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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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TITLE: G-SELC: Optimization by Sequential Elimination of Level Combinations using Genetic Algorithms and Gaussian Processes
SPEAKER: Dr. Abhyuday Mandal
Department of Statistics
University of Georgia
ABSTRACT:
Identifying promising compounds from a vast collection of feasible compounds is an important and yet challenging problem in pharmaceutical industry. An efficient solution to this problem will help reduce the expenditure at the early stages of drug discovery. In an attempt to solve this problem, Mandal, Wu and Johnson (2006) proposed the SELC algorithm. Although powerful, it fails to extract substantial information from the data to guide the search efficiently as this methodology is not based on any statistical modeling. The proposed approach uses Gaussian Process modeling to improve upon SELC, and hence named G-SELC. The performance of the proposed methodology is illustrated using four and five dimensional test functions. Finally, we implement the new algorithm on a real pharmaceutical data set for finding a group of chemical compounds with optimal properties.
(Joint research with C.F. Jeff Wu and Pritam Ranjan)
