Topology of biological networks and reliability of information processing

Konstantin Klemm, Stefan Bornholdt

Research output: Contribution to journalArticle

133 Citations (Scopus)

Abstract

Survival of living cells and organisms is largely based on highly reliable function of their regulatory networks. However, the elements of biological networks, e.g., regulatory genes in genetic networks or neurons in the nervous system, are far from being reliable dynamical elements. How can networks of unreliable elements perform reliably? We here address this question in networks of autonomous noisy elements with fluctuating timing and study the conditions for an overall system behavior being reproducible in the presence of such noise. We find a clear distinction between reliable and unreliable dynamical attractors. In the reliable case, synchrony is sustained in the network, whereas in the unreliable scenario, fluctuating timing of single elements can gradually desynchronize the system, leading to nonreproducible behavior. The likelihood of reliable dynamical attractors strongly depends on the underlying topology of a network. Comparing with the observed architectures of gene regulation networks, we find that those 3-node subgraphs that allow for reliable dynamics are also those that are more abundant in nature, suggesting that specific topologies of regulatory networks may provide a selective advantage in evolution through their resistance against noise.

Original languageEnglish
Pages (from-to)18414-18419
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume102
Issue number51
DOIs
Publication statusPublished - Dec 20 2005
Externally publishedYes

Fingerprint

Gene Regulatory Networks
Automatic Data Processing
Noise
Nervous System
Cell Survival
Neurons

Keywords

  • Biological computation
  • Computer model
  • Genetic networks
  • Robustness
  • Stability

ASJC Scopus subject areas

  • General
  • Genetics

Cite this

Topology of biological networks and reliability of information processing. / Klemm, Konstantin; Bornholdt, Stefan.

In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 102, No. 51, 20.12.2005, p. 18414-18419.

Research output: Contribution to journalArticle

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