Published September 25, 2006 | Version v1
Journal article

Application of random matrix theory to biological networks

  • 1. Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States)
  • 2. Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, SC 29634 (United States)
  • 3. Department of Physics, Xiangtan University, Hunan 411105 (China) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)
  • 4. Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)
  • 5. Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019 (United States) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

Description

We show that spectral fluctuation of interaction matrices of a yeast protein-protein interaction network and a yeast metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we demonstrate that while the global biological networks evaluated belong to GOE, removal of interactions between constituents transitions the networks to systems of isolated modules described by the Poisson distribution. Our results indicate that although biological networks are very different from other complex systems at the molecular level, they display the same statistical properties at network scale. The transition point provides a new objective approach for the identification of functional modules

Additional details

Identifiers

DOI
10.1016/j.physleta.2006.04.076;
arXiv
arXiv:q-bio/0503035v1;
PII
S0375-9601(06)00653-0;

Publishing Information

Journal Title
Physics Letters. A
Journal Volume
357
Journal Issue
6
Journal Page Range
p. 420-423
ISSN
0375-9601
CODEN
PYLAAG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
38067131
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
BIOLOGICAL MODELS; MATRICES; PROTEINS; RANDOMNESS; YEASTS
Descriptors DEC
EUMYCOTA; FUNGI; MICROORGANISMS; ORGANIC COMPOUNDS; PLANTS

Optional Information

Copyright
Copyright (c) 2006 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.