Re-thinking Conformation Space Search for Protein Structure
Speaker: Oliver Brock , UMASS Amherst
Date: November 14 2005
Time: 11:30AM to 1:00PM
Location: TOC Lab 32-G575
Host: P Clote/ BC & B Berger/ MIT
Contact: Kathleen Dickey, 617 253 3037, kvdickey@mit.edu
Relevant URL: http://www-math.mit.edu/compbiosem/****in 30 minutes****
The protein structure prediction problem remains one of the great challenges in molecular biology. It sometimes is referred to as the second half of the Human Genome Project, since knowledge of the structure of proteins encoded in the genome can lead to an understanding of cellular processes. Currently, there are two competing views on how the protein structure prediction problem may be solved. The NIH-funded Protein Structure Initiative (PSI) relies on structural genomics, a combination of experimental techniques and homology modeling. The alternative view attempts to predict the structure of proteins entirely based on computation. In this talk, I will argue that, despite the progress made in the PSI, computational methods are likely to play an important role in addressing the protein structure prediction problem. I will also present our recent work in efficient conformation space search. Due to the enormous size ofconformation space, this search iscurrently believed to be the primary obstacle on the path towards accurate computational protein structure prediction. We exploit recent insights from machine learning and robot motion planning to render this search more effective. Our approach improves the Monte Carlo approach, which has been used for conformation space search almost exclusively for over 50 years.
MIT
Department of Mathematics
& The Theory of
Computation Group
At CSAIL
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