Nature Communications (Jun 2021)
Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics
- Mathias Wilhelm,
- Daniel P. Zolg,
- Michael Graber,
- Siegfried Gessulat,
- Tobias Schmidt,
- Karsten Schnatbaum,
- Celina Schwencke-Westphal,
- Philipp Seifert,
- Niklas de Andrade Krätzig,
- Johannes Zerweck,
- Tobias Knaute,
- Eva Bräunlein,
- Patroklos Samaras,
- Ludwig Lautenbacher,
- Susan Klaeger,
- Holger Wenschuh,
- Roland Rad,
- Bernard Delanghe,
- Andreas Huhmer,
- Steven A. Carr,
- Karl R. Clauser,
- Angela M. Krackhardt,
- Ulf Reimer,
- Bernhard Kuster
Affiliations
- Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich (TUM)
- Daniel P. Zolg
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Michael Graber
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Siegfried Gessulat
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Tobias Schmidt
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Karsten Schnatbaum
- JPT Peptide Technologies GmbH
- Celina Schwencke-Westphal
- Klinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, School of Medicine, Technical University of Munich (TUM)
- Philipp Seifert
- Klinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, School of Medicine, Technical University of Munich (TUM)
- Niklas de Andrade Krätzig
- Center for Translational Cancer Research (TranslaTUM), TUM School of Medicine, Technical University of Munich (TUM)
- Johannes Zerweck
- JPT Peptide Technologies GmbH
- Tobias Knaute
- JPT Peptide Technologies GmbH
- Eva Bräunlein
- Klinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, School of Medicine, Technical University of Munich (TUM)
- Patroklos Samaras
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Ludwig Lautenbacher
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- Susan Klaeger
- Broad Institute of MIT and Harvard
- Holger Wenschuh
- JPT Peptide Technologies GmbH
- Roland Rad
- Center for Translational Cancer Research (TranslaTUM), TUM School of Medicine, Technical University of Munich (TUM)
- Bernard Delanghe
- Thermo Fisher Scientific
- Andreas Huhmer
- Thermo Fisher Scientific
- Steven A. Carr
- Broad Institute of MIT and Harvard
- Karl R. Clauser
- Broad Institute of MIT and Harvard
- Angela M. Krackhardt
- Klinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, School of Medicine, Technical University of Munich (TUM)
- Ulf Reimer
- JPT Peptide Technologies GmbH
- Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM)
- DOI
- https://doi.org/10.1038/s41467-021-23713-9
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 12
Abstract
The identification of HLA peptides by mass spectrometry is non-trivial. Here, the authors extended and used the wealth of data from the ProteomeTools project to improve the prediction of non-tryptic peptides using deep learning, and show their approach enables a variety of immunological discoveries.
