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

Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Mar;73(3 Pt 1):031924. doi: 10.1103/PhysRevE.73.031924. Epub 2006 Mar 29.


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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Animals
  • Computer Simulation
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation / physiology*
  • Humans
  • Models, Genetic*
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Proteome / metabolism*
  • Signal Transduction / physiology*


  • Proteome