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Related Experiment Video

Updated: Jun 26, 2026

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

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Published on: June 15, 2022

Quantifying local structure effects in network dynamics.

Andre S Ribeiro1, Jason Lloyd-Price, Juha Kesseli

  • 1Computational Systems Biology Research Group, Tampere University of Technology, Finland. andre.sanchesribeiro@tut.fi

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 31, 2008
PubMed
Summary
This summary is machine-generated.

Local network structure, quantified by a generalized clustering coefficient (Cp), significantly influences global network dynamics. Controlling Cp in random Boolean networks (RBNs) stabilizes their coordinated activity, revealing topology

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Area of Science:

  • Complex Systems
  • Network Science
  • Computational Biology

Background:

  • Mutual information (I) quantifies coordination between dynamical elements in networks.
  • Global network dynamics are influenced by local topological features.
  • Random Boolean networks (RBNs) serve as models for studying interacting elements.

Purpose of the Study:

  • To define a generalized clustering coefficient (Cp) that captures local structure's effect on global network dynamics.
  • To investigate the relationship between Cp, network size (N), average connectivity (k), and mutual information (I) in RBNs.
  • To develop a method for generating RBN ensembles with fixed Cp values to control network dynamics.

Main Methods:

  • Definition and calculation of a generalized clustering coefficient (Cp).
  • Analysis of mutual information (I) in ensembles of Random Boolean Networks (RBNs) with varying N and k.
  • Development of a network rewiring method to generate RBNs with controlled Cp values while preserving degree distributions.

Main Results:

  • Cp variation explains changes in global mutual information (I) with network size (N) and connectivity (k).
  • Network rewiring successfully generated RBNs with fixed Cp values, eliminating dependencies of I on N and k when Cp=0.
  • Cp exhibits a power-law dependence on N in standard RBNs, indicating its influence on large-scale networks.

Conclusions:

  • Local network topology, specifically Cp, is a critical determinant of global network dynamics.
  • Controlling Cp allows for the generation of synthetic networks with predictable dynamics, mimicking large-scale behavior.
  • The findings suggest that biological network topology may be shaped by selection to optimize component coordination.