Ryan Shihabi

This paper introduces a method to detect cryptic pockets from apo protein structures using a structural world model, achieving high accuracy and outperforming existing approaches.

The paper uses AI to analyze spatial data from Alzheimer's mouse models, revealing new protein interactions and synaptic structures linked to disease.

The paper introduces HI-JEPA, a model trained on molecular proximity measurements to predict protein interactions and disease-related configurations.