Use of gene networks for identifying and validating drug targets.
We propose a new method for identifying and validating drug targets by using gene networks, which are estimated from cDNA microarray gene expression profile data. We created novel gene disruption and drug response microarray gene expression profile data libraries for the purpose of drug target elucidation. We use two types of microarray gene expression profile data for estimating gene networks and then identifying drug targets. The estimated gene networks play an essential role in understanding drug response data and this information is unattainable from clustering methods, which are the standard for gene expression analysis. In the construction of gene networks, we use the Bayesian network model. We use an actual example from analysis of the Saccharomyces cerevisiae gene expression profile data to express a concrete strategy for the application of gene network information to drug discovery.
Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan. imoto@ims.u-tokyo.ac.jp
Seiya
S
Imoto
Christopher J
CJ
Savoie
Sachiyo
S
Aburatani
Sunyong
S
Kim
Kousuke
K
Tashiro
Satoru
S
Kuhara
Satoru
S
Miyano
D000465:Algorithms; D001499:Bayes Theorem; D016000:Cluster Analysis; D019295:Computational Biology; D015870:Gene Expression / Q000187:drug effects*; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D005800:Genes, Fungal / Q000187:drug effects; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics; D014584:User-Computer Interface