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. © 2011, Mary Ann Liebert, Inc.
Graudenzi, A., Serra, R., Villani, M., Damiani, C., Colacci, A., Kauffman, S. (2011). Dynamical properties of a Boolean model of gene regulatory network with memory. JOURNAL OF COMPUTATIONAL BIOLOGY, 18(10), 1291-1303 [10.1089/cmb.2010.0069].
Dynamical properties of a Boolean model of gene regulatory network with memory
Graudenzi A
;Serra R;Damiani C;
2011
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. © 2011, Mary Ann Liebert, Inc.File | Dimensione | Formato | |
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