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Proceedings Paper

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents
Author(s): Pierre R. Bushel; Lee Bennett; Hisham Hamadeh; James Green; Alan Ableson; Steve Misener; Richard Paules; Cynthia Afshari
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Paper Abstract

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Paper Details

Date Published: 5 June 2002
PDF: 9 pages
Proc. SPIE 4623, Functional Monitoring and Drug-Tissue Interaction, (5 June 2002); doi: 10.1117/12.469471
Show Author Affiliations
Pierre R. Bushel, National Institute of Environmental Health Sciences (United States)
Lee Bennett, National Institute of Environmental Health Sciences (United States)
Hisham Hamadeh, National Institute of Environmental Health Sciences (United States)
James Green, Molecular Mining Corp. (Canada)
Alan Ableson, Molecular Mining Corp. (Canada)
Steve Misener, Molecular Mining Corp. (Canada)
Richard Paules, National Institute of Environmental Health Sciences (United States)
Cynthia Afshari, National Institute of Environmental Health Sciences (United States)


Published in SPIE Proceedings Vol. 4623:
Functional Monitoring and Drug-Tissue Interaction
Manfred D. Kessler; Gerhard J. Mueller, Editor(s)

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