Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins. In Joanna Slusky (Eds.), PLOS Computational Biology, (20)3:e1011939, Public Library of Science (PLoS), March 2024. [PUMA: imported topic_lifescience] URL
Self-supervised machine learning methods for protein design improve sampling, but not the identification of high-fitness variants. Cold Spring Harbor Laboratory, June 2024. [PUMA: imported topic_lifescience] URL
Interpretable Chirality-Aware Graph Neural Network for Quantitative Structure Activity Relationship Modeling in Drug Discovery. Proceedings of the AAAI Conference on Artificial Intelligence, (37)12:14356â14364, Association for the Advancement of Artificial Intelligence (AAAI), June 2023. [PUMA: imported topic_lifescience] URL
Benchmarking AlphaMissense Pathogenicity Predictions Against Cystic Fibrosis Variants. Cold Spring Harbor Laboratory, October 2023. [PUMA: imported topic_lifescience] URL
Modeling conformational states of proteins with AlphaFold. Current Opinion in Structural Biology, (81):102645, Elsevier BV, August 2023. [PUMA: imported topic_lifescience] URL