Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles

Seiya Imoto, Yoshinor Tamada, Hiromitsu Araki, Kaori Yasuda, Cristin G. Print, Stephen D. Charnock-Jones, Deborah Sanders, Christopher J. Savoie, Kousuke Tashiro, Satoru Kuhara, Satoru Miyano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

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-a, which is a known target of fenofibrate.

Original languageEnglish
Title of host publicationProceedings of the Pacific Symposium on Biocomputing 2006, PSB 2006
Pages559-571
Number of pages13
Publication statusPublished - 2006
Event11th Pacific Symposium on Biocomputing 2006, PSB 2006 - Maui, HI, United States
Duration: Jan 3 2006Jan 7 2006

Publication series

NameProceedings of the Pacific Symposium on Biocomputing 2006, PSB 2006

Other

Other11th Pacific Symposium on Biocomputing 2006, PSB 2006
CountryUnited States
CityMaui, HI
Period1/3/061/7/06

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Medicine(all)

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    Imoto, S., Tamada, Y., Araki, H., Yasuda, K., Print, C. G., Charnock-Jones, S. D., Sanders, D., Savoie, C. J., Tashiro, K., Kuhara, S., & Miyano, S. (2006). Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles. In Proceedings of the Pacific Symposium on Biocomputing 2006, PSB 2006 (pp. 559-571). (Proceedings of the Pacific Symposium on Biocomputing 2006, PSB 2006).