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Hannes Stark & Bowen Jing: Generative Models for Biomolecular Prediction, Dynamics, and Design

Time and place: 14:00 on Zoom. Register online!

Speaker: Hannes Stark & Bowen Jing, MIT

Title: Generative Models for Biomolecular Prediction, Dynamics, and Design

Abstract: We lay out three avenues in which we think generative models are especially valuable for modeling biomolecules. 1) Hard prediction tasks can be better addressed with generative models that can suggest and rank multiple solutions (e.g., docking). 2) The dynamics and conformations of biomolecules can be captured with generative models (e.g., protein conformational ensembles and MD trajectories). 3) Designing new biomolecules can be accelerated, informed by samples or likelihoods from generative models (e.g., protein binder or regulatory DNA design).

Bio: Bowen and Hannes are 4th and 3rd year PhD students at MIT working with Bonnie Berger, Tommi Jaakkola, and Regina Barzilay. Their interests center around using generative models for biomolecular applications ranging from protein engineering to molecular dynamics.

Later Event: October 21
AI Day 2024 + Nordic AI Meet