Author

Wiona Sophie Glänzer

ETH Zurich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:cell type annotation· 1 Approach:contrastive learning· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

Alexander YermanosiD· 2 shared Sai T. ReddyiD· 2 shared Anamay Samant· 1 shared Andreas AgrafiotisiD· 1 shared Andreas ScheckiD· 1 shared Daphne van GinnekeniD· 1 shared Derek M. MasoniD· 1 shared Evgenios Kladis· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersImmunology

Alexander YermanosORCID

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2 papers

Recent·Most cited

ImmunologybioRxivPreprintFeb 26, 2026

Contrastive learning for antibody-antigen sequence-to-specificity prediction

Hyunho Lee, Karla M. Castro, Sean Renwick…·Sai T. Reddy

This paper introduces CALM, a model that predicts antibody-antigen binding from sequences using contrastive learning, achieving 7% top-1 retrieval on a test set.

1 citation

protein sequencedeep learning

𝕏 PostBluesky

BioinformaticsBriefings in BioinformaticsPeer-reviewedJul 1, 2025

Protein language model pseudolikelihoods capture features of in vivo B cell selection and evolution

Daphne van Ginneken, Anamay Samant, Karlis Daga-Krumins…·Alexander Yermanos

This study shows that protein language model pseudolikelihoods correlate with B cell selection features like SHM and isotype usage, but not binding affinity, in vivo.

6 citations

humanmouse

𝕏 PostBluesky