Author

Ludwig Lautenbacher

Technical University of MunichORCID 0000-0002-1540-5911Unclaimed 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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Approach:deep learning· 2 Assay:proteomics· 2 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Mathias WilhelmiD· 2 shared Wassim GabrieliD· 2 shared Alexey I. NesvizhskiiiD· 1 shared Andreas F. R. HühmeriD· 1 shared Armin SoleymaniniyaiD· 1 shared Bernard DelangheiD· 1 shared Bernhard KüsteriD· 1 shared Brendan MacLeaniD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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10 top collaborators · 30 mutual co-author links

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2 shared papersBioinformatics

Mathias WilhelmORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 7, 2025

Learning the Unseen: Data-Augmented Deep Learning for PTM Discovery with Prosit-PTM

Wassim Gabriel, Daniel Paul Zolg, Victor Giurcoiu…·Mathias Wilhelm

This paper introduces Prosit-PTM, a deep learning model for PTM discovery that improves zero-shot prediction using a synthetic dataset and chemically-informed encoding.

DOI 10.1101/2025.11.07.687302

proteomicsdeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJun 1, 2024

Koina: Democratizing machine learning for proteomics research

Ludwig Lautenbacher, Kevin Yang, Tobias Kockmann…·Mathias Wilhelm

Koina provides an open-source, accessible ML/DL prediction service for proteomics, improving integration with existing tools like FragPipe.

24 citations

proteomicsmachine learning (classical)

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