proceeding Papers Interacting Random Boolean Networks


Random Boolean networks (RBN) have been extensively studied as models of genetic regulatory networks. While many studies have been devoted to the dynamics of isolated random Boolean networks, which may considered as models of isolated cells, in this paper we consider a set of interacting RBNs, which may be regarded as a simplified model of a tissue or a monoclonal colony. In order to do so, we introduce a cellular automata (CA) model, where each cell site is occupied by a RBN. The mutual influence among cells is modelled by letting the activation of some genes in a RBN be affected by that of some genes in neighbouring RBNs. It is shown that the dynamics of the CA is far from trivial. Different measures are introduced to provide indications about the overall behaviour. In a sense which is made precise in the text, it is shown that the degree of order of the CA is affected by the interaction strength, and that markedly different behaviours are observed. We propose a classification of these behaviours into four classes, based upon the way in which the various measures of order are affected by the interaction strength. It is shown that the dynamical properties of isolated RBNs affect the probability that a CA composed by those RBNs belongs to one of the four classes, and therefore also affects the probability that a higher interaction strength leads to a greater, or a smaller, degree of or

Paper Details


R. Serra,  M. Villani,  C. Damiani,  A. Graudenzi,  P. Ingrami


Proceedings of the European Conference on Complex Systems (ECCS 07 Dresden, October 2007)