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Seminar Announcement

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*Network-based Statistical Models and Methods for Identification of
Cellular Mechanisms of Action*

*Eric Kolaczyk*

*Department of Mathematics and Statistics *

*Boston University*

*Johnson Center G19 - Gold Room*

* 4400 University Drive, Fairfax, VA 22030***

*Time: 11:00 A.M. - 12:00 P.M.***

*Date: Friday, Apr 5, 2013 ***

*Abstract*

Identifying biological mechanisms of action (e.g. biological pathways) that
control disease states, drug response, and altered cellular function is a
multifaceted problem involving a dynamic system of biological variables
that culminate in an altered cellular state. The challenge is in
deciphering the factors that play key roles in determining the cell's fate.
In this talk I will describe some of the efforts by our group to develop
statistical models and methods for identification of cellular mechanisms of
action. More specifically, we assume gene expression data and treat the
problem of determining mechanisms of action under perturbation (e.g., drug
treatment, gene knockout, etc.) as a type of inverse problem. I will
describe three approaches to solving this inverse problem. The first
attempts to use only the gene expression data and to `filter' that data by
an inferred network of gene regulatory interactions. The other two -- one
testing-based and the other regression-based -- use gene expression data in
conjunction with information from biological databases. More specifically,
gene expression is modeled as deriving from a perturbed latent network of
pathways, where the inter-connections among pathways is informed by shared
biological function. Illustrations are given in the context of yeast
experiments and human cancer.

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-- 
Yunpeng Zhao, PhD

Assistant Professor
Department of Statistics
Volgenau School of Engineering <[log in to unmask]>
George Mason University
Engineering Building, Room 1719, MS 4A7
4400 University Drive
Fairfax, VA 22030-4444

Phone: 703-993-1674
Email: [log in to unmask]