Author

Denis Vashchenko

Lawrence Livermore National Laboratory

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 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Research Focus:sequence-to-function modeling· 1 Research Focus:software / tool· 1 Approach:statistical model· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

André Ricardo GonçalvesiD· 1 shared Brenden K. PeterseniD· 1 shared Chak Shing LeeiD· 1 shared Conor F. HayesiD· 1 shared Daniel FaissoliD· 1 shared Felipe Leno da SilvaiD· 1 shared Mikel LandajuelaiD· 1 shared Sam Nguyen· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 18 mutual co-author links

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1 shared paperBioinformatics

André Ricardo GonçalvesORCID

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2 papers

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

AbBERT: Learning Antibody Humanness via Masked Language Modeling

Denis Vashchenko, Sam Nguyen, André Ricardo Gonçalves, Felipe Leno da Silva, Brenden K. Petersen, Thomas Desautels, Daniel Faissol

AbBERT is a transformer-based language model trained on antibody sequences to predict humanness, showing utility in antibody design and optimization.

bioRxiv · Aug 2, 2022 · PreprintBioinformatics