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Microarray Gene Co-Expression Analysis And Validation
by
Cheng Cheng
St. Jude Children's Research Hospital
Most microarray gene expression analyses have focused on the analysis of each gene (probe) individually. Because genes form complex signaling and regulatory pathways in carrying out their biological functions, existence of co-expressions are plausible in even a snap-shot microarray gene expression experiment, and such co-expressions may be reflected by the stochastic relationships among the genes’ expression data. Detecting the co-expressions may help identify the underlying signaling/regulatory pathways involved in the biological process of interest. A clustering algorithm for this purpose, coupled with an inference procedure for validation in another, independent gene expression data set, will be presented in this talk. The methodology will be illustrated by a real-data example.
Date received: July 27, 2007
Copyright © 2007 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cavm-08.