The yeast cell-cycle network is robustly designed.

The interactions between proteins, DNA, and RNA in living cells constitute molecular networks that govern various cellular functions. To investigate the global dynamical properties and stabilities of such networks, we studied the cell-cycle regulatory network of the budding yeast. With the use of a simple dynamical model, it was demonstrated that the cell-cycle network is extremely stable and robust for its function. The biological stationary state, the G1 state, is a global attractor of the dynamics. The biological pathway, the cell-cycle sequence of protein states, is a globally attracting trajectory of the dynamics. These properties are largely preserved with respect to small perturbations to the network. These results suggest that cellular regulatory networks are robustly designed for their functions.

[1]  N. Rashevsky.  Mathematical biophysics of cell division , 1943 .

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

[3]  R M May,et al.  Biological Populations with Nonoverlapping Generations: Stable Points, Stable Cycles, and Chaos , 1974, Science.

[4]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[5]  G. Parisi.  A simple model for the immune network. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[6]  AC Tose.  Cell , 1993, Cell.

[7]  V. Hu.  The Cell Cycle , 1994, GWUMC Department of Biochemistry Annual Spring Symposia.

[8]  J. Onuchic,et al.  Navigating the folding routes , 1995, Science.

[9]  N. Wingreen,et al.  Emergence of Preferred Structures in a Simple Model of Protein Folding , 1996, Science.

[10]  J. Onuchic,et al.  Theory of protein folding: the energy landscape perspective. , 1997, Annual review of physical chemistry.

[11]  K. Dill,et al.  From Levinthal to pathways to funnels , 1997, Nature Structural Biology.

[12]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[13]  U. Alon,et al.  Robustness in bacterial chemotaxis , 2022 .

[14]  S. Huang,et al.  Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks. , 2000, Experimental cell research.

[15]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

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

[17]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[18]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[19]  Kathy Chen,et al.  Network dynamics and cell physiology , 2001, Nature Reviews Molecular Cell Biology.

[20]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[21]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[22]  Peter G Wolynes,et al.  Stochastic gene expression as a many-body problem , 2003, Proceedings of the National Academy of Sciences of the United States of America.

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

[24]  M. Aldana.  Boolean dynamics of networks with scale-free topology , 2003 .

[25]  H. Othmer,et al.  The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster. , 2003, Journal of theoretical biology.