Target Discovery and Validation Reviews and Protocols

3
Analysis of Gene Networks
for Drug Target Discovery and Validation
Seiya Imoto, Yoshinori Tamada, Christopher J. Savoie,
and Satoru Miyano
Summary
Understanding responses of the cellular system for a dosing molecule is one of the most
important problems in pharmacogenomics. In this chapter, we describe computational methods
for identifying and validating drug target genes based on the gene networks estimated from
microarray gene expression data. We use two types of microarray gene expression data: gene disruptant
microarray data and time-course drug response microarray data. For this purpose, the
information of gene networks plays an essential role and is unattainable from clustering methods,
which are the standard for gene expression analysis. The gene network is estimated from disruptant
microarray data by the Bayesian network model, and then the proposed method automatically
identifies sets of genes or gene regulatory pathways affected by the drug. We use an actual
example from analysis of Saccharomyces cerevisiae gene expression profile data to express a
concrete strategy for the application of gene network information toward drug target discovery.
Key Words: Bayes statistics; Bayesian network; Boolean network; drug target; gene network;
microarray data.
1. Introduction
In recent years, microarray technology has produced a large volume of genomewide
gene expression data under various experimental conditions, such as gene
disruptions, gene overexpressions, shocks, cancer cells, and so on (Chapters 4 and
5, Volume 1). Based on this new data production, there have been considerable
attempts to estimate gene networks from such gene expression data, and several
computational methods have been proposed together with mathematical models
for gene networks, such as Boolean networks (1–3), differential equation models
From: Methods in Molecular Biology, vol. 360, Target Discovery and Validation Reviews and Protocols
Volume I, Emerging Strategies for Targets and Biomarker Discovery
Edited by: M. Sioud © Humana Press Inc., Totowa, NJ
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