This work studies MHC-I binding prediction for antigenic peptide discovery. It identifies evaluation pitfalls, proposes a unified methodology, and introduces a transformer model trained on interspecies data.

Presented at: ICLR 2023 Machine Learning for Drug Discovery (MLDD) Workshop