When: October 12, 2016, 2:00 PM
Location: 3rd Floor Orchard View Room , Discovery Building
Contact: 608-316-4401, email@example.com
Data-driven protein engineering: learning the relationship between sequence and function
Rational protein engineering relies on accurate models that relate a protein’s sequence to its biochemical properties, such as binding affinity, enzymatic activity, and stability. These molecular properties are often extremely difficult to model because they may be poorly understood or involve subtle, possibly dynamic, structural changes. In this talk, I will present an alternative modeling approach where statistical models are used to learn the relationship between protein sequence and function from experimental data. These data-driven models are able to capture the numerous and possibly unknown factors that shape the sequence-function mapping, and thus provide unprecedented predictive accuracy. Furthermore, we can apply concepts from Bayesian decision theory to efficiently explore protein sequence space and discover optimized sequences. As technology for high-throughput experimentation advances, this class of models could play an increasing role in protein science and engineering.
All QBio sponsored talks take place on Wednesdays at 2:00 p.m. in the 3rd floor Orchard View room of the Discovery Building unless otherwise noted. Talks are open to the public. Access to the room is via the elevator behind Aldo’s Cafe in the Northeast corner of the building.