Research
Biological molecules carry out their functions through complex interactions with diverse molecular partners. However, predictive models that capture the underlying principles of these interactions—and can generalize across different biological contexts—remain elusive for many critical interaction types. Our research focuses on developing flexible, predictive models for protein-RNA and protein-small molecule interactions, which play crucial roles in a broad range of human diseases. We aim to leverage these predictive models to develop new therapeutic approaches for hematologic malignancies, several of which are driven by stereotyped mutations affecting protein-RNA complexes.
Our Focus:
We develop novel experimental technologies that enable us to measure how different types of biological molecules interact with each other at unprecedented scales. We then integrate these large-scale measurements with machine learning algorithms to build computational models that can predict and understand molecular interactions at atomic resolution. These models are then tested for their ability to predict and design interactions on independent data collected by ourselves and others.
