Author

Jakob Träuble

Technical University of MunichPrimary ORCID profile (0009-0007-2619-9395 · 6 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Jakob TräubleiD6 papers · University of Cambridge

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:deconvolution· 1 Approach:deep learning· 1 Assay:proteomics· 1

Frequent Co-Authors

Daniela Klaproth-AndradeiD· 1 shared Johannes HingerliD· 1 shared Julien GagneuriD· 1 shared Mathias WilhelmiD· 1 shared Nicholas H. SmithiD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

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5 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Daniela Klaproth-AndradeORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJan 5, 2023

Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing

Daniela Klaproth-Andrade, Johannes Hingerl, Nicholas H. Smith…·Julien Gagneur

This paper introduces Spectralis, a deep learning method for de novo peptide sequencing that improves sensitivity and precision in tandem mass spectrometry.

8 citations

proteomicsdeep learning

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