Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Scaling in ordered and critical random boolean networks.

J E S Socolar1, S A Kauffman

  • 1Bios Group and Santa Fe Institute, Santa Fe, New Mexico 87501, USA.

Physical Review Letters
|March 14, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Extrinsic and intrinsic effects setting viscosity in complex fluids and life processes: the role of fundamental physical constants.

The European physical journal. E, Soft matter·2025
Same author

Mixed anhydrides at the intersection between peptide and RNA autocatalytic sets: evolution of biological coding.

Interface focus·2023
Same author

Directed force chain networks and stress response in static granular materials.

The European physical journal. E, Soft matter·2016
Same author

Robustness analysis of a Boolean model of gene regulatory network with memory.

Journal of computational biology : a journal of computational molecular cell biology·2011
Same author

Cell-cell interaction and diversity of emergent behaviours.

IET systems biology·2011
Same author

Phase transition in a class of nonlinear random networks.

Physical review. E, Statistical, nonlinear, and soft matter physics·2010
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

Random Boolean networks, used for modeling complex systems, exhibit critical dynamics relevant to biology. Studies show that key scaling properties for these networks only appear in very large systems.

Area of Science:

  • Complex systems science
  • Computational biology
  • Network theory

Background:

  • Random Boolean networks (RBNs) model genetic regulatory networks and complex systems.
  • Biological systems often operate near a critical point separating ordered and chaotic dynamics.
  • Understanding network properties at criticality is crucial for biological insights.

Purpose of the Study:

  • Investigate scaling properties of RBNs at criticality.
  • Analyze the average number of dynamically relevant nodes.
  • Determine the median number of distinct attractors in large-scale RBNs.

Main Methods:

  • Theoretical analysis of Random Boolean networks.
  • Computational simulations of network dynamics.
  • Examination of scaling behavior with system size.

Related Experiment Videos

Main Results:

  • The average number of dynamically relevant nodes scales with system size.
  • The median number of distinct attractors also exhibits specific scaling.
  • Accurate asymptotic scaling laws are observed only for very large networks.

Conclusions:

  • Critical dynamics in RBNs are essential for modeling biological complexity.
  • Scaling properties are robust indicators of network behavior at criticality.
  • Future research should focus on large-scale network analysis to capture emergent phenomena.