Application of random matrix theory to microarray data for discovering functional gene modules

被引：71

作者：

Luo, F

Zhong, JX ^{[1
]}

Yang, YF

Zhou, JZ

机构：

[1] Xiangtan Univ, Dept Phys, Xiangtan 411105, Peoples R China

[2] Clemson Univ, Dept Comp Sci, Clemson, SC 29634 USA

[3] Oak Ridge Natl Lab, Div Math & Comp Sci, Oak Ridge, TN 37831 USA

[4] Oak Ridge Natl Lab, Div Environm Sci, Oak Ridge, TN 37831 USA

[5] Univ Oklahoma, Dept Bot & Microbiol, Norman, OK 73019 USA

来源：

PHYSICAL REVIEW E | 2006年 / 73卷 / 03期

关键词：

D O I：

10.1103/PhysRevE.73.031924

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

We show that spectral fluctuation of coexpression correlation matrices of yeast gene microarray profiles follows the description of the Gaussian orthogonal ensemble (GOE) of the random matrix theory (RMT) and removal of small values of the correlation coefficients results in a transition from the GOE statistics to the Poisson statistics of the RMT. This transition is directly related to the structural change of the gene expression network from a global network to a network of isolated modules.

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LUO F, UNPUB