Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network

S. Imoto, Kim Sunyong, T. Goto, S. Aburatani, Kosuke Tashiro, S. Kuhara, S. Miyano

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

15 Citations (Scopus)

Abstract

We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network construction is in the estimation of the conditional distribution of each random variable. We consider fitting nonparametric regression models with heterogeneous error variances to the microarray gene expression data to capture the nonlinear structures between genes. A problem still remains to be solved in selecting an optimal graph, which gives the best representation of the system among genes. We theoretically derive a new graph selection criterion from Bayes approach in general situations. The proposed method includes previous methods based on Bayesian networks. We demonstrate the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae gene expression data newly obtained by disrupting 100 genes.

Original languageEnglish
Title of host publicationProceedings - IEEE Computer Society Bioinformatics Conference, CSB 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages219-227
Number of pages9
ISBN (Electronic)076951653X, 9780769516530
DOIs
Publication statusPublished - Jan 1 2002
Event1st International IEEE Computer Society Bioinformatics Conference, CSB 2002 - Stanford, United States
Duration: Aug 14 2002Aug 16 2002

Other

Other1st International IEEE Computer Society Bioinformatics Conference, CSB 2002
CountryUnited States
CityStanford
Period8/14/028/16/02

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Biomedical Engineering
  • Health Informatics

Cite this

Imoto, S., Sunyong, K., Goto, T., Aburatani, S., Tashiro, K., Kuhara, S., & Miyano, S. (2002). Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. In Proceedings - IEEE Computer Society Bioinformatics Conference, CSB 2002 (pp. 219-227). [1039344] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSB.2002.1039344