Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

Naoki Nariai, S. Kim, S. Imoto, S. Miyano

Research output: Contribution to journalArticlepeer-review

66 Citations (Scopus)

Abstract

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Original languageEnglish
Pages (from-to)336-347
Number of pages12
JournalPacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Publication statusPublished - 2004 Jan 1

ASJC Scopus subject areas

  • Medicine(all)

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