Author

Luca C Herrmann

University of ViennaORCID 0009-0006-0783-1212Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biochemistry· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:diffusion model· 1 Research Focus:drug response / drug discovery· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1 Assay:proteomics· 1

Frequent Co-Authors

Alex KangiD· 1 shared Alexander TongiD· 1 shared Amir MotmaeniD· 1 shared Andrew C. LuiD· 1 shared Ariane MoraiD· 1 shared Asim K. BeraiD· 1 shared Béla P. FrohniD· 1 shared Brian CoventryiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

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10 top collaborators · 24 mutual co-author links

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1 shared paperBiochemistry

Alex KangORCID

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintSep 11, 2026

Reframing enzyme function prediction as conditional generation

William JF Rieger, Sebastian Haeussermann, Luca Herrmann…·Ariane Mora

Fluxion generates enzyme function predictions by modeling electron flow trajectories, enabling function generation beyond static classification.

DOI 10.64898/2026.09.09.750355

proteomicsdeep learning

𝕏 PostBluesky

BiochemistrybioRxivPreprintSep 29, 2025

De novo design of phosphotyrosine peptide binders

Magnus S. Bauer, Jason Z. Zhang, Kejia Wu…·David A. Baker

This paper introduces RFD2-MI, a deep learning framework for designing phosphotyrosine peptide binders, showing high specificity and affinity for phosphorylated targets.

4 citations

protein structuredeep learning

𝕏 PostBluesky