Rebecca F. Alford

EGGNet is a geometric deep learning framework for predicting molecule-protein interactions, achieving competitive performance on binding affinity and interface prediction tasks.

The paper presents a framework for ensuring reproducibility in bio-macromolecular modeling through automated benchmarks and a test server, demonstrating its utility for Rosetta and other tools.

VIPUR integrates sequence and structural modeling to classify protein variants, showing improved accuracy and interpretability in predicting deleterious mutations across organisms and diseases.