Modular Random Boolean Networks
Cellular Automata and Lattice Gases
2015-03-17 v2 Adaptation and Self-Organizing Systems
Molecular Networks
Abstract
Random Boolean networks (RBNs) have been a popular model of genetic regulatory networks for more than four decades. However, most RBN studies have been made with random topologies, while real regulatory networks have been found to be modular. In this work, we extend classical RBNs to define modular RBNs. Statistical experiments and analytical results show that modularity has a strong effect on the properties of RBNs. In particular, modular RBNs have more attractors and are closer to criticality when chaotic dynamics would be expected, compared to classical RBNs.
Keywords
Cite
@article{arxiv.1101.1893,
title = {Modular Random Boolean Networks},
author = {Rodrigo Poblanno-Balp and Carlos Gershenson},
journal= {arXiv preprint arXiv:1101.1893},
year = {2015}
}
Comments
33 pages, 14 figures, 11 tables. Corrected version, added experiments with large networks confirming results. Accepted in Artificial Life