Computational Omics and Systems Biology Group (CompOmics)

Computational Omics and Systems Biology Group

CompOmics

Organization data from Github https://github.com/CompOmics

The CompOmics group, headed by Prof. Dr. Lennart Martens, specializes in the management, analysis and integration of high-throughput Omics data.

Location:Belgium

Home Page:https://www.compomics.com/

GitHub:@CompOmics

Twitter:@CompOmics

Computational Omics and Systems Biology Group's repositories

ThermoRawFileParser

Thermo RAW file parser that runs on Linux/Mac and all other platforms that support Mono

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DeepLC

DeepLC: Retention time prediction for (modified) peptides using Deep Learning.

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ms2rescore

Modular and user-friendly platform for AI-assisted rescoring of peptide identifications

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peptide-shaker

Interpretation of proteomics identification results

ms2pip

MS²PIP: Fast and accurate peptide spectrum prediction for multiple fragmentation methods, instruments, and labeling techniques.

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searchgui

Highly adaptable common interface for proteomics search and de novo engines

compomics-utilities

Open source Java library for computational proteomics

psm_utils

Common utilities for parsing and handling peptide-spectrum matches and search engine results in Python

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IM2Deep

Collisional cross-section prediction for modified and multiconformational peptides

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mumble

Finding the perfect modification for your mass shift

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reporter

Protein quantification based on reporter ions

ms2rescore-rs

Rust functionality for the MS²Rescore package

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ecoli-peptideatlas-manuscript

Code used to produce figures in the E. coli PeptideAtlas Paper

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intro-to-deep-learning

Practical introduction to neural networks with Pytorch and Lightning

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Peptonizer2000

Confidence for taxonomic analysis in metaproteomics. Get ready to peptonize!

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bioconda-recipes

Conda recipes for the bioconda channel.

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compomics-rover

A tool to visualize and validate quantitative proteomics data from different sources.

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compomics.github.io

Compomics github website.

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EUPA_2025_DIA

Analysis of limitations of DIA data analysis for EuPA 2025 presentation

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iDeepLC

iDeepLC: A deep Learning-based retention time predictor for unseen modified peptides with a novel encoding system

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molcraft

Deep Learning on Molecules.

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molexpress

Graph Neural Networks with Keras 3

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oui-discovery

Collaboration between CompOmics & OpenProt group

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Workshop_Grenoble_2025

Workshop on MS²Rescore for data-driven peptide identification rescoring (Grenoble, 2025)

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