Quarterly (winter, spring, summer, fall)
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ISSN
1064-5462
E-ISSN
1530-9185
2014 Impact factor:
1.39

Artificial Life

Fall 2011, Vol. 17, No. 4, Pages 331-351
(doi: 10.1162/artl_a_00042)
© 2011 Massachusetts Institute of Technology
Modular Random Boolean Networks1
Article PDF (703.78 KB)
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, than classical RBNs.