Coupled random boolean network forming an artificial tissue
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Information transfer among coupled random boolean networks
ACRI'10 Proceedings of the 9th international conference on Cellular automata for research and industry
A new evolutionary gene regulatory network reverse engineering tool
EvoBIO'11 Proceedings of the 9th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Modular random boolean networks1
Artificial Life
Criticality of spatiotemporal dynamics in contact mediated pattern formation
IPCAT'12 Proceedings of the 9th international conference on Information Processing in Cells and Tissues
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Deciphering the influence of the interaction among the constituents of a complex system on the overall behaviour is one of the main goals of complex systems science. The model we present in this work is a 2D square cellular automaton whose of each cell is occupied by a complete random Boolean network. Random Boolean networks are a well-known simplified model of genetic regulatory networks and this model of interacting RBNs may be therefore regarded as a simplified model of a tissue or a monoclonal colony. The mechanism of cell-to-cell interaction is here simulated letting some nodes of a particular network being influenced by the state of some nodes belonging to its neighbouring cells. One possible means to investigate the overall dynamics of a complex system is studying its response to perturbations. Our analyses follow this methodological approach. Even though the dynamics of the system is far from trivial we could show in a clear way how the interaction affects the dynamics and the global degree of order.