Information transfer among coupled random boolean networks

Authors:
Chiara Damiani;Stuart A. Kauffman;Roberto Serra;Marco Villani;Annamaria Colacci
Affiliations:
Department of Social, Cognitive and Quantitative Sciences, Modena and Reggio Emilia University, Reggio Emilia;Departments of Biochemistry and Mathematics, University of Vermont, Burlington, VT;Department of Social, Cognitive and Quantitative Sciences, Modena and Reggio Emilia University, Reggio Emilia;Department of Social, Cognitive and Quantitative Sciences, Modena and Reggio Emilia University, Reggio Emilia;Excellence Environmental Carcinogenesis, Environmental Protection and Health Prevention Agency, Bologna, Italia
Venue:
ACRI'10 Proceedings of the 9th international conference on Cellular automata for research and industry
Year:
2010

Citing 3
Cited 3

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Abstract

Information processing and information flow occur at many levels in the course of an organism's development and throughout its lifespan. Biological networks inside cells transmit information from their inputs (e.g. the concentrations of proteins or other signaling molecules) to their outputs (e.g. the expression levels of various genes). Moreover, cells do not exist in isolation, but they constantly interact with one another. We study the information flow in a model of interacting genetic networks, which are represented as Boolean graphs. It is observed that the information transfer among the networks is not linearly dependent on the amount of nodes that are able to influence the state of genes in surrounding cells.