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Computational proteomics and bioinformatics

Computational expertise in the Protein Research Group

Computational analysis is an integral part of modern proteomics. Within the Protein Research Group, we develop and apply computational approaches for quantitative proteomics, statistical analysis, protein networks, post-translational modifications and the interpretation of complex biological datasets.

Our computational activities range from the development of dedicated software and statistical methods to reproducible workflows for processing and interpreting mass spectrometry-based data. The tools and resources below illustrate this expertise and its development across several generations of proteomics research.

Selected computational tools and resources

Name Description Publication
PolySTest Robust statistical testing of quantitative proteomics data. Schwämmle et al., 2020
HUMOS eLearning web application developed to support teaching of Orbitrap mass spectrometry. Bubis et al., 2020
ComplexBrowser R-based software for supervised analysis of changes in protein-complex abundance and subunit co-expression in proteomics datasets. Michalak et al., 2019
CoExpresso Tool for investigating co-regulatory behaviour and its significance among protein subunits in known protein complexes. Chalabi et al., 2019
ProtProtocols and IsoProt Containerised workflows for proteomics data analysis. Griss et al., 2019
Citrullia Software for confident identification of citrullinated peptides. Larsen et al., 2020
topdownR Software for systematic investigation of MS/MS fragmentation methods on Orbitrap instruments and analysis of the resulting spectra. Shliaha et al., 2018
VSClust Feature-based variance-sensitive clustering of omics data. Schwämmle et al., 2018
SuperQuant Quantitative proteomics data-processing approach using complementary fragment ions to identify and quantify multiple co-isolated peptides in tandem mass spectra. Gorshkov et al., 2015
A2b2-restrictor Deconvolution of multiple fragmented peptides using the relationship between a2/b2 and yn-2 ions in HCD spectra. Kryuchkov et al., 2014
CrossTalkDB Platform for collecting, statistically assessing and analysing multiply modified proteins and estimating post-translational modification crosstalk. Schwämmle et al., 2014
PhosphoSiteLocalizer Approach for phosphosite localisation using complementary peptide fragmentation by CID and ETD. Hansen et al., 2012
MASSAI Software for analysis of data from chemical cross-linking experiments. Rasmussen et al., 2011
GPMAW Software for analysing proteins and peptides.
GitHub projects Source code and documentation for current and former software developments.
Bitbucket projects Source code and documentation for current and former software developments.

Computational approaches in our research 

Computational methods are integrated across research and collaborations within the Protein Research Group. Our expertise supports the analysis of complex proteomics and other omics datasets and connects experimental measurements with quantitative analysis and biological interpretation.

Last Updated 26.08.2026