Boolean modeling of collective effects in complex networks.

Journal Article

Complex systems are often modeled as Boolean networks in attempts to capture their logical structure and reveal its dynamical consequences. Approximating the dynamics of continuous variables by discrete values and Boolean logic gates may, however, introduce dynamical possibilities that are not accessible to the original system. We show that large random networks of variables coupled through continuous transfer functions often fail to exhibit the complex dynamics of corresponding Boolean models in the disordered (chaotic) regime, even when each individual function appears to be a good candidate for Boolean idealization. A suitably modified Boolean theory explains the behavior of systems in which information does not propagate faithfully down certain chains of nodes. Model networks incorporating calculated or directly measured transfer functions reported in the literature on transcriptional regulation of genes are described by the modified theory.

Full Text

Duke Authors

Cited Authors

  • Norrell, J; Socolar, JE

Published Date

  • June 8, 2009

Published In

Volume / Issue

  • 79 / 6

Start / End Page

  • nihpa131303 -

PubMed ID

  • 19649269

Pubmed Central ID

  • PMC2718684

Electronic International Standard Serial Number (EISSN)

  • 1550-2376

Digital Object Identifier (DOI)

  • 10.1103/PhysRevE.79.061908

Language

  • ENG