Derek M. Mason

This paper introduces CALM, a model that predicts antibody-antigen binding from sequences using contrastive learning, achieving 7% top-1 retrieval on a test set.

This study uses antibody repertoire data and machine learning to predict and engineer antibody affinities, achieving accurate predictions and successful in silico design of seven out of eight synthetic variants.

Mammalian display of CRISPR-introduced trastuzumab mutant libraries trains a network that picks antigen binders out of a hundred-million-variant virtual library; 30 of 30 tested variants bound.