LC-MS data processing tool for large-scale metabolomics experiments.

Fast and Accurate CE-, GC- and LC-MS(/MS) Data Processing

The MetaRbolomics book. A review of R packages in BioC, CRAN, gitlab and github.

AutoRT: Peptide retention time prediction using deep learning

Python module for lipidomics LC MS/MS data analysis

R-package - Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

A python package for protein inference in Mass Spectrometric data analysis.

Code, Data and Results of the publication: "Probabilistic Framework for Integration of Tandem-Mass Spectrum and Retention Time Information in Small Molecule Identification" by Bach et al. 2020

LipidHunter is capable to perform bottom up identification of lipids from LC-MS/MS and shotgun lipidomics data by resembling a workflow of manual spectra annotation. LipidHunter generates interactive HTML output with its unique six-panel-image, which provides an easy way to review, store, and share the identification results.

High-throughput MS/MS annotation with a in-house database

BMDMS-NP

tools collection of Sipros for stable isotopic mass spectrum meta proteomic research

Generate annotated Peptide Spectrum Matches (PSMs) from proteomic database search result

Python & R scripts collection for AdipoAtlas project

Extracts the features of peptide spectral library for better understanding and its efficient usage in DIA database search

LC-MS/MS derived peptide retention time deviation calculator across replicates for DDA and DIA derived result files.

MFQL files for Natural Products Dereplication

R package for annotation of glycans in MS1 and MS2 data

Predict and match digested peptides sequences, their mass m/z and MS/MS spectra with chemical derivatization or post-translational modification.

Predicting ion-mobility and spectra for labeled peptides