Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks

Authors:
Seiya Imoto;Tomoyuki Higuchi;Takao Goto;Kousuke Tashiro;Satoru Kuhara;Satoru Miyano
Affiliations:
-;-;-;-;-;-
Venue:
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Year:
2003

Citing 5
Cited 10

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Abstract

We propose a statistical method for estimating a genenetwork based on Bayesian networks from microarray geneexpression data together with biological knowledge includingprotein-protein interactions, protein-DNA interactions,binding site information, existing literature and so on. Unfortunately,microarray data do not contain enough informationfor constructing gene networks accurately in manycases. Our method adds biological knowledge to the estimationmethod of gene networks under a Bayesian statisticalframework, and also controls the trade-off betweenmicroarray information and biological knowledge automatically.We conduct Monte Carlo simulations to show theeffectiveness of the proposed method. We analyze Saccharomycescerevisiae gene expression data as an application.