Alan C. Cheng

The paper presents a model validation framework for molecular property prediction models in drug discovery, revealing four failure modes and showing that common evaluation protocols overestimate performance.

Boltz-Perturb improves ligand binding pose prediction by introducing inference-time perturbations, achieving higher success rates with less computation.

The paper identifies functionally important breast cancer SNPs by analyzing pleiotropy, conservation, and protein structure to prioritize mutations likely to impact disease progression.