arXiv Machine Learning By Mansoor Ahmed, Huirong Chai, Haoxin Wang, Hemanth Venkateswara, Murray Patterson

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning

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arXiv:2606. 04154v1 Announce Type: cross Abstract: Antibodies neutralize foreign antigens by binding to specific surface regions called epitopes.

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arXiv Machine Learning
Aug 12

AgForce Enables Antigen-conditioned Generative Antibody Design

arXiv:2605. 21610v2 Announce Type: replace Abstract: Antibody design methods condition on antigen structure to generate complementarity-determining regions (CDR), yet a systematic evaluation of baseline methods reveals that they largely ignore the antigen input.

By Mansoor Ahmed, Murray Patterson
arXiv Machine Learning
Jun 30

Transformer-Based Active Learning for Data-Efficient Vaccine Epitope Selection in PRRS

arXiv:2606. 28659v1 Announce Type: cross Abstract: High-fidelity molecular docking simulations can produce biologically relevant estimates of epitope-receptor binding affinity but are computationally expensive and therefore limit the number of candidates that can be screened for vaccine design.

By Aspen Erlandsson Brisebois, Zahed Khatooni, Connor Burbridge, Brook Byrns, Heather L. Wilson, Sureesh Tikoo, Steven Rayan, Gordon Broderick
Hugging Face Trending Papers
Jul 22

Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design

Antibodies are essential proteins that play a central role in immune recognition by binding specific antigen molecules. Although recent protein language models have enabled progress in single-chain protein modeling and generation, they often fall short in antigen-specific antibody design, where effective modeling requires explicit pairing between antibody and antigen, particularly at the epitope level.