Scaling in ordered and critical random boolean networks

Phys Rev Lett. 2003 Feb 14;90(6):068702. doi: 10.1103/PhysRevLett.90.068702. Epub 2003 Feb 13.

Abstract

Random Boolean networks, originally invented as models of genetic regulatory networks, are simple models for a broad class of complex systems that show rich dynamical structures. From a biological perspective, the most interesting networks lie at or near a critical point in parameter space that divides "ordered" from "chaotic" attractor dynamics. We study the scaling of the average number of dynamically relevant nodes and the median number of distinct attractors in such networks. Our calculations indicate that the correct asymptotic scalings emerge only for very large systems.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression
  • Mathematical Computing
  • Models, Genetic*
  • Nonlinear Dynamics