title: Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles.
abstract: We propose a computational strategy for discovering gene networks affected by a chemical compound. Two kinds of DNA microarray data are assumed to be used: One dataset is short time-course data that measure responses of genes following an experimental treatment. The other dataset is obtained by several hundred single gene knock-downs. These two datasets provide three kinds of information; (i) A gene network is estimated from time-course data by the dynamic Bayesian network model, (ii) Relationships between the knocked-down genes and their regulatees are estimated directly from knock-down microarrays and (iii) A gene network can be estimated by gene knock-down data alone using the Bayesian network model. We propose a method that combines these three kinds of information to provide an accurate gene network that most strongly relates to the mode-of-action of the chemical compound in cells. This information plays an essential role in pharmacogenomics. We illustrate this method with an actual example where human endothelial cell gene networks were generated from a novel time course of gene expression following treatment with the drug fenofibrate, and from 270 novel gene knock-downs. Finally, we succeeded in inferring the gene network related to PPAR-alpha, which is a known target of fenofibrate.
authors.affiliation: Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1, Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.
authors.forename: Seiya
authors.initials: S
authors.lastname: Imoto
authors.forename: Yoshinori
authors.initials: Y
authors.lastname: Tamada
authors.forename: Hiromitsu
authors.initials: H
authors.lastname: Araki
authors.forename: Kaori
authors.initials: K
authors.lastname: Yasuda
authors.forename: Cristin G
authors.initials: CG
authors.lastname: Print
authors.forename: Stephen D
authors.initials: SD
authors.lastname: Charnock-Jones
authors.forename: Deborah
authors.initials: D
authors.lastname: Sanders
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Savoie
authors.forename: Kousuke
authors.initials: K
authors.lastname: Tashiro
authors.forename: Satoru
authors.initials: S
authors.lastname: Kuhara
authors.forename: Satoru
authors.initials: S
authors.lastname: Miyano
mesh_terms: D001499:Bayes Theorem; D019295:Computational Biology; D042783:Endothelial Cells / Q000187:drug effects / Q000378:metabolism; D011345:Fenofibrate / Q000494:pharmacology; D015870:Gene Expression / Q000187:drug effects; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D047493:PPAR alpha / Q000235:genetics; D010597:Pharmacogenetics; D012313:RNA / Q000235:genetics*; D034741:RNA, Small Interfering / Q000235:genetics
chemical_list: D047493:PPAR alpha; D034741:RNA, Small Interfering; D012313:RNA; D011345:Fenofibrate