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Bioinformatics Vol. 19 no. 9 2003
Pages 1124-1131
© 2003 Oxford University Press

Gene interaction in DNA microarray data is decomposed by information geometric measure

Hiroyuki Nakahara 1,*, Shin-ichi Nishimura 1,3, Masato Inoue 1,4, Gen Hori 2 and Shun-ichi Amari 1

1 Lab. for Mathematical Neuroscience, RIKEN Brain Science Institute, Saitama 351-0198
2 Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute
3 Department of Otolaryngology, Faculty of Medicine, University of Tokyo
4 Department of Otolaryngology, Graduate School of Medicine, Kyoto University, Japan

Received on May 1, 2002 ; revised on November 18, 2002 and December 10, 2002 ; accepted on December 18, 2002

Motivation: Given the vast amount of gene expression data, it is essential to develop a simple and reliable method of investigating the fine structure of gene interaction. We show how an information geometric measure achieves this

Results: We introduce an information geometric measure of binary random vectors and show how this measure reveals the fine structure of gene interaction. In particular, we propose an iterative procedure by using this measure (called IPIG). The procedure finds higher-order dependencies which may underlie the interaction between two genes of interest. To demonstrate the method, we investigate the interaction between the two genes of interest in the data from human acute lymphoblastic leukemia cells. The method successfully discovered biologically known findings and also selected other genes as hidden causes that constitute the interaction

Availability: Softwares are currently not available but are possibly made available in future at http://www.mns.brain.riken.go.jp/~nakahara/DNA_pub.html where all the related information is also linked.

Contact: hiro{at}brain.riken.go.jp

* To whom correspondence should be addressed.


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