TY - JOUR T1 - Modular Random {Boolean} Networks JF - Artificial Life Y1 - 2011 A1 - Rodrigo {Poblanno-Balp} A1 - Carlos Gershenson AB - 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. PB - MIT Press VL - 17 UR - http://arxiv.org/abs/1101.1893 ER - TY - CHAP T1 - Modular Random {Boolean} Networks T2 - {Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems Y1 - 2010 A1 - Rodrigo {Poblanno-Balp} A1 - Carlos Gershenson ED - Harold Fellermann ED - Mark Dörr ED - Martin M. Hanczyc ED - Lone Ladegaard Laursen ED - Sarah Maurer ED - Daniel Merkle ED - Pierre-Alain Monnard ED - Kasper St$ø$y ED - Steen Rasmussen JF - {Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems PB - MIT Press CY - Odense, Denmark UR - http://mitpress.mit.edu/books/chapters/0262290758chap56.pdf ER -