Generative Models for Biomolecular Prediction, Dynamics, and Design
Learning objectives
- Understand how generative models improve hard prediction tasks by suggesting and ranking multiple solutions.
- Explore how generative models capture the dynamics and conformations of biomolecules.
- Learn how generative models accelerate the design of new biomolecules using sampled data or likelihoods.
Speaker biography
Bowen and Hannes are PhD candidates at MIT working with Drs. Bonnie Berger, Tommi Jaakkola, and Regina Barzilay. Their interests center around using generative models for biomolecular applications ranging from protein engineering to molecular dynamics.