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Future Directions Presentation
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Bio
Stern has been on the faculty of Iowa State since 1994. He was an associate professor of statistics from 1994-97; director of graduate studies from 1996-98; and professor of statistics from 1997 to present. He was appointed interim director of the Baker Center in 2000. Prior to Iowa State, Stern held several positions at Harvard University, including associate professor of statistics and director of undergraduate studies in statistics. He received a B.S. in mathematics from the Massachusetts Institute of Technology in 1981; and an M.S. in 1985 and a Ph.D. in 1987, both from Stanford University.
HOPS: A Distributed Hybrid Optimization Technique for Protein Structure Prediction
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Abstract
The key to understanding the mechanism of life lies in understanding how proteins work. Nearly all functional aspects of an organism rely on proteins; enzymes, brain chemicals like dopamine, hormones, and hundreds of thousands of others. Surprisingly, a properly working protein works because it has just the right three dimensional shape, a shape determined by the protein's molecular composition, which is in turn described in the genome. Given that we now have access to extensive genomic information, the next challenge for computational biologists is to determine a protein's three dimensional shape (or ``tertiary structure'') -- and, consequently, its biological function -- from its molecular composition (or ``primary structure''), expressed as the sequence of constituent amino acids. This ''protein folding problem'' is enormously difficult, both because of the number of possible configurations a protein might assume and because we don't yet precisely understand the science of the folding process itself. We have been working on a new hybrid optimization approach to this problem that marks the convergence of several different research efforts. Our approach blends a distributed AI search technique we originally developed for use in automated deduction systems with a number of continuous optimization methods and powerful biochemically-inspired heuristics based on experimental data obtained in the laboratory. In this talk, I will describe the general architecture of our system, give an update on our recent progress, and demonstrate some preliminary folding results.
Joint work with Yinyu Ye (Management Sciences/Applied Mathematics), Kenneth Murphy (Biochemistry), Mauro Leoncini (CNR, Pisa, Italy), and Giovanni Resta (CNR, Pisa, Italy)
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