Robustness Analysis of a Boolean Model of Gene Regulatory Network with Memory

The response to different kinds of perturbations of a discrete model of gene regulatory network, which is a generalization of the random Boolean network (RBN) model, is discussed. The model includes memory effects, and the analysis pays particular attention to the influence on the system stability of a parameter (i.e., the decay time of the gene products) that determines the duration of the memory effects. It is shown that this parameter deeply affects the overall behavior of the system, with special regard to the dynamical regimes and the sensitivity. Furthermore, a noteworthy divergence in the response of systems characterized by different memory lengths in the presence of either temporary or permanent damages is highlighted, as is the substantial difference, with respect to classical RBNs, between the specific dynamical regime and the landscape of the attractors.

[1]  Roberto Serra,et al.  On the fate of perturbations in critical random Boolean networks , 2009 .

[2]  Guy Karlebach,et al.  Modelling and analysis of gene regulatory networks , 2008, Nature Reviews Molecular Cell Biology.

[3]  Stuart A. Kauffman,et al.  ORIGINS OF ORDER , 2019, Origins of Order.

[4]  Uri Alon,et al.  An Introduction to Systems Biology , 2006 .

[5]  S. Kauffman,et al.  On the dynamics of random Boolean networks subject to noise: attractors, ergodic sets and cell types. , 2010, Journal of theoretical biology.

[6]  M Villani,et al.  Genetic network models and statistical properties of gene expression data in knock-out experiments. , 2004, Journal of theoretical biology.

[7]  Nicola J. Rinaldi,et al.  Transcriptional Regulatory Networks in Saccharomyces cerevisiae , 2002, Science.

[8]  Heinz Georg Schuster,et al.  Reviews of nonlinear dynamics and complexity , 2008 .

[9]  S. Kauffman.  Gene regulation networks: a theory for their global structure and behaviors. , 1971, Current topics in developmental biology.

[10]  Bing Su,et al.  Small but influential: the role of microRNAs on gene regulatory network and 3'UTR evolution. , 2009, Journal of genetics and genomics = Yi chuan xue bao.

[11]  D. Noble.  Music of life : biology beyond the genome , 2006 .

[12]  James R. Knight,et al.  A Protein Interaction Map of Drosophila melanogaster , 2003, Science.

[13]  Roberto Serra,et al.  Genetic Regulatory Networks and Neural Networks , 2009, WIRN.

[14]  B. Derrida,et al.  Random networks of automata: a simple annealed approximation , 1986 .

[15]  Roberto Serra,et al.  Timing of molecular processes in a synchronous Boolean model of genetic regulatory network , 2009 .

[16]  S. Kauffman.  Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[17]  G. Parisi,et al.  The modular structure of Kauffman networks , 1997, cond-mat/9708214.

[18]  Stijn van Dongen,et al.  miRBase: microRNA sequences, targets and gene nomenclature , 2005, Nucleic Acids Res..

[19]  Ilya Shmulevich,et al.  Eukaryotic cells are dynamically ordered or critical but not chaotic. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[20]  John Archibald Wheeler,et al.  At Home in the Universe , 1994 .

[21]  Barbara Drossel.  Number of attractors in random Boolean networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Hiroaki Kitano,et al.  Foundations of systems biology , 2001 .

[23]  O. Yli-Harja,et al.  Perturbation avalanches and criticality in gene regulatory networks. , 2006, Journal of theoretical biology.

[24]  M Chaves,et al.  Methods of robustness analysis for Boolean models of gene control networks. , 2006, Systems biology.

[25]  M. Tyers,et al.  From genomics to proteomics , 2003, Nature.

[26]  L Glass,et al.  Co-operative components, spatial localization and oscillatory cellular dynamics. , 1972, Journal of theoretical biology.

[27]  Lan V. Zhang,et al.  Evidence for dynamically organized modularity in the yeast protein–protein interaction network , 2004, Nature.

[28]  M. Gerstein,et al.  Genomic analysis of regulatory network dynamics reveals large topological changes , 2004, Nature.

[29]  René Thomas.  Regulatory networks seen as asynchronous automata: A logical description , 1991 .

[30]  Vasant Honavar,et al.  Temporal Boolean Network Models of Genetic Networks and their Inference from Gene Expression Time Series , 2001, Complex Syst..

[31]  Roberto Serra,et al.  Dynamical Properties of a Boolean Model of Gene Regulatory Network with Memory , 2011, J. Comput. Biol..

[32]  L. Glass,et al.  The logical analysis of continuous, non-linear biochemical control networks. , 1973, Journal of theoretical biology.

[33]  R. Thomas,et al.  Boolean formalization of genetic control circuits. , 1973, Journal of theoretical biology.

[34]  S. L. Wong,et al.  A Map of the Interactome Network of the Metazoan C. elegans , 2004, Science.

[35]  Carsten Peterson,et al.  Random Boolean network models and the yeast transcriptional network , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[36]  S. Kauffman,et al.  Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data. , 2007, Journal of theoretical biology.

[37]  Roberto Serra,et al.  The simulation of gene knock-out in scale-free random Boolean models of genetic networks , 2008, Networks Heterog. Media.

[38]  Kunihiko Kaneko,et al.  Life: An Introduction to Complex Systems Biology , 2006 .

[39]  Jerrold E. Marsden,et al.  Perspectives and Problems in Nonlinear Science , 2003 .

[40]  H. Kitano,et al.  Computational systems biology , 2002, Nature.

[41]  S. Kauffman.  Homeostasis and Differentiation in Random Genetic Control Networks , 1969, Nature.

[42]  Christopher G. Langton,et al.  Life at the Edge of Chaos , 1992 .

[43]  Jeffrey W. Roberts,et al.  遺伝子の分子生物学 = Molecular biology of the gene , 1970 .

[44]  J. Doyle,et al.  Reverse Engineering of Biological Complexity , 2002, Science.