Estimating gene networks from expression data and binding location data via boolean networks

Osamu Hirose, Naoki Nariai, Yoshinori Tamada, Hideo Bannai, Seiya Imoto, Satoru Miyano

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

In this paper, we propose a computational method for estimating gene networks by the Boolean network model. The Boolean networks have some practical problems in analyzing DNA microarray gene expression data: One is the choice of threshold value for discretization of gene expression data, since expression data take continuous variables. The other problem is that it is often the case that the optimal gene network is not determined uniquely and it is difficult to choose the optimal one from the candidates by using expression data only. To solve these problems, we use the binding location data produced by Lee et al. [8] together with expression data and illustrate a strategy to decide the optimal threshold and gene network. To show the effectiveness of the proposed method, we analyze Saccharomyces cerevisiae cell cycle gene expression data as a real application.

Original languageEnglish
Pages (from-to)349-356
Number of pages8
JournalUnknown Journal
Volume3482
Issue numberIII
Publication statusPublished - 2005
Externally publishedYes

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All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)

Cite this

Hirose, O., Nariai, N., Tamada, Y., Bannai, H., Imoto, S., & Miyano, S. (2005). Estimating gene networks from expression data and binding location data via boolean networks. Unknown Journal, 3482(III), 349-356.