[Colloquium] Guest Speaker

[Ponda Barnes]

Guest Speaker announcement
 
Presented by: Toyota Technological Institute at Chicago
 
Speaker: Yuan QI
Speaker's home page: http://web.media.mit.edu/~yuanqi/
 
Date:  Tuesday, March 20, 2007
Time:  10:00am
Location: TTI-C Conference room
 
 
Title: Bayesian Learning for Deciphering Gene Regulation
 
Abstract:
 
Gene regulation plays a fundamental role in biological systems.  As more
high-throughput biological data becomes available it is possible to
quantitatively study gene regulation in a systematic way. In this talk I
present my work on three related problems on gene regulation including: (1)
identifying genes that affect organism development; (2) detecting
protein-DNA binding events and cis-regulatory elements; (3) and deciphering
regulatory cascades at the transcriptional level for embryonic stem cell
development.  To address these problems, we must overcome many computational
challenges, including little prior biological knowledge, joint effect of
many biological variables, and large model spaces for learning. 
 
Facing these computational challenges, I developed novel Bayesian methods to
analyze high-throughput data, in order to deepen our understanding of gene
regulation for organism development.  Specifically, I first devised a novel
Bayesian semi-supervised classification method to identify candidate genes
specific to certain lineages and cell-types of C. elegans embryos.  My
computational predictions about some previously uncharacterized genes were
experimentally confirmed by my biologist collaborators.  Second, I built a
new Bayesian graphical model of protein-DNA binding and developed an
approximate inference algorithm to efficiently estimate binding events in
high spatial-resolution and guide motif discovery.  The software
implementation of this algorithm is being used by research groups worldwide.
Third, I developed a novel nonparametric Bayesian model that enables the
reconstruction of a regulatory cascade for the development of embryonic stem
cells, without predefining the level of the cascade or the branching number
at each level.  Some predictions were experimentally confirmed by our
collaborators and independently by other research groups.
 
 If you have any questions or would like to meet the speaker, please contact
Ponda Barnes at pondabarnes at tti-c.org
For future TTI-C talks and events, please go to
http://ttic.uchicago.edu/cal/month.php
 
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