Stochastic model of yeast cell-cycle network

Biological functions in living cells are controlled by protein interaction and genetic networks. These molecular networks should be dynamically stable against various fluctuations which are inevitable in the living world. In this paper, we propose and study a stochastic model for the network regulating the cell cycle of the budding yeast. The stochasticity in the model is controlled by a temperature-like parameter . Our simulation results show that both the biological stationary state and the biological pathway are stable for a wide range of “temperature”. There is, however, a sharp transition-like behavior at c, below which the dynamics are dominated by noise. We also define a pseudo energy landscape for the system in which the biological pathway can be seen as a deep valley. c 2006 Elsevier B.V. All rights reserved.

[1]  S. Counce.  The Strategy of the Genes , 1958, The Yale Journal of Biology and Medicine.

[2]  B. Futcher.  Transcriptional regulatory networks and the yeast cell cycle. , 2002, Current opinion in cell biology.

[3]  A. Murray,et al.  Recycling the Cell Cycle Cyclins Revisited , 2004, Cell.

[4]  Chen Dayue,et al.  Metastability of exponentially perturbed Markov chains , 1996 .

[5]  Edward R. Dougherty,et al.  Steady-state probabilities for attractors in probabilistic Boolean networks , 2005, Signal Process..

[6]  Bor-Sen Chen,et al.  Quantitative characterization of the transcriptional regulatory network in the yeast cell cycle , 2004, Bioinform..

[7]  Pll Siinksen,et al.  Control , 1999 .

[8]  Leo P. Kadanoff,et al.  Numerical and Theoretical Studies of Noise Effects in the Kauffman Model , 2002 .

[9]  P Ao,et al.  LETTER TO THE EDITOR: Potential in stochastic differential equations: novel construction , 2004 .

[10]  Q. Ouyang,et al.  The yeast cell-cycle network is robustly designed. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[11]  C. Rao,et al.  Control, exploitation and tolerance of intracellular noise , 2002, Nature.

[12]  Katherine C. Chen,et al.  Quantitative characterization of a mitotic cyclin threshold regulating exit from mitosis. , 2005, Molecular biology of the cell.

[13]  Andrew W. Murray,et al.  The Ups and Downs of Modeling the Cell Cycle , 2004, Current Biology.

[14]  Kai Lai Chung,et al.  Markov Chains with Stationary Transition Probabilities , 1961 .

[15]  L. Hood,et al.  Calculating biological behaviors of epigenetic states in the phage λ life cycle , 2004, Functional & Integrative Genomics.

[16]  Katherine C. Chen,et al.  Integrative analysis of cell cycle control in budding yeast. , 2004, Molecular biology of the cell.

[17]  Katherine C. Chen,et al.  Kinetic analysis of a molecular model of the budding yeast cell cycle. , 2000, Molecular biology of the cell.

[18]  Mike Tyers,et al.  Cell cycle goes global. , 2004, Current opinion in cell biology.

[19]  Feng,et al.  Role of noises in neural networks. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[20]  F. Cross,et al.  Testing a mathematical model of the yeast cell cycle. , 2002, Molecular biology of the cell.