Author

Jonathan Patsenker

Yale University

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· 2

Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:fine-mapping· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1

Frequent Co-Authors

Henry Li· 2 shared Meng WangiD· 2 shared Steven H. KleinsteiniD· 2 shared Yuval KlugeriD· 2 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Henry Li

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2 papers

Recent·Most cited

Supervised fine-tuning of pre-trained antibody language models improves antigen specificity prediction

Meng Wang, Jonathan Patsenker, Henry Li, Yuval Kluger, Steven H. Kleinstein

This study improves antigen specificity prediction by fine-tuning pre-trained antibody language models on SARS-CoV-2 and influenza antigens, showing better accuracy than models trained on embeddings alone.

PLoS Computational Biology · Mar 31, 2025Peer-reviewedBioinformatics

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity

Meng Wang, Jonathan Patsenker, Henry Li, Yuval Kluger, Steven H. Kleinstein

This study evaluates B cell receptor sequence embeddings for predicting sequence properties and specificity, finding that BCR-specific embeddings and paired-chain sequences improve performance.

Nucleic Acids Research · Nov 11, 2023Peer-reviewedBioinformatics