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Nature Communications|March 28, 2020
Generating high quality libraries for DIA MS with empirically corrected peptide predictionsBrian C Searle, Kristian E Swearingen, Christopher A Barnes, et al.Molecular & Cellular Proteomics : MCP|May 2, 2019
PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New ProteoformsSteven Verbruggen, Elvis Ndah, Wim Van Criekinge, et al.Nucleic Acids Research|November 7, 2017
ProteomicsDBTobias Schmidt, Patroklos Samaras, Martin Frejno, et al.Journal of Proteome Research|January 24, 2023
ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in ProteomicsTobias G Rehfeldt, Ralf Gabriels, Robbin Bouwmeester, et al.Molecular & Cellular Proteomics : MCP|April 6, 2021
Spectral Prediction Features as a Solution for the Search Space Size Problem in ProteogenomicsSteven Verbruggen, Siegfried Gessulat, Ralf Gabriels, et al.Nature Methods|May 29, 2019
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learningSiegfried Gessulat, Tobias Schmidt, Daniel Paul Zolg, et al.Rapid Communications in Mass Spectrometry : RCM|May 20, 2021
INFERYS rescoring: Boosting peptide identifications and scoring confidence of database search resultsDaniel P Zolg, Siegfried Gessulat, Carmen Paschke, et al.Nucleic Acids Research|October 31, 2019
ProteomicsDB: a multi-omics and multi-organism resource for life science researchPatroklos Samaras, Tobias Schmidt, Martin Frejno, et al.Journal of Proteome Research|February 21, 2025
A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and AnalysisMarkus Schneider, Daniel P Zolg, Patroklos Samaras, et al.Nature Methods|April 22, 2025
Unifying the analysis of bottom-up proteomics data with CHIMERYSMartin Frejno, Michelle T Berger, Johanna Tüshaus, et al.Pageof 2