Author

Chak Shing Lee

Lawrence Livermore National LaboratoryORCID 0000-0002-9573-3463Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

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Approach:deep learning· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1

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Conor F. HayesiD· 1 shared Denis Vashchenko· 1 shared Mikel LandajuelaiD· 1 shared

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2025-2025 · peak 1/yr

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1 shared paperBioinformatics

Conor F. HayesORCID

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1 paper

Recent·Most cited

Reinforcement Learning for Antibody Sequence Infilling

Chak Shing Lee, Conor F. Hayes, Denis Vashchenko, Mikel Landajuela

This paper introduces a reinforcement learning framework for antibody sequence design that improves biophysical properties using infilling models and online learning strategies.

bioRxiv · Aug 8, 2025 · PreprintBioinformatics