Journal Papers Dynamical properties of a Boolean model of gene regulatory network with memory


Abstract

Classical random Boolean networks (RBN) are not well suited to describe experimental data from time-course microarray, mainly because of the strict assumptions about the synchronicity of the regulatory mechanisms. In order to overcome this setback, a generalization of the RBN model is described and analyzed. Gene products (e.g., regulatory proteins) are introduced, with each one characterized by a specific decay time, thereby introducing a form of memory in the system. The dynamics of these networks is analyzed, and it is shown that the distribution of the decay times has a strong effect that can be adequately described and understood. The implications for the dynamical criticality of the networks are also discussed.



Paper Details

Authors

A. Graudenzi,  R. Serra,  M. Villani,  C. Damiani,  A. Colacci,  S. Kauffman

Publication

Journal of Computational Biology, 18, , 1-13

Download

http://www.liebertonline.com/doi/abs/10.1089/cmb.2010.0069

Language

English
.