Deciphering the influence of the interaction among the constituentsof a complex system on the overall behaviour is one of themain goals of complex systems science. The model we present in thiswork is a 2D square cellular automaton whose of each cell is occupiedby a complete random Boolean network. Random Boolean networks area well-known simplified model of genetic regulatory networks and thismodel of interacting RBNs may be therefore regarded as a simplifiedmodel of a tissue or a monoclonal colony. The mechanism of cell-to-cellinteraction is here simulated letting some nodes of a particular networkbeing influenced by the state of some nodes belonging to its neighbouringcells. One possible means to investigate the overall dynamics of acomplex system is studying its response to perturbations. Our analysesfollow this methodological approach. Even though the dynamics of thesystem is far from trivial we could show in a clear way how the interactionaffects the dynamics and the global degree of order.
THE DIFFUSION OF PERTURBATIONS IN A MODEL OF COUPLED RANDOM BOOLEAN NETWORKS / Serra, Roberto; Villani, Marco; Damiani, Chiara; Graudenzi, Alex; A., Colacci. - STAMPA. - 5191:(2008), pp. 315-322. (Intervento presentato al convegno 8th International Conference on Cellular Automata for Research and Industry, ACRI 2008 tenutosi a Yokohama, Japan nel 23 September 2008 through 26 September 2008) [10.1007/978-3-540-79992-4_40].
THE DIFFUSION OF PERTURBATIONS IN A MODEL OF COUPLED RANDOM BOOLEAN NETWORKS
SERRA, Roberto;VILLANI, Marco;DAMIANI, Chiara;GRAUDENZI, Alex;
2008
Abstract
Deciphering the influence of the interaction among the constituentsof a complex system on the overall behaviour is one of themain goals of complex systems science. The model we present in thiswork is a 2D square cellular automaton whose of each cell is occupiedby a complete random Boolean network. Random Boolean networks area well-known simplified model of genetic regulatory networks and thismodel of interacting RBNs may be therefore regarded as a simplifiedmodel of a tissue or a monoclonal colony. The mechanism of cell-to-cellinteraction is here simulated letting some nodes of a particular networkbeing influenced by the state of some nodes belonging to its neighbouringcells. One possible means to investigate the overall dynamics of acomplex system is studying its response to perturbations. Our analysesfollow this methodological approach. Even though the dynamics of thesystem is far from trivial we could show in a clear way how the interactionaffects the dynamics and the global degree of order.
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