Author

Juan Restrepo

Max Planck Institute of BiochemistryORCID 0009-0004-0711-0103Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Approach:deep learning· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Jüergen CoxiD· 2 shared Bryan Crampton· 1 shared Christoph WichmanniD· 1 shared Dániel SzöllősiiD· 1 shared Dejan ŠtepeciD· 1 shared Helmut GrubmülleriD· 1 shared Jure ŽbontariD· 1 shared Maximilien BurqiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

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10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Jüergen CoxORCID

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2 papers

Recent·Most cited

Bimodal peptide collision cross section distribution reflects two stable conformations in the gas phase

Juan Restrepo, Dániel Szöllősi, Tobias Kiermeyer, Christoph Wichmann, Helmut Grubmüller, J. Cox

The paper identifies a bimodal distribution of peptide collision cross sections, showing two stable conformations, and proposes a two-valued predictor to improve peptide identification in proteomics.

Journal of Proteome Research · Apr 29, 2026Peer-reviewedBioinformatics

Back to Basics: Spectrum and Peptide Sequence are Sufficient for Top-tier Mass Spectrometry Proteomics Identification

Maximilien Burq, Dejan Štepec, Juan Restrepo, Jure Žbontar, Shamil Z. Urazbakhtin, Bryan Crampton, Shivani Tiwary, Rehan Chinoy, Melissa Miao, Jüergen Cox, Peter Cimermančič

This paper introduces a deep learning-based approach for peptide identification in mass spectrometry proteomics that outperforms existing tools by using spectra and peptide sequences directly.

bioRxiv · Aug 19, 2024 · PreprintBioinformatics