210_endoplasmic reticulum", + "source": "Nsp4_cell", "target": "Nsp4:NUP210_complex_endoplasmic reticulum", "sign": true }, @@ -856,13 +856,13 @@ }, { "id": "t28", - "source": "P-ATPase_complex_cell", + "source": "Nsp6", "target": "P-ATPase:Nsp6_complex", "sign": true }, { "id": "t29", - "source": "Nsp6", + "source": "P-ATPase_complex_cell", "target": "P-ATPase:Nsp6_complex", "sign": true }, @@ -1018,13 +1018,13 @@ }, { "id": "t55", - "source": "TOM complex_complex", + "source": "Nsp4_cell", "target": "Nsp4_mitochondrion", "sign": true }, { "id": "t56", - "source": "Nsp4_cell", + "source": "TOM complex_complex", "target": "Nsp4_mitochondrion", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json index 60e27a51c..b59365516 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Nsp9_protein.json @@ -2518,13 +2518,13 @@ "edges": [ { "id": "t1", - "source": "Nsp9_cell", + "source": "Fibrillin_complex_human host", "target": "Fibrillincomp_complex", "sign": true }, { "id": "t2", - "source": "Fibrillin_complex_human host", + "source": "Nsp9_cell", "target": "Fibrillincomp_complex", "sign": true }, @@ -2554,25 +2554,25 @@ }, { "id": "t7", - "source": "MIB1", + "source": "DLL1", "target": "MIBcomp_complex", "sign": true }, { "id": "t8", - "source": "DLL1", + "source": "MIB1", "target": "MIBcomp_complex", "sign": true }, { "id": "t9", - "source": "Vpr", + "source": "COPS_complex_nucleus", "target": "COPS_complex_nucleus", "sign": true }, { "id": "t10", - "source": "COPS_complex_nucleus", + "source": "Vpr", "target": "COPS_complex_nucleus", "sign": true }, @@ -2590,55 +2590,55 @@ }, { "id": "t13", - "source": "S-Adenosylmethionine_drug", + "source": "MAT1A", "target": "SAdComp_complex", "sign": true }, { "id": "t14", - "source": "MAT1A", + "source": "S-Adenosylmethionine_drug", "target": "SAdComp_complex", "sign": true }, { "id": "t15", - "source": "nup1_complex", + "source": "nup2_complex", "target": "Nuclear Pore_complex", "sign": true }, { "id": "t16", - "source": "nup2_complex", + "source": "nup1_complex", "target": "Nuclear Pore_complex", "sign": true }, { "id": "t17", - "source": "EXOSC2", + "source": "EXOSC5", "target": "EXOCcomp_complex", "sign": true }, { "id": "t18", - "source": "Nsp8", + "source": "EXOSC8", "target": "EXOCcomp_complex", "sign": true }, { "id": "t19", - "source": "EXOSC5", + "source": "EXOSC3", "target": "EXOCcomp_complex", "sign": true }, { "id": "t20", - "source": "EXOSC3", + "source": "Nsp8", "target": "EXOCcomp_complex", "sign": true }, { "id": "t21", - "source": "EXOSC8", + "source": "EXOSC2", "target": "EXOCcomp_complex", "sign": true }, @@ -2686,55 +2686,55 @@ }, { "id": "t29", - "source": "Nsp9_nucleus", + "source": "ZNF503", "target": "znfcomp_complex", "sign": true }, { "id": "t30", - "source": "ZNF503", + "source": "Nsp9_nucleus", "target": "znfcomp_complex", "sign": true }, { "id": "t31", - "source": "Nsp8", + "source": "Nsp7", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t32", - "source": "Nsp7", + "source": "Nsp12", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t33", - "source": "Nsp12", + "source": "Nsp8", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t34", - "source": "Nsp7812_complex_cell", + "source": "remdesivir _drug", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t35", - "source": "remdesivir _drug", + "source": "favipiravir_drug", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t36", - "source": "RdRpassembled_rna", + "source": "Nsp7812_complex_cell", "target": "Nsp7812_complex_cell", "sign": true }, { "id": "t37", - "source": "favipiravir_drug", + "source": "RdRpassembled_rna", "target": "Nsp7812_complex_cell", "sign": true }, @@ -2746,13 +2746,13 @@ }, { "id": "t39", - "source": "NUP58", + "source": "NUP54", "target": "nup1_complex", "sign": true }, { "id": "t40", - "source": "NUP54", + "source": "NUP58", "target": "nup1_complex", "sign": true }, @@ -2770,13 +2770,13 @@ }, { "id": "t43", - "source": "EDN1-homo_complex_nucleus", + "source": "BAG6", "target": "EDN1-homo_complex_nucleus", "sign": true }, { "id": "t44", - "source": "BAG6", + "source": "EDN1-homo_complex_nucleus", "target": "EDN1-homo_complex_nucleus", "sign": true }, @@ -2788,49 +2788,49 @@ }, { "id": "t46", - "source": "NEK7", + "source": "NEK9", "target": "NEKs_complex", "sign": true }, { "id": "t47", - "source": "NEK9", + "source": "NEK7", "target": "NEKs_complex", "sign": true }, { "id": "t48", - "source": "POLR2E", + "source": "POLR2A", "target": "gtfrnapoly_complex", "sign": true }, { "id": "t49", - "source": "POLR2B", + "source": "POLR2G", "target": "gtfrnapoly_complex", "sign": true }, { "id": "t50", - "source": "POLR2A", + "source": "GTF2F2", "target": "gtfrnapoly_complex", "sign": true }, { "id": "t51", - "source": "GTF2F2", + "source": "POLR2E", "target": "gtfrnapoly_complex", "sign": true }, { "id": "t52", - "source": "GTF2B", + "source": "POLR2B", "target": "gtfrnapoly_complex", "sign": true }, { "id": "t53", - "source": "POLR2G", + "source": "GTF2B", "target": "gtfrnapoly_complex", "sign": true }, @@ -2860,25 +2860,25 @@ }, { "id": "t58", - "source": "COPS5", + "source": "COPS6", "target": "COPS_complex_nucleus", "sign": true }, { "id": "t59", - "source": "COPS4", + "source": "COPS2", "target": "COPS_complex_nucleus", "sign": true }, { "id": "t60", - "source": "COPS8", + "source": "COPS4", "target": "COPS_complex_nucleus", "sign": true }, { "id": "t61", - "source": "COPS2", + "source": "COPS5", "target": "COPS_complex_nucleus", "sign": true }, @@ -2890,7 +2890,7 @@ }, { "id": "t63", - "source": "COPS6", + "source": "COPS8", "target": "COPS_complex_nucleus", "sign": true }, @@ -2926,13 +2926,13 @@ }, { "id": "t69", - "source": "TAT", + "source": "GTF2F2", "target": "TAT-HIV_complex", "sign": true }, { "id": "t70", - "source": "GTF2F2", + "source": "TAT", "target": "TAT-HIV_complex", "sign": true }, @@ -2950,13 +2950,13 @@ }, { "id": "t73", - "source": "AIFM1", + "source": "SPART", "target": "SPARTcomp_complex", "sign": true }, { "id": "t74", - "source": "SPART", + "source": "AIFM1", "target": "SPARTcomp_complex", "sign": true }, @@ -2974,13 +2974,13 @@ }, { "id": "t77", - "source": "Nsp10_cell", + "source": "Nsp9_cell", "target": "pathogen_complex", "sign": true }, { "id": "t78", - "source": "Nsp9_cell", + "source": "Nsp10_cell", "target": "pathogen_complex", "sign": true }, @@ -3004,7 +3004,7 @@ }, { "id": "t82", - "source": "FOCAD", + "source": "Nsp7", "target": "FOCADcomp_complex", "sign": true }, @@ -3016,7 +3016,7 @@ }, { "id": "t84", - "source": "Nsp7", + "source": "FOCAD", "target": "FOCADcomp_complex", "sign": true }, @@ -3070,13 +3070,13 @@ }, { "id": "t93", - "source": "Rofecoxib_drug", + "source": "PTGS2", "target": "PTGScomp_complex", "sign": true }, { "id": "t94", - "source": "PTGS2", + "source": "Rofecoxib_drug", "target": "PTGScomp_complex", "sign": true }, @@ -3100,13 +3100,13 @@ }, { "id": "t98", - "source": "MAT2A", + "source": "MAT2B", "target": "MAT_complex", "sign": true }, { "id": "t99", - "source": "MAT2B", + "source": "MAT2A", "target": "MAT_complex", "sign": true }, @@ -3124,25 +3124,25 @@ }, { "id": "t102", - "source": "Flavin adenine dinucleotide_drug", + "source": "AIFM1", "target": "AIFMFlaComp_complex", "sign": true }, { "id": "t103", - "source": "AIFM1", + "source": "Flavin adenine dinucleotide_drug", "target": "AIFMFlaComp_complex", "sign": true }, { "id": "t104", - "source": "Sitaxentan_drug", + "source": "EDNRA", "target": "EDNRASitaComp_complex", "sign": true }, { "id": "t105", - "source": "EDNRA", + "source": "Sitaxentan_drug", "target": "EDNRASitaComp_complex", "sign": true }, @@ -3160,25 +3160,25 @@ }, { "id": "t108", - "source": "EDNRA", + "source": "Acetylsalicylic acid_drug", "target": "EDNRAcetComp_complex", "sign": true }, { "id": "t109", - "source": "Acetylsalicylic acid_drug", + "source": "EDNRA", "target": "EDNRAcetComp_complex", "sign": true }, { "id": "t110", - "source": "Macitentan_drug", + "source": "EDNRA", "target": "EDNRMacComp_complex", "sign": true }, { "id": "t111", - "source": "EDNRA", + "source": "Macitentan_drug", "target": "EDNRMacComp_complex", "sign": true }, @@ -3196,25 +3196,25 @@ }, { "id": "t114", - "source": "MYCBP2", + "source": "Nsp12", "target": "MYCBPcomp_complex", "sign": true }, { "id": "t115", - "source": "Nsp12", + "source": "MYCBP2", "target": "MYCBPcomp_complex", "sign": true }, { "id": "t116", - "source": "SBNO1", + "source": "Nsp12", "target": "SBNOcomp_complex", "sign": true }, { "id": "t117", - "source": "Nsp12", + "source": "SBNO1", "target": "SBNOcomp_complex", "sign": true }, @@ -3232,25 +3232,25 @@ }, { "id": "t120", - "source": "ADP_simple_molecule", + "source": "BCKDK", "target": "ADPcomp_complex", "sign": true }, { "id": "t121", - "source": "BCKDK", + "source": "ADP_simple_molecule", "target": "ADPcomp_complex", "sign": true }, { "id": "t122", - "source": "DCAF7", + "source": "ZNF503", "target": "dcafznf_complex", "sign": true }, { "id": "t123", - "source": "ZNF503", + "source": "DCAF7", "target": "dcafznf_complex", "sign": true }, @@ -3268,13 +3268,13 @@ }, { "id": "t126", - "source": "ZNF318", + "source": "Nsp12", "target": "ZNFcomp_complex", "sign": true }, { "id": "t127", - "source": "Nsp12", + "source": "ZNF318", "target": "ZNFcomp_complex", "sign": true }, @@ -3292,13 +3292,13 @@ }, { "id": "t130", - "source": "SRP54", + "source": "Nsp8", "target": "SRP54comp_complex", "sign": true }, { "id": "t131", - "source": "Nsp8", + "source": "SRP54", "target": "SRP54comp_complex", "sign": true }, @@ -3310,13 +3310,13 @@ }, { "id": "t133", - "source": "ZC3H7A ", + "source": "Nsp12", "target": "ZC3H7Acomp_complex", "sign": true }, { "id": "t134", - "source": "Nsp12", + "source": "ZC3H7A ", "target": "ZC3H7Acomp_complex", "sign": true }, @@ -3346,37 +3346,37 @@ }, { "id": "t139", - "source": "CA12", + "source": "Nsp7", "target": "CA12comp_complex", "sign": true }, { "id": "t140", - "source": "Nsp7", + "source": "CA12", "target": "CA12comp_complex", "sign": true }, { "id": "t141", - "source": "CA12", + "source": "Zonisamide_drug", "target": "ZonisamideComp_complex", "sign": true }, { "id": "t142", - "source": "Zonisamide_drug", + "source": "CA12", "target": "ZonisamideComp_complex", "sign": true }, { "id": "t143", - "source": "Ellagic Acid_drug", + "source": "CA12", "target": "EAcomp_complex", "sign": true }, { "id": "t144", - "source": "CA12", + "source": "Ellagic Acid_drug", "target": "EAcomp_complex", "sign": true }, @@ -3394,13 +3394,13 @@ }, { "id": "t147", - "source": "CA12", + "source": "Benzthiazide_drug", "target": "BZcomp_complex", "sign": true }, { "id": "t148", - "source": "Benzthiazide_drug", + "source": "CA12", "target": "BZcomp_complex", "sign": true }, @@ -3418,31 +3418,31 @@ }, { "id": "t151", - "source": "ELN", + "source": "PLG", "target": "Fibrillin_complex_human host", "sign": true }, { "id": "t152", - "source": "Fibrillin_complex_human host", + "source": "ELN", "target": "Fibrillin_complex_human host", "sign": true }, { "id": "t153", - "source": "PLG", + "source": "Fibrillin_complex_human host", "target": "Fibrillin_complex_human host", "sign": true }, { "id": "t154", - "source": "ELN", + "source": "Rofecoxib_drug", "target": "RofecoxibComp_complex", "sign": true }, { "id": "t155", - "source": "Rofecoxib_drug", + "source": "ELN", "target": "RofecoxibComp_complex", "sign": true }, @@ -3460,13 +3460,13 @@ }, { "id": "t158", - "source": "ENV", + "source": "PCSK1", "target": "NECENVComp_complex", "sign": true }, { "id": "t159", - "source": "PCSK1", + "source": "ENV", "target": "NECENVComp_complex", "sign": true }, @@ -3508,13 +3508,13 @@ }, { "id": "t166", - "source": "COMT", + "source": "Nsp7", "target": "COMT_complex", "sign": true }, { "id": "t167", - "source": "Nsp7", + "source": "COMT", "target": "COMT_complex", "sign": true }, @@ -3568,13 +3568,13 @@ }, { "id": "t176", - "source": "3,5-Dinitrocatechol_drug", + "source": "COMT", "target": "DCcomp_complex", "sign": true }, { "id": "t177", - "source": "COMT", + "source": "3,5-Dinitrocatechol_drug", "target": "DCcomp_complex", "sign": true }, @@ -3592,25 +3592,25 @@ }, { "id": "t180", - "source": "(3,4-DIHYDROXY-2-NITROPHENYL)(PHENYL)METHANONE_drug", + "source": "COMT", "target": "DNCcomp_complex", "sign": true }, { "id": "t181", - "source": "COMT", + "source": "(3,4-DIHYDROXY-2-NITROPHENYL)(PHENYL)METHANONE_drug", "target": "DNCcomp_complex", "sign": true }, { "id": "t182", - "source": "COMT", + "source": "2-Methoxyestradiol_drug", "target": "MCcomp_complex", "sign": true }, { "id": "t183", - "source": "2-Methoxyestradiol_drug", + "source": "COMT", "target": "MCcomp_complex", "sign": true }, @@ -3628,37 +3628,37 @@ }, { "id": "t186", - "source": "GDP_simple_molecule", + "source": "RAB7A", "target": "RGcomp_complex_cell", "sign": true }, { "id": "t187", - "source": "RAB7A", + "source": "GDP_simple_molecule", "target": "RGcomp_complex_cell", "sign": true }, { "id": "t188", - "source": "Suramin_drug", + "source": "SIRT5", "target": "SScomp_complex", "sign": true }, { "id": "t189", - "source": "SIRT5", + "source": "Suramin_drug", "target": "SScomp_complex", "sign": true }, { "id": "t190", - "source": "GDP_simple_molecule", + "source": "RHOA", "target": "RGcomp_complex_cell", "sign": true }, { "id": "t191", - "source": "RHOA", + "source": "GDP_simple_molecule", "target": "RGcomp_complex_cell", "sign": true }, @@ -3712,7 +3712,7 @@ }, { "id": "t200", - "source": "MRPS5", + "source": "Nsp8", "target": "MRPScomp_complex", "sign": true }, @@ -3724,25 +3724,25 @@ }, { "id": "t202", - "source": "Nsp8", + "source": "MRPS5", "target": "MRPScomp_complex", "sign": true }, { "id": "t203", - "source": "IMPDH2", + "source": "Ribavirin_drug", "target": "IRcomp_complex", "sign": true }, { "id": "t204", - "source": "Ribavirin_drug", + "source": "IMPDH2", "target": "IRcomp_complex", "sign": true }, { "id": "t205", - "source": "LOXL1", + "source": "FBLN5", "target": "LOXcomp_complex", "sign": true }, @@ -3754,7 +3754,7 @@ }, { "id": "t207", - "source": "FBLN5", + "source": "LOXL1", "target": "LOXcomp_complex", "sign": true }, @@ -3784,25 +3784,25 @@ }, { "id": "t212", - "source": "SRP72", + "source": "Nsp7", "target": "SRP72comp_complex", "sign": true }, { "id": "t213", - "source": "Nsp7", + "source": "SRP72", "target": "SRP72comp_complex", "sign": true }, { "id": "t214", - "source": "NARS2", + "source": "L-Asparagine_simple_molecule", "target": "NLcomp_complex", "sign": true }, { "id": "t215", - "source": "L-Asparagine_simple_molecule", + "source": "NARS2", "target": "NLcomp_complex", "sign": true }, @@ -3820,25 +3820,25 @@ }, { "id": "t218", - "source": "Nsp8", + "source": "AATF", "target": "AATFcomp_complex", "sign": true }, { "id": "t219", - "source": "AATF", + "source": "Nsp8", "target": "AATFcomp_complex", "sign": true }, { "id": "t220", - "source": "IMPDH2", + "source": "Nsp14_nucleus", "target": "INPDH2comp_complex", "sign": true }, { "id": "t221", - "source": "Nsp14_nucleus", + "source": "IMPDH2", "target": "INPDH2comp_complex", "sign": true }, @@ -3856,25 +3856,25 @@ }, { "id": "t224", - "source": "TCF12", + "source": "Nsp12", "target": "TCFcomp_complex", "sign": true }, { "id": "t225", - "source": "Nsp12", + "source": "TCF12", "target": "TCFcomp_complex", "sign": true }, { "id": "t226", - "source": "Nsp10_nucleus", + "source": "ERGIC1", "target": "ERGIC1comp_complex", "sign": true }, { "id": "t227", - "source": "ERGIC1", + "source": "Nsp10_nucleus", "target": "ERGIC1comp_complex", "sign": true }, @@ -3892,13 +3892,13 @@ }, { "id": "t230", - "source": "GFER", + "source": "FAD_simple_molecule", "target": "FGCOMP_complex", "sign": true }, { "id": "t231", - "source": "FAD_simple_molecule", + "source": "GFER", "target": "FGCOMP_complex", "sign": true }, @@ -3928,25 +3928,25 @@ }, { "id": "t236", - "source": "Nsp8", + "source": "NGDN", "target": "NGDNcomp_complex", "sign": true }, { "id": "t237", - "source": "NGDN", + "source": "Nsp8", "target": "NGDNcomp_complex", "sign": true }, { "id": "t238", - "source": "CCDC86", + "source": "Nsp8", "target": "CCDCcomp_complex", "sign": true }, { "id": "t239", - "source": "Nsp8", + "source": "CCDC86", "target": "CCDCcomp_complex", "sign": true }, @@ -3976,37 +3976,37 @@ }, { "id": "t244", - "source": "NARS2", + "source": "Nsp8", "target": "NARS2comp_complex", "sign": true }, { "id": "t245", - "source": "Nsp8", + "source": "NARS2", "target": "NARS2comp_complex", "sign": true }, { "id": "t246", - "source": "ZNF250", + "source": "Nsp14_nucleus", "target": "ZNF250comp_complex", "sign": true }, { "id": "t247", - "source": "Nsp14_nucleus", + "source": "ZNF250", "target": "ZNF250comp_complex", "sign": true }, { "id": "t248", - "source": "Nsp14_cell", + "source": "PEG10", "target": "PEG10comp_complex", "sign": true }, { "id": "t249", - "source": "PEG10", + "source": "Nsp14_cell", "target": "PEG10comp_complex", "sign": true }, @@ -4042,13 +4042,13 @@ }, { "id": "t255", - "source": "PLAT", + "source": "Nafamostat_drug", "target": "PLG", "sign": true }, { "id": "t256", - "source": "Nafamostat_drug", + "source": "PLAT", "target": "PLG", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json index a2815c607..071d3ab6b 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf10_Cul2_pathway.json @@ -620,7 +620,7 @@ }, { "id": "t2", - "source": "Rbx1:Cul2_complex", + "source": "Zyg11B:EloBC_complex", "target": "Cul2 ubiquitin ligase_complex", "sign": true }, @@ -632,19 +632,19 @@ }, { "id": "t4", - "source": "Zyg11B:EloBC_complex", + "source": "Rbx1:Cul2_complex", "target": "Cul2 ubiquitin ligase_complex", "sign": true }, { "id": "t5", - "source": "CSN5_complex", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", "target": "Cul2 ubiquitin ligase_complex", "sign": true }, { "id": "t6", - "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "source": "CSN5_complex", "target": "Cul2 ubiquitin ligase_complex", "sign": true }, @@ -668,19 +668,19 @@ }, { "id": "t10", - "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "source": "Orf10", "target": "Cul2 ubiquitin ligase:Orf10_complex", "sign": true }, { "id": "t11", - "source": "Cul2 ubiquitin ligase_complex", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "target": "Cul2 ubiquitin ligase:Orf10_complex", "sign": true }, { "id": "t12", - "source": "Orf10", + "source": "Cul2 ubiquitin ligase_complex", "target": "Cul2 ubiquitin ligase:Orf10_complex", "sign": true }, @@ -710,13 +710,13 @@ }, { "id": "t17", - "source": "Zyg11B:EloBC_complex", + "source": "ELOB", "target": "ELOB:ELOC_complex", "sign": true }, { "id": "t18", - "source": "ELOB", + "source": "Zyg11B:EloBC_complex", "target": "ELOB:ELOC_complex", "sign": true }, @@ -740,43 +740,43 @@ }, { "id": "t22", - "source": "NEDD8", + "source": "NAE_complex", "target": "NAE:NEDD8_complex", "sign": true }, { "id": "t23", - "source": "NAE_complex", + "source": "NEDD8", "target": "NAE:NEDD8_complex", "sign": true }, { "id": "t24", - "source": "CUL2", + "source": "Cul2 ubiquitin ligase_complex", "target": "Rbx1:Cul2_complex", "sign": true }, { "id": "t25", - "source": "Cul2 ubiquitin ligase_complex", + "source": "RBX1", "target": "Rbx1:Cul2_complex", "sign": true }, { "id": "t26", - "source": "RBX1", + "source": "CUL2", "target": "Rbx1:Cul2_complex", "sign": true }, { "id": "t27", - "source": "Cul2 ubiquitin ligase:Orf10_complex", + "source": "ubit_traget", "target": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "sign": true }, { "id": "t28", - "source": "ubit_traget", + "source": "Cul2 ubiquitin ligase:Orf10_complex", "target": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "sign": true }, @@ -788,19 +788,19 @@ }, { "id": "t30", - "source": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", + "source": "UBE2M:NEDD8_complex", "target": "Cul2 ubiquitin ligase:substrate_complex_cell", "sign": true }, { "id": "t31", - "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", + "source": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "target": "Cul2 ubiquitin ligase:substrate_complex_cell", "sign": true }, { "id": "t32", - "source": "UBE2M:NEDD8_complex", + "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", "target": "Cul2 ubiquitin ligase:substrate_complex_cell", "sign": true }, @@ -812,13 +812,13 @@ }, { "id": "t34", - "source": "Cul2 ubiquitin ligase:substrate_complex_cell", + "source": "E2_ubiquitinated", "target": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "sign": true }, { "id": "t35", - "source": "E2_ubiquitinated", + "source": "Cul2 ubiquitin ligase:substrate_complex_cell", "target": "Cul2 ubiquitin ligase:N8:E2-Ub:substrate_complex", "sign": true }, @@ -854,37 +854,37 @@ }, { "id": "t41", - "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", + "source": "E2_ubiquitinated", "target": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", "sign": true }, { "id": "t42", - "source": "E2_ubiquitinated", + "source": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", "sign": true }, { "id": "t43", - "source": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "sign": true }, { "id": "t44", - "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", + "source": "Cul2 ubiquitin ligase:N8:Orf10:E2-Ub:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "sign": true }, { "id": "t45", - "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "source": "UBE2M:NEDD8_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "sign": true }, { "id": "t46", - "source": "UBE2M:NEDD8_complex", + "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", "target": "Cul2 ubiquitin ligase:N8:Orf10:substrate_complex", "sign": true }, @@ -902,13 +902,13 @@ }, { "id": "t49", - "source": "UBE2M", + "source": "NAE:NEDD8_complex", "target": "UBE2M:NEDD8_complex", "sign": true }, { "id": "t50", - "source": "NAE:NEDD8_complex", + "source": "UBE2M", "target": "UBE2M:NEDD8_complex", "sign": true }, @@ -920,49 +920,49 @@ }, { "id": "t52", - "source": "NAE1", + "source": "UBA3", "target": "NAE_complex", "sign": true }, { "id": "t53", - "source": "UBA3", + "source": "NAE1", "target": "NAE_complex", "sign": true }, { "id": "t54", - "source": "ELOB:ELOC_complex", + "source": "ELOB_rna", "target": "ELOB", "sign": true }, { "id": "t55", - "source": "ELOB_rna", + "source": "ELOB:ELOC_complex", "target": "ELOB", "sign": true }, { "id": "t56", - "source": "ELOC_rna", + "source": "ELOB:ELOC_complex", "target": "ELOC", "sign": true }, { "id": "t57", - "source": "ELOB:ELOC_complex", + "source": "ELOC_rna", "target": "ELOC", "sign": true }, { "id": "t58", - "source": "Zyg11B:EloBC_complex", + "source": "ZYG11B_rna", "target": "ZYG11B", "sign": true }, { "id": "t59", - "source": "ZYG11B_rna", + "source": "Zyg11B:EloBC_complex", "target": "ZYG11B", "sign": true }, @@ -980,13 +980,13 @@ }, { "id": "t62", - "source": "Rbx1:Cul2_complex", + "source": "CUL2_rna", "target": "CUL2", "sign": true }, { "id": "t63", - "source": "CUL2_rna", + "source": "Rbx1:Cul2_complex", "target": "CUL2", "sign": true }, @@ -1010,7 +1010,7 @@ }, { "id": "t67", - "source": "E2_rna", + "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", "target": "E2", "sign": true }, @@ -1022,13 +1022,13 @@ }, { "id": "t69", - "source": "Cul2 ubiquitin ligase:N8:Orf10:0E2:substrate_complex", + "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", "target": "E2", "sign": true }, { "id": "t70", - "source": "Cul2 ubiquitin ligase:N8:E2:substrate_complex", + "source": "E2_rna", "target": "E2", "sign": true }, @@ -1040,19 +1040,19 @@ }, { "id": "t72", - "source": "E1", + "source": "Ub_simple_molecule", "target": "E1_ubiquitinated", "sign": true }, { "id": "t73", - "source": "Ub_simple_molecule", + "source": "ATP_simple_molecule", "target": "E1_ubiquitinated", "sign": true }, { "id": "t74", - "source": "ATP_simple_molecule", + "source": "E1", "target": "E1_ubiquitinated", "sign": true }, @@ -1082,37 +1082,37 @@ }, { "id": "t79", - "source": "E1", + "source": "Ub_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t80", - "source": "Ub_simple_molecule", + "source": "ATP_simple_molecule", "target": "AMP_simple_molecule", "sign": true }, { "id": "t81", - "source": "ATP_simple_molecule", + "source": "E1", "target": "AMP_simple_molecule", "sign": true }, { "id": "t82", - "source": "E1", + "source": "Ub_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t83", - "source": "Ub_simple_molecule", + "source": "ATP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t84", - "source": "ATP_simple_molecule", + "source": "E1", "target": "PPi_simple_molecule", "sign": true }, @@ -1124,19 +1124,19 @@ }, { "id": "t86", - "source": "Orf10 (+)ss sgmRNA_rna", + "source": "Cul2 ubiquitin ligase:Orf10_complex", "target": "Orf10", "sign": true }, { "id": "t87", - "source": "Cul2 ubiquitin ligase:Orf10_complex", + "source": "Orf10 (+)ss sgmRNA_rna", "target": "Orf10", "sign": true }, { "id": "t88", - "source": "UBE2M:NEDD8_complex", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "target": "UBE2M", "sign": true }, @@ -1148,7 +1148,7 @@ }, { "id": "t90", - "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "source": "UBE2M:NEDD8_complex", "target": "UBE2M", "sign": true }, @@ -1160,19 +1160,19 @@ }, { "id": "t92", - "source": "ubit_traget_ubiquitinated", + "source": "DUB", "target": "ubit_traget", "sign": true }, { "id": "t93", - "source": "DUB", + "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", "target": "ubit_traget", "sign": true }, { "id": "t94", - "source": "Cul2 ubiquitin ligase:Orf10:substrate_complex", + "source": "ubit_traget_ubiquitinated", "target": "ubit_traget", "sign": true }, @@ -1214,13 +1214,13 @@ }, { "id": "t101", - "source": "UBA3_rna", + "source": "NAE_complex", "target": "UBA3", "sign": true }, { "id": "t102", - "source": "NAE_complex", + "source": "UBA3_rna", "target": "UBA3", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json index a61878654..fc3e64ea6 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Orf3a.json @@ -499,31 +499,31 @@ }, { "id": "t7", - "source": "Orf3a", + "source": "E", "target": "P65/P015_complex", "sign": true }, { "id": "t8", - "source": "IKBKG/IKBKB/CHUK_complex", + "source": "Orf3a", "target": "P65/P015_complex", "sign": true }, { "id": "t9", - "source": "E", + "source": "IKBKG/IKBKB/CHUK_complex", "target": "P65/P015_complex", "sign": true }, { "id": "t10", - "source": "TRIM30a/TRIM38_complex", + "source": "TRAF6", "target": "TAB2/TAB3/TAK1_complex", "sign": true }, { "id": "t11", - "source": "TRAF6", + "source": "TRIM30a/TRIM38_complex", "target": "TAB2/TAB3/TAK1_complex", "sign": true }, @@ -535,49 +535,49 @@ }, { "id": "t13", - "source": "TAB2/TAB3/TAK1_complex", + "source": "TRIM22", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { "id": "t14", - "source": "TRIM29", + "source": "TRIM27/TRIM21_complex", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { "id": "t15", - "source": "TRIM14/TRIM23_complex", + "source": "TAB2/TAB3/TAK1_complex", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { "id": "t16", - "source": "TRIM22", + "source": "TRIM14/TRIM23_complex", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { "id": "t17", - "source": "TRIM27/TRIM21_complex", + "source": "TRIM29", "target": "NEMO/IKKA/IKKB_complex", "sign": true }, { "id": "t18", - "source": "NFKB1", + "source": "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated", "target": "NFKB1:NFKNIA_complex", "sign": true }, { "id": "t19", - "source": "CACTIN", + "source": "NFKB1", "target": "NFKB1:NFKNIA_complex", "sign": true }, { "id": "t20", - "source": "NFKBIA_phosphorylated_ubiquitinated_ubiquitinated_ubiquitinated", + "source": "CACTIN", "target": "NFKB1:NFKNIA_complex", "sign": true }, @@ -625,7 +625,7 @@ }, { "id": "t28", - "source": "TRIM38", + "source": "TRIM23", "target": "TRAF6", "sign": true }, @@ -637,7 +637,7 @@ }, { "id": "t30", - "source": "TRIM23", + "source": "TRIM38", "target": "TRAF6", "sign": true }, @@ -649,25 +649,25 @@ }, { "id": "t32", - "source": "TRIM38", + "source": "TLR3", "target": "TICAM1", "sign": true }, { "id": "t33", - "source": "TLR3", + "source": "TRIM38", "target": "TICAM1", "sign": true }, { "id": "t34", - "source": "TRIM59", + "source": "TLR7/8/9_complex", "target": "MYD88", "sign": true }, { "id": "t35", - "source": "TLR7/8/9_complex", + "source": "TRIM59", "target": "MYD88", "sign": true }, @@ -715,19 +715,19 @@ }, { "id": "t43", - "source": "P65/P015_complex", + "source": "CASP1", "target": "IL1b", "sign": true }, { "id": "t44", - "source": "E", + "source": "P65/P015_complex", "target": "IL1b", "sign": true }, { "id": "t45", - "source": "CASP1", + "source": "E", "target": "IL1b", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json index abf62bac3..4ddf4dfcb 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/PAMP_signaling.json @@ -770,13 +770,13 @@ }, { "id": "t2", - "source": "IRAK4", + "source": "IRAK1", "target": "MYD88:IRAK:TRAF_complex", "sign": true }, { "id": "t3", - "source": "IRAK1", + "source": "IRAK4", "target": "MYD88:IRAK:TRAF_complex", "sign": true }, @@ -794,7 +794,7 @@ }, { "id": "t6", - "source": "MAVS", + "source": "TRAF6", "target": "MAVS:TRAF_complex", "sign": true }, @@ -806,19 +806,19 @@ }, { "id": "t8", - "source": "TRAF6", + "source": "MAVS", "target": "MAVS:TRAF_complex", "sign": true }, { "id": "t9", - "source": "TRADD", + "source": "MAVS", "target": "MAVS:TRADD_complex", "sign": true }, { "id": "t10", - "source": "MAVS", + "source": "TRADD", "target": "MAVS:TRADD_complex", "sign": true }, @@ -848,25 +848,25 @@ }, { "id": "t15", - "source": "IKBKG", + "source": "CHUK", "target": "IKK Complex_complex_cell", "sign": true }, { "id": "t16", - "source": "CHUK", + "source": "IKBKG", "target": "IKK Complex_complex_cell", "sign": true }, { "id": "t17", - "source": "NFKBIA", + "source": "NFKB1", "target": "NFKB:NFKBIA_complex_cell", "sign": true }, { "id": "t18", - "source": "NFKB1", + "source": "NFKBIA", "target": "NFKB:NFKBIA_complex_cell", "sign": true }, @@ -878,19 +878,19 @@ }, { "id": "t20", - "source": "Nsp3", + "source": "MAVS:TRADD_complex", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, { "id": "t21", - "source": "M", + "source": "Nsp3", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, { "id": "t22", - "source": "MAVS:TRADD_complex", + "source": "M", "target": "TANK:TRAF3:IKBKE_complex_cell", "sign": true }, @@ -938,13 +938,13 @@ }, { "id": "t30", - "source": "ssRNA_rna", + "source": "TLR7", "target": "TLR7:ssRNA_complex", "sign": true }, { "id": "t31", - "source": "TLR7", + "source": "ssRNA_rna", "target": "TLR7:ssRNA_complex", "sign": true }, @@ -968,7 +968,7 @@ }, { "id": "t35", - "source": "M", + "source": "dsRNA_rna_cell", "target": "DDX58:dsRNA_complex", "sign": true }, @@ -980,31 +980,31 @@ }, { "id": "t37", - "source": "dsRNA_rna_cell", + "source": "M", "target": "DDX58:dsRNA_complex", "sign": true }, { "id": "t38", - "source": "Nsp3", + "source": "M", "target": "IFIH1:dsRNA_complex", "sign": true }, { "id": "t39", - "source": "M", + "source": "Nsp3", "target": "IFIH1:dsRNA_complex", "sign": true }, { "id": "t40", - "source": "dsRNA_rna_cell", + "source": "IFIH1", "target": "IFIH1:dsRNA_complex", "sign": true }, { "id": "t41", - "source": "IFIH1", + "source": "dsRNA_rna_cell", "target": "IFIH1:dsRNA_complex", "sign": true }, @@ -1040,19 +1040,19 @@ }, { "id": "t47", - "source": "Nsp15", + "source": "EIF2AK2", "target": "EIF2AK2:dsRNA_complex", "sign": true }, { "id": "t48", - "source": "EIF2AK2", + "source": "dsRNA_rna_cell", "target": "EIF2AK2:dsRNA_complex", "sign": true }, { "id": "t49", - "source": "dsRNA_rna_cell", + "source": "Nsp15", "target": "EIF2AK2:dsRNA_complex", "sign": true }, @@ -1070,7 +1070,7 @@ }, { "id": "t52", - "source": "M", + "source": "CASP10", "target": "IKK Complex_complex_cell", "sign": true }, @@ -1082,19 +1082,19 @@ }, { "id": "t54", - "source": "CASP10", + "source": "M", "target": "IKK Complex_complex_cell", "sign": true }, { "id": "t55", - "source": "JNK_complex", + "source": "MAPK14_phosphorylated", "target": "AP1_complex", "sign": true }, { "id": "t56", - "source": "MAPK14_phosphorylated", + "source": "JNK_complex", "target": "AP1_complex", "sign": true }, @@ -1112,37 +1112,37 @@ }, { "id": "t59", - "source": "TLR3:dsRNA_complex", + "source": "TICAM1_cell", "target": "TICAM1_cell", "sign": true }, { "id": "t60", - "source": "TICAM1_cell", + "source": "TLR3:dsRNA_complex", "target": "TICAM1_cell", "sign": true }, { "id": "t61", - "source": "TBK1_cell", + "source": "TANK:TRAF3:IKBKE_complex_cell", "target": "TBK1_cell", "sign": true }, { "id": "t62", - "source": "TANK:TRAF3:IKBKE_complex_cell", + "source": "TBK1_cell", "target": "TBK1_cell", "sign": true }, { "id": "t63", - "source": "Nsp3", + "source": "TANK:TRAF3:IKBKE_complex_cell", "target": "IKBKE_cell", "sign": true }, { "id": "t64", - "source": "TANK:TRAF3:IKBKE_complex_cell", + "source": "Nsp3", "target": "IKBKE_cell", "sign": true }, @@ -1154,19 +1154,19 @@ }, { "id": "t66", - "source": "Nsp3", + "source": "Orf3b", "target": "IRF3_phosphorylated_cell", "sign": true }, { "id": "t67", - "source": "Orf3b", + "source": "Nsp3", "target": "IRF3_phosphorylated_cell", "sign": true }, { "id": "t68", - "source": "TBK1_cell", + "source": "Orf8", "target": "IRF3_phosphorylated_cell", "sign": true }, @@ -1178,43 +1178,43 @@ }, { "id": "t70", - "source": "Orf8", + "source": "TBK1_cell", "target": "IRF3_phosphorylated_cell", "sign": true }, { "id": "t71", - "source": "RNF135", + "source": "TRIM25", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t72", - "source": "DDX58:dsRNA_complex", + "source": "RNF135", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t73", - "source": "TRIM25", + "source": "N", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t74", - "source": "N", + "source": "DDX58:dsRNA_complex", "target": "DDX58_ubiquitinated", "sign": true }, { "id": "t75", - "source": "IFIH1:dsRNA_complex", + "source": "DDX58_ubiquitinated", "target": "MAVS", "sign": true }, { "id": "t76", - "source": "DDX58_ubiquitinated", + "source": "IFIH1:dsRNA_complex", "target": "MAVS", "sign": true }, @@ -1262,7 +1262,7 @@ }, { "id": "t84", - "source": "UBE2N", + "source": "MYD88:IRAK:TRAF_complex", "target": "TRAF6_ubiquitinated", "sign": true }, @@ -1274,7 +1274,7 @@ }, { "id": "t86", - "source": "MYD88:IRAK:TRAF_complex", + "source": "UBE2N", "target": "TRAF6_ubiquitinated", "sign": true }, @@ -1322,13 +1322,13 @@ }, { "id": "t94", - "source": "MAP3K7", + "source": "EIF2AK2:dsRNA_complex", "target": "MAP2K6_phosphorylated", "sign": true }, { "id": "t95", - "source": "EIF2AK2:dsRNA_complex", + "source": "MAP3K7", "target": "MAP2K6_phosphorylated", "sign": true }, @@ -1364,25 +1364,25 @@ }, { "id": "t101", - "source": "IRF3_phosphorylated_nucleus", + "source": "NFKB_complex", "target": "transcription of proinflammatory proteins_phenotype", "sign": true }, { "id": "t102", - "source": "IRF7_phosphorylated", + "source": "AP1_complex", "target": "transcription of proinflammatory proteins_phenotype", "sign": true }, { "id": "t103", - "source": "AP1_complex", + "source": "IRF3_phosphorylated_nucleus", "target": "transcription of proinflammatory proteins_phenotype", "sign": true }, { "id": "t104", - "source": "NFKB_complex", + "source": "IRF7_phosphorylated", "target": "transcription of proinflammatory proteins_phenotype", "sign": true } diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json index 38a97e144..6cade6b34 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Pyrimidine_deprivation.json @@ -970,13 +970,13 @@ "edges": [ { "id": "t1", - "source": "NF-kB_complex", + "source": "IRF3_phosphorylated", "target": "IFNB1_space_expression_space_complex_complex", "sign": true }, { "id": "t2", - "source": "IRF3_phosphorylated", + "source": "NF-kB_complex", "target": "IFNB1_space_expression_space_complex_complex", "sign": true }, @@ -1006,13 +1006,13 @@ }, { "id": "t7", - "source": "cGAMP-STING_complex_endoplasmic reticulum-Golgi intermediate compartment", + "source": "LC3", "target": "cGAMP:STING:LC3_complex", "sign": true }, { "id": "t8", - "source": "LC3", + "source": "cGAMP-STING_complex_endoplasmic reticulum-Golgi intermediate compartment", "target": "cGAMP:STING:LC3_complex", "sign": true }, @@ -1024,55 +1024,55 @@ }, { "id": "t10", - "source": "cGAS", + "source": "dsDNA_simple_molecule", "target": "cGAS:dsDNA_complex", "sign": true }, { "id": "t11", - "source": "dsDNA_simple_molecule", + "source": "cGAS", "target": "cGAS:dsDNA_complex", "sign": true }, { "id": "t12", - "source": "MRE11", + "source": "dsDNA_simple_molecule", "target": "MRE11:dsDNA_complex", "sign": true }, { "id": "t13", - "source": "dsDNA_simple_molecule", + "source": "MRE11", "target": "MRE11:dsDNA_complex", "sign": true }, { "id": "t14", - "source": "cGAMP:STING_complex_Golgi apparatus", + "source": "TBK1", "target": "STING:TBK1_complex_Golgi apparatus", "sign": true }, { "id": "t15", - "source": "TBK1", + "source": "STING_Golgi apparatus", "target": "STING:TBK1_complex_Golgi apparatus", "sign": true }, { "id": "t16", - "source": "STING_Golgi apparatus", + "source": "cGAMP:STING_complex_Golgi apparatus", "target": "STING:TBK1_complex_Golgi apparatus", "sign": true }, { "id": "t17", - "source": "SAR1A", + "source": "cGAMP:STING_complex_endoplasmic reticulum", "target": "cGAMP-STING_complex_COPII-coated vesicle", "sign": true }, { "id": "t18", - "source": "cGAMP:STING_complex_endoplasmic reticulum", + "source": "SAR1A", "target": "cGAMP-STING_complex_COPII-coated vesicle", "sign": true }, @@ -1108,19 +1108,19 @@ }, { "id": "t24", - "source": "H+simple_molecule", + "source": "CAD", "target": "H2O_simple_molecule", "sign": true }, { "id": "t25", - "source": "CAD", + "source": "H+simple_molecule", "target": "H2O_simple_molecule", "sign": true }, { "id": "t26", - "source": "UMPS", + "source": "orotidine_space_5'-monophosphate_simple_molecule", "target": "UMP_simple_molecule", "sign": true }, @@ -1132,13 +1132,13 @@ }, { "id": "t28", - "source": "uridine_simple_molecule", + "source": "UMPS", "target": "UMP_simple_molecule", "sign": true }, { "id": "t29", - "source": "orotidine_space_5'-monophosphate_simple_molecule", + "source": "uridine_simple_molecule", "target": "UMP_simple_molecule", "sign": true }, @@ -1150,13 +1150,13 @@ }, { "id": "t31", - "source": "cGAS:dsDNA_complex", + "source": "ATP_simple_molecule", "target": "cGAMP_simple_molecule", "sign": true }, { "id": "t32", - "source": "ATP_simple_molecule", + "source": "cGAS:dsDNA_complex", "target": "cGAMP_simple_molecule", "sign": true }, @@ -1168,25 +1168,25 @@ }, { "id": "t34", - "source": "CDP_simple_molecule", + "source": "ribonucleoside-diphosphate reductase_complex", "target": "dCDP_simple_molecule", "sign": true }, { "id": "t35", - "source": "ribonucleoside-diphosphate reductase_complex", + "source": "CDP_simple_molecule", "target": "dCDP_simple_molecule", "sign": true }, { "id": "t36", - "source": "UMP_simple_molecule", + "source": "CMPK", "target": "UDP_simple_molecule", "sign": true }, { "id": "t37", - "source": "CMPK", + "source": "UMP_simple_molecule", "target": "UDP_simple_molecule", "sign": true }, @@ -1210,25 +1210,25 @@ }, { "id": "t41", - "source": "L-Gln_simple_molecule", + "source": "L-Asp_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t42", - "source": "L-Asp_simple_molecule", + "source": "CAD", "target": "Pi_simple_molecule", "sign": true }, { "id": "t43", - "source": "H2O_simple_molecule", + "source": "L-Gln_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t44", - "source": "CAD", + "source": "H2O_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, @@ -1240,13 +1240,13 @@ }, { "id": "t46", - "source": "CAP_simple_molecule", + "source": "HCO3-simple_molecule", "target": "Pi_simple_molecule", "sign": true }, { "id": "t47", - "source": "HCO3-simple_molecule", + "source": "CAP_simple_molecule", "target": "Pi_simple_molecule", "sign": true }, @@ -1258,31 +1258,31 @@ }, { "id": "t49", - "source": "H+simple_molecule", + "source": "CAD", "target": "(S)-dihydroorotate_simple_molecule", "sign": true }, { "id": "t50", - "source": "CAD", + "source": "H+simple_molecule", "target": "(S)-dihydroorotate_simple_molecule", "sign": true }, { "id": "t51", - "source": "L-Gln_simple_molecule", + "source": "CAD", "target": "ADP_simple_molecule", "sign": true }, { "id": "t52", - "source": "H2O_simple_molecule", + "source": "L-Gln_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t53", - "source": "HCO3-simple_molecule", + "source": "H2O_simple_molecule", "target": "ADP_simple_molecule", "sign": true }, @@ -1294,49 +1294,49 @@ }, { "id": "t55", - "source": "CAD", + "source": "HCO3-simple_molecule", "target": "ADP_simple_molecule", "sign": true }, { "id": "t56", - "source": "dCMP_simple_molecule", + "source": "DCTD", "target": "dUMP_simple_molecule", "sign": true }, { "id": "t57", - "source": "DUT", + "source": "dUTP_simple_molecule", "target": "dUMP_simple_molecule", "sign": true }, { "id": "t58", - "source": "DCTD", + "source": "DUT", "target": "dUMP_simple_molecule", "sign": true }, { "id": "t59", - "source": "dUTP_simple_molecule", + "source": "dCMP_simple_molecule", "target": "dUMP_simple_molecule", "sign": true }, { "id": "t60", - "source": "CAP_simple_molecule", + "source": "L-Asp_simple_molecule", "target": "N-carbamoyl-L-aspartate_simple_molecule", "sign": true }, { "id": "t61", - "source": "L-Asp_simple_molecule", + "source": "CAD", "target": "N-carbamoyl-L-aspartate_simple_molecule", "sign": true }, { "id": "t62", - "source": "CAD", + "source": "CAP_simple_molecule", "target": "N-carbamoyl-L-aspartate_simple_molecule", "sign": true }, @@ -1372,7 +1372,7 @@ }, { "id": "t68", - "source": "dTTP_simple_molecule", + "source": "dsDNA_simple_molecule", "target": "DNA_gene", "sign": true }, @@ -1384,13 +1384,13 @@ }, { "id": "t70", - "source": "dsDNA_simple_molecule", + "source": "virus_space_replication_phenotype", "target": "DNA_gene", "sign": true }, { "id": "t71", - "source": "virus_space_replication_phenotype", + "source": "dTTP_simple_molecule", "target": "DNA_gene", "sign": true }, @@ -1444,31 +1444,31 @@ }, { "id": "t80", - "source": "UMPS", + "source": "PRPP_simple_molecule", "target": "PPi_simple_molecule", "sign": true }, { "id": "t81", - "source": "PRPP_simple_molecule", + "source": "UMPS", "target": "PPi_simple_molecule", "sign": true }, { "id": "t82", - "source": "L-Gln_simple_molecule", + "source": "CAD", "target": "L-Glu_simple_molecule", "sign": true }, { "id": "t83", - "source": "H2O_simple_molecule", + "source": "L-Gln_simple_molecule", "target": "L-Glu_simple_molecule", "sign": true }, { "id": "t84", - "source": "HCO3-simple_molecule", + "source": "H2O_simple_molecule", "target": "L-Glu_simple_molecule", "sign": true }, @@ -1480,7 +1480,7 @@ }, { "id": "t86", - "source": "CAD", + "source": "HCO3-simple_molecule", "target": "L-Glu_simple_molecule", "sign": true }, @@ -1510,19 +1510,19 @@ }, { "id": "t91", - "source": "L-Gln_simple_molecule", + "source": "CAD", "target": "CAP_simple_molecule", "sign": true }, { "id": "t92", - "source": "H2O_simple_molecule", + "source": "L-Gln_simple_molecule", "target": "CAP_simple_molecule", "sign": true }, { "id": "t93", - "source": "HCO3-simple_molecule", + "source": "H2O_simple_molecule", "target": "CAP_simple_molecule", "sign": true }, @@ -1534,7 +1534,7 @@ }, { "id": "t95", - "source": "CAD", + "source": "HCO3-simple_molecule", "target": "CAP_simple_molecule", "sign": true }, @@ -1552,13 +1552,13 @@ }, { "id": "t98", - "source": "MRE11:RAD50:DNA_complex_endoplasmic reticulum", + "source": "STING_endoplasmic reticulum", "target": "STING_Golgi apparatus", "sign": true }, { "id": "t99", - "source": "STING_endoplasmic reticulum", + "source": "MRE11:RAD50:DNA_complex_endoplasmic reticulum", "target": "STING_Golgi apparatus", "sign": true }, @@ -1582,7 +1582,7 @@ }, { "id": "t103", - "source": "(S)-dihydroorotate_simple_molecule", + "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", "target": "QH2_simple_molecule", "sign": true }, @@ -1594,19 +1594,19 @@ }, { "id": "t105", - "source": "P1788_simple_molecule", + "source": "CoQ_simple_molecule", "target": "QH2_simple_molecule", "sign": true }, { "id": "t106", - "source": "CoQ_simple_molecule", + "source": "P1788_simple_molecule", "target": "QH2_simple_molecule", "sign": true }, { "id": "t107", - "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", + "source": "(S)-dihydroorotate_simple_molecule", "target": "QH2_simple_molecule", "sign": true }, @@ -1618,31 +1618,31 @@ }, { "id": "t109", - "source": "UMPS", + "source": "PRPP_simple_molecule", "target": "orotidine_space_5'-monophosphate_simple_molecule", "sign": true }, { "id": "t110", - "source": "PRPP_simple_molecule", + "source": "UMPS", "target": "orotidine_space_5'-monophosphate_simple_molecule", "sign": true }, { "id": "t111", - "source": "NME1", + "source": "dUDP_simple_molecule", "target": "dUTP_simple_molecule", "sign": true }, { "id": "t112", - "source": "dUDP_simple_molecule", + "source": "NME1", "target": "dUTP_simple_molecule", "sign": true }, { "id": "t113", - "source": "(S)-dihydroorotate_simple_molecule", + "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", "target": "orotate_simple_molecule", "sign": true }, @@ -1654,49 +1654,49 @@ }, { "id": "t115", - "source": "P1788_simple_molecule", + "source": "CoQ_simple_molecule", "target": "orotate_simple_molecule", "sign": true }, { "id": "t116", - "source": "CoQ_simple_molecule", + "source": "P1788_simple_molecule", "target": "orotate_simple_molecule", "sign": true }, { "id": "t117", - "source": "dihydroorotate_space_dehydrogenase_space_holoenzyme_simple_molecule", + "source": "(S)-dihydroorotate_simple_molecule", "target": "orotate_simple_molecule", "sign": true }, { "id": "t118", - "source": "UMPS", + "source": "orotidine_space_5'-monophosphate_simple_molecule", "target": "CO2_simple_molecule", "sign": true }, { "id": "t119", - "source": "orotidine_space_5'-monophosphate_simple_molecule", + "source": "UMPS", "target": "CO2_simple_molecule", "sign": true }, { "id": "t120", - "source": "CDP_simple_molecule", + "source": "UTP_simple_molecule", "target": "CTP_simple_molecule", "sign": true }, { "id": "t121", - "source": "UTP_simple_molecule", + "source": "NME1", "target": "CTP_simple_molecule", "sign": true }, { "id": "t122", - "source": "NME1", + "source": "CDP_simple_molecule", "target": "CTP_simple_molecule", "sign": true }, @@ -1708,13 +1708,13 @@ }, { "id": "t124", - "source": "UDP_simple_molecule", + "source": "ribonucleoside-diphosphate reductase_complex", "target": "dUDP_simple_molecule", "sign": true }, { "id": "t125", - "source": "ribonucleoside-diphosphate reductase_complex", + "source": "UDP_simple_molecule", "target": "dUDP_simple_molecule", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json index 8bec1221c..8b70c26f0 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/RTC-and-transcription.json @@ -310,25 +310,25 @@ "edges": [ { "id": "t1", - "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_cell", + "source": "nsp9_cell", "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "sign": true }, { "id": "t2", - "source": "complex_complex_cell", + "source": "CoV_space_poly-br_merase_space_complex_complex_cell", "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "sign": true }, { "id": "t3", - "source": "CoV_space_poly-br_merase_space_complex_complex_cell", + "source": "complex_complex_cell", "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "sign": true }, { "id": "t4", - "source": "nsp9_cell", + "source": "(+)gRNA_space_(including_space_ORF1a_space_ORF1b)_gene_cell", "target": "Replication_space_transcription_space_complex_space__complex_double membrane vesicle viral factory", "sign": true }, @@ -340,25 +340,25 @@ }, { "id": "t6", - "source": "nsp8_space_(II)", + "source": "nsp7", "target": "complex_complex_cell", "sign": true }, { "id": "t7", - "source": "nsp7", + "source": "nsp8_space_(II)", "target": "complex_complex_cell", "sign": true }, { "id": "t8", - "source": "nsp14", + "source": "nsp10", "target": "CoV_space_poly-br_merase_space_complex_complex_cell", "sign": true }, { "id": "t9", - "source": "nsp10", + "source": "nsp14", "target": "CoV_space_poly-br_merase_space_complex_complex_cell", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json index 2ed1e2392..41846515a 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Renin_angiotensin.json @@ -841,7 +841,7 @@ "edges": [ { "id": "t1", - "source": "AGTR1_cell", + "source": "angiotensin II_simple_molecule_cell", "target": "ACE2:AGTR1_complex", "sign": true }, @@ -853,31 +853,31 @@ }, { "id": "t3", - "source": "angiotensin II_simple_molecule_cell", + "source": "AGTR1_cell", "target": "ACE2:AGTR1_complex", "sign": true }, { "id": "t4", - "source": "Camostat mesilate_drug", + "source": "ACE2_cell", "target": "ACE2-Spike complex_complex", "sign": true }, { "id": "t5", - "source": "S", + "source": "TMPRSS2", "target": "ACE2-Spike complex_complex", "sign": true }, { "id": "t6", - "source": "TMPRSS2", + "source": "Camostat mesilate_drug", "target": "ACE2-Spike complex_complex", "sign": true }, { "id": "t7", - "source": "ACE2_cell", + "source": "S", "target": "ACE2-Spike complex_complex", "sign": true }, @@ -895,37 +895,37 @@ }, { "id": "t10", - "source": "REN", + "source": "AGT", "target": "angiotensin I_simple_molecule", "sign": true }, { "id": "t11", - "source": "AGT", + "source": "ACE_cell", "target": "angiotensin I_simple_molecule", "sign": true }, { "id": "t12", - "source": "ACE_cell", + "source": "REN", "target": "angiotensin I_simple_molecule", "sign": true }, { "id": "t13", - "source": "angiotensin 1-12_simple_molecule", + "source": "CTSG", "target": "angiotensin I_simple_molecule", "sign": true }, { "id": "t14", - "source": "CTSG", + "source": "CTSD", "target": "angiotensin I_simple_molecule", "sign": true }, { "id": "t15", - "source": "CTSD", + "source": "angiotensin 1-12_simple_molecule", "target": "angiotensin I_simple_molecule", "sign": true }, @@ -949,25 +949,25 @@ }, { "id": "t19", - "source": "angiotensin 1-12_simple_molecule", + "source": "CMA1", "target": "angiotensin II_simple_molecule_cell", "sign": true }, { "id": "t20", - "source": "angiotensin I_simple_molecule", + "source": "KLK1", "target": "angiotensin II_simple_molecule_cell", "sign": true }, { "id": "t21", - "source": "CMA1", + "source": "angiotensin 1-12_simple_molecule", "target": "angiotensin II_simple_molecule_cell", "sign": true }, { "id": "t22", - "source": "KLK1", + "source": "angiotensin I_simple_molecule", "target": "angiotensin II_simple_molecule_cell", "sign": true }, @@ -979,31 +979,31 @@ }, { "id": "t24", - "source": "THOP1", + "source": "angiotensin 1-9_simple_molecule", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t25", - "source": "MME_cell", + "source": "PREP", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t26", - "source": "PREP", + "source": "THOP1", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t27", - "source": "angiotensin 1-12_simple_molecule", + "source": "ACE_cell_active", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t28", - "source": "angiotensin 1-9_simple_molecule", + "source": "ACE2_cell", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, @@ -1015,79 +1015,79 @@ }, { "id": "t30", - "source": "ACE_cell_active", + "source": "angiotensin II_simple_molecule_cell", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t31", - "source": "angiotensin II_simple_molecule_cell", + "source": "PRCP", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t32", - "source": "PRCP", + "source": "MME_cell", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t33", - "source": "ACE2_cell", + "source": "angiotensin 1-12_simple_molecule", "target": "angiotensin 1-7_simple_molecule_cell", "sign": true }, { "id": "t34", - "source": "CGP42112A_drug", + "source": "angiotensin 1-9_simple_molecule", "target": "AGTR2_cell_active", "sign": true }, { "id": "t35", - "source": "angiotensin 1-9_simple_molecule", + "source": "angiotensin A_simple_molecule", "target": "AGTR2_cell_active", "sign": true }, { "id": "t36", - "source": "AGTR2_cell", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "AGTR2_cell_active", "sign": true }, { "id": "t37", - "source": "angiotensin A_simple_molecule", + "source": "AGTR2_cell", "target": "AGTR2_cell_active", "sign": true }, { "id": "t38", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "angiotensin II_simple_molecule_cell", "target": "AGTR2_cell_active", "sign": true }, { "id": "t39", - "source": "angiotensin II_simple_molecule_cell", + "source": "CGP42112A_drug", "target": "AGTR2_cell_active", "sign": true }, { "id": "t40", - "source": "MAS1_cell", + "source": "angiotensin 1-5_simple_molecule", "target": "MAS1_cell_active", "sign": true }, { "id": "t41", - "source": "angiotensin 1-5_simple_molecule", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "MAS1_cell_active", "sign": true }, { "id": "t42", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "MAS1_cell", "target": "MAS1_cell_active", "sign": true }, @@ -1099,37 +1099,37 @@ }, { "id": "t44", - "source": "Calcitriol_simple_molecule", + "source": "estradiol_simple_molecule", "target": "ACE_cell", "sign": true }, { "id": "t45", - "source": "estradiol_simple_molecule", + "source": "Calcitriol_simple_molecule", "target": "ACE_cell", "sign": true }, { "id": "t46", - "source": "ACE2_gene", + "source": "hypertension_phenotype", "target": "ACE2_cell", "sign": true }, { "id": "t47", - "source": "Calcitriol_simple_molecule", + "source": "aging_phenotype", "target": "ACE2_cell", "sign": true }, { "id": "t48", - "source": "SARS-CoV-2 infection_phenotype", + "source": "Calcitriol_simple_molecule", "target": "ACE2_cell", "sign": true }, { "id": "t49", - "source": "aging_phenotype", + "source": "SARS-CoV-2 infection_phenotype", "target": "ACE2_cell", "sign": true }, @@ -1141,19 +1141,19 @@ }, { "id": "t51", - "source": "hypertension_phenotype", + "source": "ACE2_gene", "target": "ACE2_cell", "sign": true }, { "id": "t52", - "source": "S", + "source": " Diabetes mellitus, type II_phenotype", "target": "ACE2_cell", "sign": true }, { "id": "t53", - "source": " Diabetes mellitus, type II_phenotype", + "source": "S", "target": "ACE2_cell", "sign": true }, @@ -1183,37 +1183,37 @@ }, { "id": "t58", - "source": "angiotensin A_simple_molecule", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "alamandine_simple_molecule", "sign": true }, { "id": "t59", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "ACE2_cell", "target": "alamandine_simple_molecule", "sign": true }, { "id": "t60", - "source": "ACE2_cell", + "source": "angiotensin A_simple_molecule", "target": "alamandine_simple_molecule", "sign": true }, { "id": "t61", - "source": "MRGPRD_cell", + "source": "alamandine_simple_molecule", "target": "MRGPRD_cell_active", "sign": true }, { "id": "t62", - "source": "alamandine_simple_molecule", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "MRGPRD_cell_active", "sign": true }, { "id": "t63", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "MRGPRD_cell", "target": "MRGPRD_cell_active", "sign": true }, @@ -1225,55 +1225,55 @@ }, { "id": "t65", - "source": "AGTR1_cell_active", + "source": "MAS1_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { "id": "t66", - "source": "AGTR2_cell_active", + "source": "LNPEP_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { "id": "t67", - "source": "MAS1_cell_active", + "source": "MRGPRD_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { "id": "t68", - "source": "MRGPRD_cell_active", + "source": "AGTR1_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { "id": "t69", - "source": "LNPEP_cell_active", + "source": "AGTR2_cell_active", "target": "vasoconstriction_phenotype", "sign": true }, { "id": "t70", - "source": "LNPEP_cell_active", + "source": "MAS1_cell_active", "target": "inflammatory response_phenotype", "sign": true }, { "id": "t71", - "source": "MAS1_cell_active", + "source": "MRGPRD_cell_active", "target": "inflammatory response_phenotype", "sign": true }, { "id": "t72", - "source": "MRGPRD_cell_active", + "source": "AGTR1_cell_active", "target": "inflammatory response_phenotype", "sign": true }, { "id": "t73", - "source": "AGTR1_cell_active", + "source": "LNPEP_cell_active", "target": "inflammatory response_phenotype", "sign": true }, @@ -1303,13 +1303,13 @@ }, { "id": "t78", - "source": "sex, male_phenotype", + "source": "ENPEP_cell", "target": "ENPEP_cell_active", "sign": true }, { "id": "t79", - "source": "ENPEP_cell", + "source": "sex, male_phenotype", "target": "ENPEP_cell_active", "sign": true }, @@ -1369,73 +1369,73 @@ }, { "id": "t89", - "source": "sex, male_phenotype", + "source": "aging_phenotype", "target": "ACE2_cell_active", "sign": true }, { "id": "t90", - "source": "hypertension_phenotype", + "source": "sex, male_phenotype", "target": "ACE2_cell_active", "sign": true }, { "id": "t91", - "source": "aging_phenotype", + "source": "ACE2_cell", "target": "ACE2_cell_active", "sign": true }, { "id": "t92", - "source": "ACE2_cell", + "source": "hypertension_phenotype", "target": "ACE2_cell_active", "sign": true }, { "id": "t93", - "source": "sex, male_phenotype", + "source": "aldosterone_simple_molecule", "target": "ACE_cell_active", "sign": true }, { "id": "t94", - "source": "Lisinopril_drug", + "source": "hypertension_phenotype", "target": "ACE_cell_active", "sign": true }, { "id": "t95", - "source": "ACE_cell", + "source": "aging_phenotype", "target": "ACE_cell_active", "sign": true }, { "id": "t96", - "source": "ABO blood group system_phenotype", + "source": "ACE_cell", "target": "ACE_cell_active", "sign": true }, { "id": "t97", - "source": "aging_phenotype", + "source": "ABO blood group system_phenotype", "target": "ACE_cell_active", "sign": true }, { "id": "t98", - "source": "aldosterone_simple_molecule", + "source": "Lisinopril_drug", "target": "ACE_cell_active", "sign": true }, { "id": "t99", - "source": "hypertension_phenotype", + "source": "sex, male_phenotype", "target": "ACE_cell_active", "sign": true }, { "id": "t100", - "source": "MAS1:AGTR1_complex", + "source": "angiotensin IV_simple_molecule", "target": "AGTR1_cell_active", "sign": true }, @@ -1447,43 +1447,43 @@ }, { "id": "t102", - "source": "angiotensin IV_simple_molecule", + "source": "angiotensin A_simple_molecule", "target": "AGTR1_cell_active", "sign": true }, { "id": "t103", - "source": "angiotensin A_simple_molecule", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "AGTR1_cell_active", "sign": true }, { "id": "t104", - "source": "AGTR1_cell", + "source": "angiotensin II_simple_molecule_cell", "target": "AGTR1_cell_active", "sign": true }, { "id": "t105", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "MAS1:AGTR1_complex", "target": "AGTR1_cell_active", "sign": true }, { "id": "t106", - "source": "angiotensin II_simple_molecule_cell", + "source": "AGTR1_cell", "target": "AGTR1_cell_active", "sign": true }, { "id": "t107", - "source": "angiotensin 1-12_simple_molecule", + "source": "MME_cell", "target": "angiotensin 1-4_simple_molecule", "sign": true }, { "id": "t108", - "source": "MME_cell", + "source": "angiotensin 1-12_simple_molecule", "target": "angiotensin 1-4_simple_molecule", "sign": true }, @@ -1495,13 +1495,13 @@ }, { "id": "t110", - "source": "LNPEP_cell", + "source": "angiotensin IV_simple_molecule", "target": "LNPEP_cell_active", "sign": true }, { "id": "t111", - "source": "angiotensin IV_simple_molecule", + "source": "LNPEP_cell", "target": "LNPEP_cell_active", "sign": true }, @@ -1519,13 +1519,13 @@ }, { "id": "t114", - "source": "angiotensin 1-7_simple_molecule_cell", + "source": "angiotensin IV_simple_molecule", "target": "angiotensin 3-7_simple_molecule", "sign": true }, { "id": "t115", - "source": "angiotensin IV_simple_molecule", + "source": "angiotensin 1-7_simple_molecule_cell", "target": "angiotensin 3-7_simple_molecule", "sign": true }, @@ -1543,13 +1543,13 @@ }, { "id": "t118", - "source": "AGTR2_cell_active", + "source": "MAS1_cell_active", "target": "fibrosis_phenotype", "sign": true }, { "id": "t119", - "source": "MAS1_cell_active", + "source": "AGTR2_cell_active", "target": "fibrosis_phenotype", "sign": true }, @@ -1579,13 +1579,13 @@ }, { "id": "t124", - "source": "sex, male_phenotype", + "source": "MME_cell", "target": "MME_cell_active", "sign": true }, { "id": "t125", - "source": "MME_cell", + "source": "sex, male_phenotype", "target": "MME_cell_active", "sign": true }, @@ -1597,13 +1597,13 @@ }, { "id": "t127", - "source": "LNPEP_cell_active", + "source": "AGTR1_cell_active", "target": "cognition_phenotype", "sign": true }, { "id": "t128", - "source": "AGTR1_cell_active", + "source": "LNPEP_cell_active", "target": "cognition_phenotype", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json index 92ad36a72..a35415b89 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/TGFB_pathway.json @@ -201,37 +201,37 @@ "edges": [ { "id": "t1", - "source": "BMPR1/2/ACTR2_complex", + "source": "MAPK3", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t2", - "source": "Orf3a", + "source": "E", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t3", - "source": "Nsp7b_cell", + "source": "Orf3a", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t4", - "source": "E", + "source": "BAMBI", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t5", - "source": "BAMBI", + "source": "BMPR1/2/ACTR2_complex", "target": "SMAD1/5/8_complex", "sign": true }, { "id": "t6", - "source": "MAPK3", + "source": "Nsp7b_cell", "target": "SMAD1/5/8_complex", "sign": true }, @@ -243,19 +243,19 @@ }, { "id": "t8", - "source": "Nsp7b_default_compartment", + "source": "TGFB/TGFBR_complex", "target": "SMAD2/3_complex", "sign": true }, { "id": "t9", - "source": "TGFB/TGFBR_complex", + "source": "MAPK3", "target": "SMAD2/3_complex", "sign": true }, { "id": "t10", - "source": "Orf3a", + "source": "ACVR1", "target": "SMAD2/3_complex", "sign": true }, @@ -273,13 +273,13 @@ }, { "id": "t13", - "source": "MAPK3", + "source": "Orf3a", "target": "SMAD2/3_complex", "sign": true }, { "id": "t14", - "source": "ACVR1", + "source": "Nsp7b_default_compartment", "target": "SMAD2/3_complex", "sign": true }, @@ -291,37 +291,37 @@ }, { "id": "t16", - "source": "LTBP1", + "source": "BAMBI", "target": "TGFB/TGFBR_complex", "sign": true }, { "id": "t17", - "source": "BAMBI", + "source": "LTBP1", "target": "TGFB/TGFBR_complex", "sign": true }, { "id": "t18", - "source": "TGFB/TGFBR_complex", + "source": "Orf7a", "target": "PP2A_complex", "sign": true }, { "id": "t19", - "source": "Orf7a", + "source": "TGFB/TGFBR_complex", "target": "PP2A_complex", "sign": true }, { "id": "t20", - "source": "TGFB/TGFBR_complex", + "source": "Nsp7", "target": "RHOA", "sign": true }, { "id": "t21", - "source": "Nsp7", + "source": "TGFB/TGFBR_complex", "target": "RHOA", "sign": true }, diff --git a/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json b/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json index a3622c02a..d976ee828 100644 --- a/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json +++ b/scripts/covid19_diseasemaps/regnet_amr_sbml/Virus_replication_cycle.json @@ -1947,13 +1947,13 @@ "edges": [ { "id": "t1", - "source": "Nsp10", + "source": "Nsp16", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t2", - "source": "Nsp3", + "source": "Nsp9", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, @@ -1965,37 +1965,37 @@ }, { "id": "t4", - "source": "Nsp4_endoplasmic reticulum", + "source": "Nsp3", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t5", - "source": "Nsp14", + "source": "Nsp7", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t6", - "source": "Nsp16", + "source": "Nsp14", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t7", - "source": "Nsp13", + "source": "Nsp6_endoplasmic reticulum", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t8", - "source": "Nsp7", + "source": "Nsp10", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t9", - "source": "Nsp9", + "source": "Nsp8", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, @@ -2007,31 +2007,31 @@ }, { "id": "t11", - "source": "Nsp15", + "source": "Nsp4_endoplasmic reticulum", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t12", - "source": "Nsp6_endoplasmic reticulum", + "source": "Nsp15", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t13", - "source": "Nsp8", + "source": "Nsp13", "target": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "sign": true }, { "id": "t14", - "source": "S_SARS-CoV-2_space_virion", + "source": "ACE2_epithelial_space_cell", "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t15", - "source": "ACE2_epithelial_space_cell", + "source": "S_SARS-CoV-2_space_virion", "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, @@ -2043,55 +2043,55 @@ }, { "id": "t17", - "source": "S1:NRP1_space_complex_complex", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t18", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "E_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t19", - "source": "S2_SARS-CoV-2_space_virion", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t20", - "source": "cholesterol_simple_molecule", + "source": "S2_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t21", - "source": "S2_epithelial_space_cell", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t22", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t23", - "source": "M_SARS-CoV-2_space_virion", + "source": "cholesterol_simple_molecule", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t24", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_epithelial_space_cell", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, { "id": "t25", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "S1:NRP1_space_complex_complex", "target": "Nucleocapsid_complex_epithelial_space_cell", "sign": true }, @@ -2103,13 +2103,13 @@ }, { "id": "t27", - "source": "S1_default_compartment", + "source": "NRP1", "target": "S1:NRP1_space_complex_complex", "sign": true }, { "id": "t28", - "source": "NRP1", + "source": "S1_default_compartment", "target": "S1:NRP1_space_complex_complex", "sign": true }, @@ -2127,13 +2127,13 @@ }, { "id": "t31", - "source": "S_SARS-CoV-2_space_virion", + "source": "ACE2_epithelial_space_cell", "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, { "id": "t32", - "source": "ACE2_epithelial_space_cell", + "source": "S_SARS-CoV-2_space_virion", "target": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "sign": true }, @@ -2193,13 +2193,13 @@ }, { "id": "t42", - "source": "SIGMAR1_endoplasmic reticulum", + "source": "SARS-CoV2 candidate drugs_complex", "target": "SIGMAR1: drug complex_complex", "sign": true }, { "id": "t43", - "source": "SARS-CoV2 candidate drugs_complex", + "source": "SIGMAR1_endoplasmic reticulum", "target": "SIGMAR1: drug complex_complex", "sign": true }, @@ -2271,25 +2271,25 @@ }, { "id": "t55", - "source": "Selinexor_drug", + "source": "NUP210_endoplasmic reticulum", "target": "NUP210:Selinexor_complex", "sign": true }, { "id": "t56", - "source": "NUP210_endoplasmic reticulum", + "source": "Selinexor_drug", "target": "NUP210:Selinexor_complex", "sign": true }, { "id": "t57", - "source": "Nsp6_epithelial_space_cell", + "source": "SIGMAR1_endoplasmic reticulum", "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "sign": true }, { "id": "t58", - "source": "SIGMAR1_endoplasmic reticulum", + "source": "Nsp6_epithelial_space_cell", "target": "Nsp6:SIGMAR1_complex_endoplasmic reticulum", "sign": true }, @@ -2319,37 +2319,37 @@ }, { "id": "t63", - "source": "Ca+2_simple_molecule", + "source": "RAB7A", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t64", - "source": "RAB7A", + "source": "ARL8B", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t65", - "source": "ARL8B", + "source": "Ca+2_simple_molecule", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t66", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "RAB7A", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t67", - "source": "RAB7A", + "source": "ARL8B", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, { "id": "t68", - "source": "ARL8B", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "sign": true }, @@ -2373,13 +2373,13 @@ }, { "id": "t72", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t73", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -2391,13 +2391,13 @@ }, { "id": "t75", - "source": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf9b_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t76", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Orf9b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf9b_space_ds_space_sgmRNA_rna", "sign": true }, @@ -2415,13 +2415,13 @@ }, { "id": "t79", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t80", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -2433,13 +2433,13 @@ }, { "id": "t82", - "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "source": "E (+)ss sgmRNA_rna_epithelial_space_cell", "target": "E_rough_space_endoplasmic_space_reticulum", "sign": true }, { "id": "t83", - "source": "E (+)ss sgmRNA_rna_epithelial_space_cell", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "E_rough_space_endoplasmic_space_reticulum", "sign": true }, @@ -2451,13 +2451,13 @@ }, { "id": "t85", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t86", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "M_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -2511,25 +2511,25 @@ }, { "id": "t95", - "source": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "E_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t96", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "E_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t97", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t98", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -2559,19 +2559,19 @@ }, { "id": "t103", - "source": "pp1a_space_Nsp6-11", + "source": "pp1ab_space_nsp6-16", "target": "Nsp7", "sign": true }, { "id": "t104", - "source": "pp1ab_space_nsp6-16", + "source": "Nsp5_endoplasmic reticulum", "target": "Nsp7", "sign": true }, { "id": "t105", - "source": "Nsp5_endoplasmic reticulum", + "source": "pp1a_space_Nsp6-11", "target": "Nsp7", "sign": true }, @@ -2637,13 +2637,13 @@ }, { "id": "t116", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "ds_space_gRNA_rna", "sign": true }, { "id": "t117", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "ds_space_gRNA_rna", "sign": true }, @@ -2661,25 +2661,25 @@ }, { "id": "t120", - "source": "Camostat_space_mesylate_drug", + "source": "FURIN", "target": "S2_epithelial_space_cell", "sign": true }, { "id": "t121", - "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "TMPRSS2", "target": "S2_epithelial_space_cell", "sign": true }, { "id": "t122", - "source": "FURIN", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "target": "S2_epithelial_space_cell", "sign": true }, { "id": "t123", - "source": "TMPRSS2", + "source": "Camostat_space_mesylate_drug", "target": "S2_epithelial_space_cell", "sign": true }, @@ -2697,43 +2697,43 @@ }, { "id": "t126", - "source": "Camostat_space_mesylate_drug", + "source": "FURIN", "target": "ACE2_epithelial_space_cell", "sign": true }, { "id": "t127", - "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "TMPRSS2", "target": "ACE2_epithelial_space_cell", "sign": true }, { "id": "t128", - "source": "FURIN", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "target": "ACE2_epithelial_space_cell", "sign": true }, { "id": "t129", - "source": "TMPRSS2", + "source": "Camostat_space_mesylate_drug", "target": "ACE2_epithelial_space_cell", "sign": true }, { "id": "t130", - "source": "pp1a_space_Nsp6-11", + "source": "pp1ab_space_nsp6-16", "target": "Nsp10", "sign": true }, { "id": "t131", - "source": "pp1ab_space_nsp6-16", + "source": "Nsp5_endoplasmic reticulum", "target": "Nsp10", "sign": true }, { "id": "t132", - "source": "Nsp5_endoplasmic reticulum", + "source": "pp1a_space_Nsp6-11", "target": "Nsp10", "sign": true }, @@ -2745,61 +2745,61 @@ }, { "id": "t134", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "E_SARS-CoV-2_space_virion", "target": "Orf7a_endosome", "sign": true }, { "id": "t135", - "source": "S2_SARS-CoV-2_space_virion", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "Orf7a_endosome", "sign": true }, { "id": "t136", - "source": "M_SARS-CoV-2_space_virion", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "Orf7a_endosome", "sign": true }, { "id": "t137", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_SARS-CoV-2_space_virion", "target": "Orf7a_endosome", "sign": true }, { "id": "t138", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "Orf7a_endosome", "sign": true }, { "id": "t139", - "source": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf7b_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t140", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Orf7b_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf7b_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t141", - "source": "N_space_space_(-)ss_space_sgmRNA_rna", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "N_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t142", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "N_space_space_(-)ss_space_sgmRNA_rna", "target": "N_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t143", - "source": "pp1a_space_Nsp6-11", + "source": "pp1ab_space_nsp6-16", "target": "Nsp9", "sign": true }, @@ -2811,7 +2811,7 @@ }, { "id": "t145", - "source": "pp1ab_space_nsp6-16", + "source": "pp1a_space_Nsp6-11", "target": "Nsp9", "sign": true }, @@ -2823,13 +2823,13 @@ }, { "id": "t147", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "N_space_space_(-)ss_space_sgmRNA_rna", "sign": true }, { "id": "t148", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "N_space_space_(-)ss_space_sgmRNA_rna", "sign": true }, @@ -2895,43 +2895,43 @@ }, { "id": "t159", - "source": "S1:NRP1_space_complex_complex", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t160", - "source": "cholesterol_simple_molecule", + "source": "E_SARS-CoV-2_space_virion", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t161", - "source": "S2_epithelial_space_cell", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t162", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t163", - "source": "M_SARS-CoV-2_space_virion", + "source": "cholesterol_simple_molecule", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t164", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_epithelial_space_cell", "target": "Orf7a_epithelial_space_cell", "sign": true }, { "id": "t165", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "S1:NRP1_space_complex_complex", "target": "Orf7a_epithelial_space_cell", "sign": true }, @@ -2955,13 +2955,13 @@ }, { "id": "t169", - "source": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf6_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t170", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf6_space_ds_space_sgmRNA_rna", "sign": true }, @@ -2979,7 +2979,7 @@ }, { "id": "t173", - "source": "pp1a_space_Nsp6-11", + "source": "pp1ab_space_nsp6-16", "target": "Nsp8", "sign": true }, @@ -2991,7 +2991,7 @@ }, { "id": "t175", - "source": "pp1ab_space_nsp6-16", + "source": "pp1a_space_Nsp6-11", "target": "Nsp8", "sign": true }, @@ -3003,7 +3003,7 @@ }, { "id": "t177", - "source": "pp1a_space_Nsp6-11", + "source": "pp1ab_space_nsp6-16", "target": "Nsp6_endoplasmic reticulum", "sign": true }, @@ -3015,7 +3015,7 @@ }, { "id": "t179", - "source": "pp1ab_space_nsp6-16", + "source": "pp1a_space_Nsp6-11", "target": "Nsp6_endoplasmic reticulum", "sign": true }, @@ -3051,19 +3051,19 @@ }, { "id": "t185", - "source": "Nucleocapsid_complex_epithelial_space_cell", + "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", "target": "N_epithelial_space_cell", "sign": true }, { "id": "t186", - "source": "Host_space_translation_space_complex_complex_epithelial_space_cell", + "source": "N (+)ss sgmRNA_rna_epithelial_space_cell", "target": "N_epithelial_space_cell", "sign": true }, { "id": "t187", - "source": "N (+)ss sgmRNA_rna_epithelial_space_cell", + "source": "Nucleocapsid_complex_epithelial_space_cell", "target": "N_epithelial_space_cell", "sign": true }, @@ -3075,13 +3075,13 @@ }, { "id": "t189", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t190", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "S_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -3105,37 +3105,37 @@ }, { "id": "t194", - "source": "Camostat_space_mesylate_drug", + "source": "FURIN", "target": "ACE2_default_compartment", "sign": true }, { "id": "t195", - "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "TMPRSS2", "target": "ACE2_default_compartment", "sign": true }, { "id": "t196", - "source": "FURIN", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "target": "ACE2_default_compartment", "sign": true }, { "id": "t197", - "source": "TMPRSS2", + "source": "Camostat_space_mesylate_drug", "target": "ACE2_default_compartment", "sign": true }, { "id": "t198", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t199", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf8_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -3153,31 +3153,31 @@ }, { "id": "t202", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "E_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, { "id": "t203", - "source": "S2_SARS-CoV-2_space_virion", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, { "id": "t204", - "source": "M_SARS-CoV-2_space_virion", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, { "id": "t205", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, { "id": "t206", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "E_endosome", "sign": true }, @@ -3189,19 +3189,19 @@ }, { "id": "t208", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t209", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf6_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t210", - "source": "CTSB", + "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", "target": "S2_SARS-CoV-2_space_virion", "sign": true }, @@ -3213,37 +3213,37 @@ }, { "id": "t212", - "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", + "source": "CTSB", "target": "S2_SARS-CoV-2_space_virion", "sign": true }, { "id": "t213", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "E_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, { "id": "t214", - "source": "S2_SARS-CoV-2_space_virion", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, { "id": "t215", - "source": "M_SARS-CoV-2_space_virion", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, { "id": "t216", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, { "id": "t217", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "M_endosome", "sign": true }, @@ -3273,49 +3273,49 @@ }, { "id": "t222", - "source": "Camostat_space_mesylate_drug", + "source": "FURIN", "target": "S1_default_compartment", "sign": true }, { "id": "t223", - "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", + "source": "TMPRSS2", "target": "S1_default_compartment", "sign": true }, { "id": "t224", - "source": "FURIN", + "source": "ACE2:SPIKE_space_complex_complex_epithelial_space_cell", "target": "S1_default_compartment", "sign": true }, { "id": "t225", - "source": "TMPRSS2", + "source": "Camostat_space_mesylate_drug", "target": "S1_default_compartment", "sign": true }, { "id": "t226", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t227", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "E_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t228", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t229", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf14_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -3333,121 +3333,121 @@ }, { "id": "t232", - "source": "S1:NRP1_space_complex_complex", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t233", - "source": "cholesterol_simple_molecule", + "source": "E_SARS-CoV-2_space_virion", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t234", - "source": "S2_epithelial_space_cell", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t235", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t236", - "source": "M_SARS-CoV-2_space_virion", + "source": "cholesterol_simple_molecule", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t237", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_epithelial_space_cell", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t238", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "S1:NRP1_space_complex_complex", "target": "M_epithelial_space_cell", "sign": true }, { "id": "t239", - "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "source": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", "target": "Orf7b_rough_space_endoplasmic_space_reticulum", "sign": true }, { "id": "t240", - "source": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf7b_rough_space_endoplasmic_space_reticulum", "sign": true }, { "id": "t241", - "source": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf7a_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t242", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf7a_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t243", - "source": "pp1a_space_Nsp6-11", + "source": "Nsp5_endoplasmic reticulum", "target": "Nsp11", "sign": true }, { "id": "t244", - "source": "Nsp5_endoplasmic reticulum", + "source": "pp1a_space_Nsp6-11", "target": "Nsp11", "sign": true }, { "id": "t245", - "source": "S1:NRP1_space_complex_complex", + "source": "Orf7a_SARS-CoV-2_space_virion", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t246", - "source": "cholesterol_simple_molecule", + "source": "E_SARS-CoV-2_space_virion", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t247", - "source": "S2_epithelial_space_cell", + "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t248", - "source": "Nucleocapsid_complex_SARS-CoV-2_space_virion", + "source": "M_SARS-CoV-2_space_virion", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t249", - "source": "M_SARS-CoV-2_space_virion", + "source": "cholesterol_simple_molecule", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t250", - "source": "E_SARS-CoV-2_space_virion", + "source": "S2_epithelial_space_cell", "target": "E_epithelial_space_cell", "sign": true }, { "id": "t251", - "source": "Orf7a_SARS-CoV-2_space_virion", + "source": "S1:NRP1_space_complex_complex", "target": "E_epithelial_space_cell", "sign": true }, @@ -3459,7 +3459,7 @@ }, { "id": "t253", - "source": "CTSB", + "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", "target": "S1_endosome", "sign": true }, @@ -3471,7 +3471,7 @@ }, { "id": "t255", - "source": "ACE2:SPIKE_space_complex_complex_SARS-CoV-2_space_virion", + "source": "CTSB", "target": "S1_endosome", "sign": true }, @@ -3495,13 +3495,13 @@ }, { "id": "t259", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t260", - "source": "(-)ss_space_gRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf7a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "sign": true }, @@ -3543,13 +3543,13 @@ }, { "id": "t267", - "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", + "source": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", "target": "Orf8_rough_space_endoplasmic_space_reticulum", "sign": true }, { "id": "t268", - "source": "Orf8 (+)ss sgmRNA_rna_epithelial_space_cell", + "source": "Host_space_translation_space_complex_complex_rough_space_endoplasmic_space_reticulum", "target": "Orf8_rough_space_endoplasmic_space_reticulum", "sign": true }, @@ -3591,13 +3591,13 @@ }, { "id": "t275", - "source": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", + "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf3a_space_ds_space_sgmRNA_rna", "sign": true }, { "id": "t276", - "source": "Replication_space_transcription_space_complex_complex_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "Orf3a_space_(-)ss_space_sgmRNA_rna_epithelial_space_cell", "target": "Orf3a_space_ds_space_sgmRNA_rna", "sign": true }, @@ -3645,19 +3645,19 @@ }, { "id": "t284", - "source": "Nsp3", + "source": "Nsp6_endoplasmic reticulum", "target": "double membrane vesicle viral factory assembly_phenotype", "sign": true }, { "id": "t285", - "source": "Nsp4_endoplasmic reticulum", + "source": "Nsp3", "target": "double membrane vesicle viral factory assembly_phenotype", "sign": true }, { "id": "t286", - "source": "Nsp6_endoplasmic reticulum", + "source": "Nsp4_endoplasmic reticulum", "target": "double membrane vesicle viral factory assembly_phenotype", "sign": true }, @@ -3855,13 +3855,13 @@ }, { "id": "t319", - "source": "Orf7b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", + "source": "DMV molecular pore_complex", "target": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, { "id": "t320", - "source": "DMV molecular pore_complex", + "source": "Orf7b (+)ss sgmRNA_rna_double_space_membrane_space_vesicle_space_viral_space_factory", "target": "Orf7b (+)ss sgmRNA_rna_epithelial_space_cell", "sign": true }, From 5d475d1a7a40c7196cc0991a67c1985751aa9610 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Thu, 25 Apr 2024 14:57:22 -0400 Subject: [PATCH 41/44] Rerun hackathon and evaluation notebooks to regenerate regnet amrs with all upstream controllers listed --- .../epi_scenario5/epi_scenario5.ipynb | 29 ++-- .../epi_scenario5/scenario5_regnet.json | 161 +++++++++++------- .../scenario6/scenario6.ipynb | 67 ++++---- .../scenario6/scenario6_chen_regnet.json | 60 +++---- .../scenario6/scenario6_hunt_regnet.json | 74 +++++--- 5 files changed, 232 insertions(+), 159 deletions(-) diff --git a/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb b/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb index da709e512..422e8a728 100644 --- a/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb +++ b/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb @@ -10,13 +10,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 21, "id": "d3b46cfa", "metadata": {}, "outputs": [], "source": [ "import numpy\n", "import matplotlib.pyplot as plt\n", + "import json\n", "\n", "from mira.metamodel import *\n", "from mira.modeling import Model\n", @@ -35,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 22, "id": "8efb8e6b", "metadata": {}, "outputs": [], @@ -63,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 23, "id": "4be2a9c7", "metadata": {}, "outputs": [], @@ -102,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 24, "id": "3bf62177", "metadata": {}, "outputs": [], @@ -116,7 +117,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 25, "id": "fff395d8", "metadata": {}, "outputs": [], @@ -146,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 26, "id": "b38d4412", "metadata": {}, "outputs": [], @@ -166,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 27, "id": "e398426e", "metadata": {}, "outputs": [ @@ -190,7 +191,7 @@ "[ p[9, 0]*y[9, 0] - p[10, 0]*y[3, 0]*y[10, 0] - p[15, 0]*y[10, 0]]])" ] }, - "execution_count": 7, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -202,7 +203,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 28, "id": "eff2ac28", "metadata": {}, "outputs": [], @@ -213,7 +214,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 29, "id": "f8742e84", "metadata": {}, "outputs": [ @@ -223,13 +224,13 @@ "Text(0, 0.5, '# Molecules / cell')" ] }, - "execution_count": 9, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -257,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 30, "id": "a1d9cfef", "metadata": {}, "outputs": [], @@ -286,7 +287,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json b/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json index 0a21ae62c..d5a9fc130 100644 --- a/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json +++ b/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json @@ -155,211 +155,241 @@ }, { "id": "t4", + "source": "Lactose", + "target": "I_Lactose", + "sign": true, + "properties": { + "name": "t4", + "rate_constant": "k_3" + } + }, + { + "id": "t5", "source": "I", "target": "Lactose", "sign": false, "properties": { - "name": "t4", + "name": "t5", "rate_constant": "k_3" } }, { - "id": "t5", + "id": "t6", "source": "Lactose", "target": "I", "sign": false, "properties": { - "name": "t5", + "name": "t6", "rate_constant": "k_3" } }, { - "id": "t6", + "id": "t7", "source": "I_Lactose", "target": "I", "sign": true, "properties": { - "name": "t6", + "name": "t7", "rate_constant": "k_4" } }, { - "id": "t7", + "id": "t8", "source": "I_Lactose", "target": "Lactose", "sign": true, "properties": { - "name": "t7", + "name": "t8", "rate_constant": "k_4" } }, { - "id": "t8", + "id": "t9", "source": "I", "target": "I_Op", "sign": true, "properties": { - "name": "t8", + "name": "t9", "rate_constant": "k_5" } }, { - "id": "t9", + "id": "t10", + "source": "Op", + "target": "I_Op", + "sign": true, + "properties": { + "name": "t10", + "rate_constant": "k_5" + } + }, + { + "id": "t11", "source": "I", "target": "Op", "sign": false, "properties": { - "name": "t9", + "name": "t11", "rate_constant": "k_5" } }, { - "id": "t10", + "id": "t12", "source": "Op", "target": "I", "sign": false, "properties": { - "name": "t10", + "name": "t12", "rate_constant": "k_5" } }, { - "id": "t11", + "id": "t13", "source": "I_Op", "target": "I", "sign": true, "properties": { - "name": "t11", + "name": "t13", "rate_constant": "k_6" } }, { - "id": "t12", + "id": "t14", "source": "I_Op", "target": "Op", "sign": true, "properties": { - "name": "t12", + "name": "t14", "rate_constant": "k_6" } }, { - "id": "t13", + "id": "t15", + "source": "RNAP", + "target": "RNAP_Op", + "sign": true, + "properties": { + "name": "t15", + "rate_constant": "k_7" + } + }, + { + "id": "t16", "source": "Op", "target": "RNAP_Op", "sign": true, "properties": { - "name": "t13", + "name": "t16", "rate_constant": "k_7" } }, { - "id": "t14", + "id": "t17", "source": "RNAP", "target": "Op", "sign": false, "properties": { - "name": "t14", + "name": "t17", "rate_constant": "k_7" } }, { - "id": "t15", + "id": "t18", "source": "Op", "target": "RNAP", "sign": false, "properties": { - "name": "t15", + "name": "t18", "rate_constant": "k_7" } }, { - "id": "t16", + "id": "t19", "source": "RNAP_Op", "target": "RNAP", "sign": true, "properties": { - "name": "t16", + "name": "t19", "rate_constant": "k_8" } }, { - "id": "t17", + "id": "t20", "source": "RNAP_Op", "target": "Op", "sign": true, "properties": { - "name": "t17", + "name": "t20", "rate_constant": "k_8" } }, { - "id": "t18", + "id": "t21", "source": "RNAP_Op", "target": "RNAP", "sign": true, "properties": { - "name": "t18", + "name": "t21", "rate_constant": "k_9" } }, { - "id": "t19", + "id": "t22", "source": "RNAP_Op", "target": "Op", "sign": true, "properties": { - "name": "t19", + "name": "t22", "rate_constant": "k_9" } }, { - "id": "t20", + "id": "t23", "source": "RNAP_Op", "target": "r_lac", "sign": true, "properties": { - "name": "t20", + "name": "t23", "rate_constant": "k_9" } }, { - "id": "t21", + "id": "t24", "source": "r_lac", "target": "Z", "sign": true, "properties": { - "name": "t21", + "name": "t24", "rate_constant": "k_10" } }, { - "id": "t22", + "id": "t25", "source": "Z", "target": "Lactose", "sign": false, "properties": { - "name": "t22", + "name": "t25", "rate_constant": "k_11" } }, { - "id": "t23", + "id": "t26", "source": "Lactose", "target": "Z", "sign": false, "properties": { - "name": "t23", + "name": "t26", "rate_constant": "k_11" } }, { - "id": "t24", + "id": "t27", "source": "I_Lactose", "target": "Lactose", "sign": true, "properties": { - "name": "t24", + "name": "t27", "rate_constant": "k_14" } } @@ -461,8 +491,8 @@ }, { "target": "t6", - "expression": "I_Lactose*k_4", - "expression_mathml": "I_Lactosek_4" + "expression": "I*Lactose*k_3", + "expression_mathml": "ILactosek_3" }, { "target": "t7", @@ -471,8 +501,8 @@ }, { "target": "t8", - "expression": "I*Op*k_5", - "expression_mathml": "IOpk_5" + "expression": "I_Lactose*k_4", + "expression_mathml": "I_Lactosek_4" }, { "target": "t9", @@ -486,71 +516,86 @@ }, { "target": "t11", + "expression": "I*Op*k_5", + "expression_mathml": "IOpk_5" + }, + { + "target": "t12", + "expression": "I*Op*k_5", + "expression_mathml": "IOpk_5" + }, + { + "target": "t13", "expression": "I_Op*k_6", "expression_mathml": "I_Opk_6" }, { - "target": "t12", + "target": "t14", "expression": "I_Op*k_6", "expression_mathml": "I_Opk_6" }, { - "target": "t13", + "target": "t15", "expression": "Op*RNAP*k_7", "expression_mathml": "OpRNAPk_7" }, { - "target": "t14", + "target": "t16", "expression": "Op*RNAP*k_7", "expression_mathml": "OpRNAPk_7" }, { - "target": "t15", + "target": "t17", "expression": "Op*RNAP*k_7", "expression_mathml": "OpRNAPk_7" }, { - "target": "t16", + "target": "t18", + "expression": "Op*RNAP*k_7", + "expression_mathml": "OpRNAPk_7" + }, + { + "target": "t19", "expression": "RNAP_Op*k_8", "expression_mathml": "RNAP_Opk_8" }, { - "target": "t17", + "target": "t20", "expression": "RNAP_Op*k_8", "expression_mathml": "RNAP_Opk_8" }, { - "target": "t18", + "target": "t21", "expression": "RNAP_Op*k_9", "expression_mathml": "RNAP_Opk_9" }, { - "target": "t19", + "target": "t22", "expression": "RNAP_Op*k_9", "expression_mathml": "RNAP_Opk_9" }, { - "target": "t20", + "target": "t23", "expression": "RNAP_Op*k_9", "expression_mathml": "RNAP_Opk_9" }, { - "target": "t21", + "target": "t24", "expression": "k_10*r_lac", "expression_mathml": "k_10r_lac" }, { - "target": "t22", + "target": "t25", "expression": "Lactose*Z*k_11", "expression_mathml": "LactoseZk_11" }, { - "target": "t23", + "target": "t26", "expression": "Lactose*Z*k_11", "expression_mathml": "LactoseZk_11" }, { - "target": "t24", + "target": "t27", "expression": "I_Lactose*k_14", "expression_mathml": "I_Lactosek_14" }, diff --git a/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb b/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb index 27eff4d0a..5fbf56f33 100644 --- a/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb +++ b/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 52, "id": "0606e469", "metadata": {}, "outputs": [], @@ -10,6 +10,7 @@ "import numpy\n", "import sympy\n", "import matplotlib.pyplot as plt\n", + "import json\n", "\n", "from mira.metamodel import *\n", "from mira.modeling import Model\n", @@ -21,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 53, "id": "d61ac405", "metadata": {}, "outputs": [], @@ -55,18 +56,18 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 54, "id": "85dc41a5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "" ] }, - "execution_count": 3, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } @@ -77,7 +78,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 55, "id": "4c52e0e5", "metadata": {}, "outputs": [], @@ -98,18 +99,18 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 56, "id": "52e3c60a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "" ] }, - "execution_count": 5, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -120,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 57, "id": "e6662e8a", "metadata": {}, "outputs": [], @@ -144,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 58, "id": "0e97938e", "metadata": {}, "outputs": [], @@ -154,7 +155,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 59, "id": "1502c3a1", "metadata": {}, "outputs": [], @@ -165,11 +166,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 60, "id": "dde3bf5e", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -184,13 +183,13 @@ "Text(0, 0.5, 'Proportion')" ] }, - "execution_count": 9, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -210,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 61, "id": "2163ce1b", "metadata": { "scrolled": true @@ -231,7 +230,7 @@ "[ 2.0*y[2, 0] - 0.015*y[5, 0]]])" ] }, - "execution_count": 10, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -274,7 +273,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 62, "id": "fdd87873-aa57-4b0a-9725-e4a8ea5a5226", "metadata": {}, "outputs": [ @@ -312,7 +311,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 63, "id": "98b731de", "metadata": {}, "outputs": [ @@ -372,7 +371,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 64, "id": "e18ce097", "metadata": {}, "outputs": [], @@ -387,7 +386,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 65, "id": "ebb2f408", "metadata": {}, "outputs": [], @@ -408,18 +407,18 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 66, "id": "d4797e40", "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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", "text/plain": [ "" ] }, - "execution_count": 15, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } @@ -430,11 +429,9 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 67, "id": "990374cb", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -449,13 +446,13 @@ "Text(0, 0.5, 'Proportion')" ] }, - "execution_count": 16, + "execution_count": 67, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -477,7 +474,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 68, "id": "3a5c3e3a", "metadata": {}, "outputs": [], @@ -508,7 +505,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/notebooks/hackathon_2024.02/scenario6/scenario6_chen_regnet.json b/notebooks/hackathon_2024.02/scenario6/scenario6_chen_regnet.json index f2e9b9e92..ed15f71e8 100644 --- a/notebooks/hackathon_2024.02/scenario6/scenario6_chen_regnet.json +++ b/notebooks/hackathon_2024.02/scenario6/scenario6_chen_regnet.json @@ -203,21 +203,6 @@ "semantics": { "ode": { "rates": [ - { - "target": "r_1", - "expression": "V_0*r_1", - "expression_mathml": "V_0r_1" - }, - { - "target": "r_2", - "expression": "V_1*r_2", - "expression_mathml": "V_1r_2" - }, - { - "target": "r_3", - "expression": "V_2*r_3", - "expression_mathml": "V_2r_3" - }, { "target": "t1", "expression": "L_0*r_1", @@ -233,21 +218,6 @@ "expression": "L_2*r_3", "expression_mathml": "L_2r_3" }, - { - "target": "p_1", - "expression": "U_0*p_1", - "expression_mathml": "U_0p_1" - }, - { - "target": "p_2", - "expression": "U_1*p_2", - "expression_mathml": "U_1p_2" - }, - { - "target": "p_3", - "expression": "U_2*p_3", - "expression_mathml": "U_2p_3" - }, { "target": "t4", "expression": "C_0*p_1", @@ -262,6 +232,36 @@ "target": "t6", "expression": "C_2*p_1", "expression_mathml": "C_2p_1" + }, + { + "target": "r_1", + "expression": "V_0*r_1", + "expression_mathml": "V_0r_1" + }, + { + "target": "r_2", + "expression": "V_1*r_2", + "expression_mathml": "V_1r_2" + }, + { + "target": "r_3", + "expression": "V_2*r_3", + "expression_mathml": "V_2r_3" + }, + { + "target": "p_1", + "expression": "U_0*p_1", + "expression_mathml": "U_0p_1" + }, + { + "target": "p_2", + "expression": "U_1*p_2", + "expression_mathml": "U_1p_2" + }, + { + "target": "p_3", + "expression": "U_2*p_3", + "expression_mathml": "U_2p_3" } ], "observables": [], diff --git a/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json b/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json index b1fa6dc36..4b9079ad3 100644 --- a/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json +++ b/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json @@ -114,7 +114,7 @@ }, { "id": "t4", - "source": "p_1", + "source": "p_2", "target": "r_2", "sign": true, "properties": { @@ -124,51 +124,71 @@ }, { "id": "t5", + "source": "p_1", + "target": "r_2", + "sign": true, + "properties": { + "name": "t5", + "rate_constant": "C_1" + } + }, + { + "id": "t6", "source": "p_2", "target": "r_2", "sign": false, "properties": { - "name": "t5", + "name": "t6", "rate_constant": "V_1" } }, { - "id": "t6", + "id": "t7", "source": "r_2", "target": "p_2", "sign": true, "properties": { - "name": "t6", + "name": "t7", "rate_constant": "L_1" } }, { - "id": "t7", + "id": "t8", "source": "p_1", "target": "r_3", "sign": true, "properties": { - "name": "t7", + "name": "t8", "rate_constant": "C_2" } }, { - "id": "t8", + "id": "t9", + "source": "p_3", + "target": "r_3", + "sign": true, + "properties": { + "name": "t9", + "rate_constant": "C_2" + } + }, + { + "id": "t10", "source": "p_2", "target": "r_3", "sign": false, "properties": { - "name": "t8", + "name": "t10", "rate_constant": "V_2" } }, { - "id": "t9", + "id": "t11", "source": "r_3", "target": "p_3", "sign": true, "properties": { - "name": "t9", + "name": "t11", "rate_constant": "L_2" } } @@ -278,11 +298,6 @@ "expression": "L_0*r_1/(1 + p_1/d_0)", "expression_mathml": "L_0r_11p_1d_0" }, - { - "target": "p_1", - "expression": "U_0*p_1", - "expression_mathml": "U_0p_1" - }, { "target": "t4", "expression": "C_1*p_1/(1 + p_2/a_1)", @@ -290,34 +305,49 @@ }, { "target": "t5", + "expression": "C_1*p_1/(1 + p_2/a_1)", + "expression_mathml": "C_1p_11p_2a_1" + }, + { + "target": "t6", "expression": "V_1*r_2/(1 + p_2/b_1)", "expression_mathml": "V_1r_21p_2b_1" }, { - "target": "t6", + "target": "t7", "expression": "L_1*r_2/(1 + p_2/d_1)", "expression_mathml": "L_1r_21p_2d_1" }, { - "target": "p_2", - "expression": "U_1*p_2", - "expression_mathml": "U_1p_2" + "target": "t8", + "expression": "C_2*p_1/(1 + p_3/a_2)", + "expression_mathml": "C_2p_11p_3a_2" }, { - "target": "t7", + "target": "t9", "expression": "C_2*p_1/(1 + p_3/a_2)", "expression_mathml": "C_2p_11p_3a_2" }, { - "target": "t8", + "target": "t10", "expression": "V_2*r_3/(1 + p_2/b_2)", "expression_mathml": "V_2r_31p_2b_2" }, { - "target": "t9", + "target": "t11", "expression": "L_2*r_3/(1 + p_3/d_2)", "expression_mathml": "L_2r_31p_3d_2" }, + { + "target": "p_1", + "expression": "U_0*p_1", + "expression_mathml": "U_0p_1" + }, + { + "target": "p_2", + "expression": "U_1*p_2", + "expression_mathml": "U_1p_2" + }, { "target": "p_3", "expression": "U_2*p_3", From 645816a8cb0e3bf3a14fd9739fee113d45f55ced Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 26 Apr 2024 10:04:34 -0400 Subject: [PATCH 42/44] Set duplicate rates from the same transition to 0, regenerate affected regnet amrs --- mira/modeling/amr/regnet.py | 18 ++++++++++++++---- .../epi_scenario5/scenario5_regnet.json | 16 ++++++++-------- .../scenario6/scenario6_hunt_regnet.json | 12 ++++++------ 3 files changed, 28 insertions(+), 18 deletions(-) diff --git a/mira/modeling/amr/regnet.py b/mira/modeling/amr/regnet.py index 6dcdb65ed..bf128d0eb 100644 --- a/mira/modeling/amr/regnet.py +++ b/mira/modeling/amr/regnet.py @@ -149,12 +149,13 @@ def __init__(self, model: Model): if not indep_ctrl: indep_ctrl = {transition.produced[0].key} - for controller in indep_ctrl: + for index, controller in enumerate(indep_ctrl): self.create_edge( transition, vmap[controller], vmap[transition.produced[0].key], edge_id, + False if index == 0 else True ) edge_id += 1 @@ -168,12 +169,13 @@ def __init__(self, model: Model): if not indep_ctrl: indep_ctrl = {transition.consumed[0].key} - for controller in indep_ctrl: + for index, controller in enumerate(indep_ctrl): self.create_edge( transition, vmap[controller], vmap[transition.consumed[0].key], edge_id, + False if index == 0 else True ) edge_id += 1 @@ -190,6 +192,7 @@ def __init__(self, model: Model): vmap[transition.control[0].key], target, edge_id, + False ) edge_id += 1 @@ -243,7 +246,7 @@ def __init__(self, model: Model): self.time = None add_metadata_annotations(self.metadata, model) - def create_edge(self, transition, source, target, edge_id): + def create_edge(self, transition, source, target, edge_id, duplicate): """Create and append a transition dictionary to the list of transitions Parameters @@ -256,6 +259,10 @@ def create_edge(self, transition, source, target, edge_id): The name of the target of the transition edge_id : int The id to assign to the transition + duplicate : bool + A boolean that tells us whether the transition we are processing has already been + processed at least once. This is for the purpose of not adding duplicate rate laws + to the output amr. """ tid = f"t{edge_id}" transition_dict = {"id": tid} @@ -265,8 +272,11 @@ def create_edge(self, transition, source, target, edge_id): transition.template ) or is_replication(transition.template) + # if transition.template.rate_law: - rate_law = transition.template.rate_law.args[0] + # If we are processing a duplicate rate, set the rate to 0 + rate_law = transition.template.rate_law.args[0] if not duplicate \ + else safe_parse_expr('0') pnames = transition.template.get_parameter_names() # We just choose an arbitrary one deterministically rate_const = sorted(pnames)[0] if pnames else None diff --git a/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json b/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json index d5a9fc130..2cde7b44f 100644 --- a/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json +++ b/notebooks/evaluation_2024.03/epi_scenario5/scenario5_regnet.json @@ -145,7 +145,7 @@ }, { "id": "t3", - "source": "I", + "source": "Lactose", "target": "I_Lactose", "sign": true, "properties": { @@ -155,7 +155,7 @@ }, { "id": "t4", - "source": "Lactose", + "source": "I", "target": "I_Lactose", "sign": true, "properties": { @@ -481,8 +481,8 @@ }, { "target": "t4", - "expression": "I*Lactose*k_3", - "expression_mathml": "ILactosek_3" + "expression": "0", + "expression_mathml": "0" }, { "target": "t5", @@ -511,8 +511,8 @@ }, { "target": "t10", - "expression": "I*Op*k_5", - "expression_mathml": "IOpk_5" + "expression": "0", + "expression_mathml": "0" }, { "target": "t11", @@ -541,8 +541,8 @@ }, { "target": "t16", - "expression": "Op*RNAP*k_7", - "expression_mathml": "OpRNAPk_7" + "expression": "0", + "expression_mathml": "0" }, { "target": "t17", diff --git a/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json b/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json index 4b9079ad3..db8d836a8 100644 --- a/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json +++ b/notebooks/hackathon_2024.02/scenario6/scenario6_hunt_regnet.json @@ -114,7 +114,7 @@ }, { "id": "t4", - "source": "p_2", + "source": "p_1", "target": "r_2", "sign": true, "properties": { @@ -124,7 +124,7 @@ }, { "id": "t5", - "source": "p_1", + "source": "p_2", "target": "r_2", "sign": true, "properties": { @@ -305,8 +305,8 @@ }, { "target": "t5", - "expression": "C_1*p_1/(1 + p_2/a_1)", - "expression_mathml": "C_1p_11p_2a_1" + "expression": "0", + "expression_mathml": "0" }, { "target": "t6", @@ -325,8 +325,8 @@ }, { "target": "t9", - "expression": "C_2*p_1/(1 + p_3/a_2)", - "expression_mathml": "C_2p_11p_3a_2" + "expression": "0", + "expression_mathml": "0" }, { "target": "t10", From ef0898bee0c2fc584d47bb1da14a92a8631eb970 Mon Sep 17 00:00:00 2001 From: nanglo123 Date: Fri, 26 Apr 2024 10:24:04 -0400 Subject: [PATCH 43/44] Revert json import in notebook --- .../epi_scenario5/epi_scenario5.ipynb | 29 ++++---- .../scenario6/scenario6.ipynb | 67 ++++++++++--------- 2 files changed, 49 insertions(+), 47 deletions(-) diff --git a/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb b/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb index 422e8a728..da709e512 100644 --- a/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb +++ b/notebooks/evaluation_2024.03/epi_scenario5/epi_scenario5.ipynb @@ -10,14 +10,13 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 1, "id": "d3b46cfa", "metadata": {}, "outputs": [], "source": [ "import numpy\n", "import matplotlib.pyplot as plt\n", - "import json\n", "\n", "from mira.metamodel import *\n", "from mira.modeling import Model\n", @@ -36,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 2, "id": "8efb8e6b", "metadata": {}, "outputs": [], @@ -64,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 3, "id": "4be2a9c7", "metadata": {}, "outputs": [], @@ -103,7 +102,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 4, "id": "3bf62177", "metadata": {}, "outputs": [], @@ -117,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 5, "id": "fff395d8", "metadata": {}, "outputs": [], @@ -147,7 +146,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 6, "id": "b38d4412", "metadata": {}, "outputs": [], @@ -167,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 7, "id": "e398426e", "metadata": {}, "outputs": [ @@ -191,7 +190,7 @@ "[ p[9, 0]*y[9, 0] - p[10, 0]*y[3, 0]*y[10, 0] - p[15, 0]*y[10, 0]]])" ] }, - "execution_count": 27, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -203,7 +202,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 8, "id": "eff2ac28", "metadata": {}, "outputs": [], @@ -214,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 9, "id": "f8742e84", "metadata": {}, "outputs": [ @@ -224,13 +223,13 @@ "Text(0, 0.5, '# Molecules / cell')" ] }, - "execution_count": 29, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -258,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 10, "id": "a1d9cfef", "metadata": {}, "outputs": [], @@ -287,7 +286,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.10.13" } }, "nbformat": 4, diff --git a/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb b/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb index 5fbf56f33..27eff4d0a 100644 --- a/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb +++ b/notebooks/hackathon_2024.02/scenario6/scenario6.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 52, + "execution_count": 1, "id": "0606e469", "metadata": {}, "outputs": [], @@ -10,7 +10,6 @@ "import numpy\n", "import sympy\n", "import matplotlib.pyplot as plt\n", - "import json\n", "\n", "from mira.metamodel import *\n", "from mira.modeling import Model\n", @@ -22,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 2, "id": "d61ac405", "metadata": {}, "outputs": [], @@ -56,18 +55,18 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 3, "id": "85dc41a5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "" ] }, - "execution_count": 54, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -78,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 4, "id": "4c52e0e5", "metadata": {}, "outputs": [], @@ -99,18 +98,18 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 5, "id": "52e3c60a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "" ] }, - "execution_count": 56, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -121,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 6, "id": "e6662e8a", "metadata": {}, "outputs": [], @@ -145,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 7, "id": "0e97938e", "metadata": {}, "outputs": [], @@ -155,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 8, "id": "1502c3a1", "metadata": {}, "outputs": [], @@ -166,9 +165,11 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 9, "id": "dde3bf5e", - "metadata": {}, + "metadata": { + "scrolled": false + }, "outputs": [ { "name": "stderr", @@ -183,13 +184,13 @@ "Text(0, 0.5, 'Proportion')" ] }, - "execution_count": 60, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -209,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 10, "id": "2163ce1b", "metadata": { "scrolled": true @@ -230,7 +231,7 @@ "[ 2.0*y[2, 0] - 0.015*y[5, 0]]])" ] }, - "execution_count": 61, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -273,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 11, "id": "fdd87873-aa57-4b0a-9725-e4a8ea5a5226", "metadata": {}, "outputs": [ @@ -311,7 +312,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 12, "id": "98b731de", "metadata": {}, "outputs": [ @@ -371,7 +372,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 13, "id": "e18ce097", "metadata": {}, "outputs": [], @@ -386,7 +387,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 14, "id": "ebb2f408", "metadata": {}, "outputs": [], @@ -407,18 +408,18 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 15, "id": "d4797e40", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "" ] }, - "execution_count": 66, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -429,9 +430,11 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 16, "id": "990374cb", - "metadata": {}, + "metadata": { + "scrolled": false + }, "outputs": [ { "name": "stderr", @@ -446,13 +449,13 @@ "Text(0, 0.5, 'Proportion')" ] }, - "execution_count": 67, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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" ] @@ -474,7 +477,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 17, "id": "3a5c3e3a", "metadata": {}, "outputs": [], @@ -505,7 +508,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.10.13" } }, "nbformat": 4, From d2fcbd9625529b6cc0d92273f46b83548967c962 Mon Sep 17 00:00:00 2001 From: Ben Gyori Date: Fri, 26 Apr 2024 15:28:10 -0400 Subject: [PATCH 44/44] Use fewer models from web for testing --- tests/test_sbml_qual.py | 29 ++++------------------------- 1 file changed, 4 insertions(+), 25 deletions(-) diff --git a/tests/test_sbml_qual.py b/tests/test_sbml_qual.py index a3b73ef3c..8328b83b6 100644 --- a/tests/test_sbml_qual.py +++ b/tests/test_sbml_qual.py @@ -7,30 +7,7 @@ from mira.sources.sbml.qual_api import template_model_from_sbml_qual_string from mira.sources.biomodels import get_sbml_model -models = [ - "Apoptosis", - "Coagulation-pathway", - "ER_Stress", - "ETC", - "E_protein", - "HMOX1_Pathway", - "IFN-lambda", - "Interferon1", - "JNK_pathway", - "Kynurenine_pathway", - "NLRP3_Activation", - "Nsp14", - "Nsp4_Nsp6", - "Nsp9_protein", - "Orf10_Cul2_pathway", - "Orf3a", - "PAMP_signaling", - "Pyrimidine_deprivation", - "RTC-and-transcription", - "Renin_angiotensin", - "TGFB_pathway", - "Virus_replication_cycle", -] +models = ["Apoptosis"] BASE_URL = "https://git-r3lab.uni.lu/covid/models/-/raw/master/Executable%20Modules/SBML_qual_build/sbml" @@ -42,7 +19,9 @@ def test_qual_models_from_example_repo(): def test_qual_models_from_biomodels(): - model_ids = ["BIOMD0000000562", "BIOMD0000000592", "BIOMD0000000593"] + model_ids = ["BIOMD0000000562"] + # Full model list for reference + #model_ids = ["BIOMD0000000562", "BIOMD0000000592", "BIOMD0000000593"] for model_id in model_ids: model_text = get_sbml_model(model_id) tm = template_model_from_sbml_qual_string(model_text)