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

Hiroyuki Nakahara*, Shin Ichi Nishimura, Masato Inoue, Gen Hori, Shun Ichi Amari

*この研究の対応する著者

研究成果: Article査読

8 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)1124-1131
ページ数8
ジャーナルBioinformatics
19
9
DOI
出版ステータスPublished - 2003 6月 12
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率
  • 生化学
  • 分子生物学
  • コンピュータ サイエンスの応用
  • 計算理論と計算数学
  • 計算数学

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