(575g) Invited Talk: Machine Learning-Guided Directed Evolution of Functional Proteins

Data-driven modeling and deep learning present powerful tools that are opening up new paradigms and opportunities in the understanding, discovery, and design of soft and biological materials. I will describe our recent applications of deep representational learning to expose the sequence-function relationship within homologous protein families and to use these principles for the generative data-driven design and experimental testing of synthetic proteins with elevated function within machine learning-guided directed evolution campaigns.