Gene Networks Viewed through Two Models

Authors:
Satoru Miyano;Rui Yamaguchi;Yoshinori Tamada;Masao Nagasaki;Seiya Imoto
Affiliations:
Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan 108-8639;Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan 108-8639;Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan 108-8639;Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan 108-8639;Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan 108-8639
Venue:
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
Year:
2009

Citing 3
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Abstract

This paper presents our computational and measurement strategy for investigating gene networks from gene expression data using state space model and dynamic Bayesian network model with nonparametric regression. These methods are applied to gene expression data based on gene knockdowns and drug responses for generating large global maps of gene regulation which will light up the geography where drug target pathways lie down.