JSM 2004 Online Program

Abstract #301877

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Activity Number:	348
Type:	Luncheons
Date/Time:	Wednesday, August 11, 2004 : 12:30 PM to 1:50 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #301877
Title:	Bayesian Methods in Bioinformatics Research - SOLD OUT
Author(s):	Jun S. Liu*+
Companies:	Harvard University
Address:	Dept. of Statistics, Cambridge, MA, 02138,
Keywords:	gene network ; machine learning ; microarray ; MCMC ; sequence analysis ; transcription regulation
Abstract:	Discussions will be focused on pressing issues in bioinformatics research, especially those that are at the interface of statistics, genetics, and genomics. We show that the Bayesian modeling approach is a suitable framework for combining and synthesizing information and for handling such complex problems as understanding gene regulation, inferring relationships among proteins, and analyzing functionalities of conserved structural cores of proteins. More detailed mathematical formulations will be given in the short course "Tutorial on the Bayesian methods in bioinformatics" given by JSL.

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