Jesse Durham

The paper validates and analyzes 12,000 AI-designed CAR-T binders from a global competition, identifying successful designs and factors improving their performance.

The paper develops TriCyP, a model to predict cysteine states in protein structures, achieving high accuracy and identifying new biological patterns and protein families.

The paper predicts 18,316 human protein-protein interactions with 90% precision using enhanced coevolutionary analysis and a new deep learning model.

DPAM automatically parses AlphaFold models to recognize and classify protein domains, outperforming existing methods in accuracy and boundary assignment.

The paper uses AlphaFold to predict cancer protein-protein interactions and maps somatic mutations to these interfaces, revealing functional insights and potential drug targets.