Physics x Data Science Seminar: Claus Horn, Yale School of Medicine

“Physics - ML - Proteins”

The convergence of machine learning and protein science unlocks transformative possibilities in computational biology and biomedicine. This talk explores the synergy between physics-based modeling and machine learning to advance protein design, with applications spanning biochemistry and medicine. Key topics include protein-ligand binding prediction, enzyme engineering, and inhibitor design. Addressing these challenges requires interdisciplinary innovations, leveraging graph neural networks, protein language models, autonomous agents, and federated learning.

Host: Naomi Gluck and Nathan Suri