arXiv Machine Learning June 30, 2026 By Aspen Erlandsson Brisebois, Zahed Khatooni, Connor Burbridge, Brook Byrns, Heather L. Wilson, Sureesh Tikoo, Steven Rayan, Gordon Broderick

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

Read the original on arXiv Machine Learning →

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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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