Modular Random Boolean Networks

被引：20

作者：

Poblanno-Balp, Rodrigo ^{[1
,2
]}

Gershenson, Carlos ^{[1
,2
]}

机构：

[1] Univ Nacl Autonoma Mexico, Inst Invest Matemat Aplicadas & Sistemas, Mexico City 04510, DF, Mexico

[2] Univ Nacl Autonoma Mexico, Ctr Ciencias Complejidad, Mexico City 04510, DF, Mexico

来源：

ARTIFICIAL LIFE | 2011年 / 17卷 / 04期

关键词：

Modularity; criticality; topology; random Boolean networks; genetic regulatory networks; PHASE-TRANSITIONS; ROBUSTNESS; REDUNDANCY; DYNAMICS; CHAOS;

D O I：

10.1162/artl_a_00042

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：331 / 351

页数：21

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