Stochastic Model of Yeast Cell Cycle Network

Abstract

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 $\beta$. 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 ${\beta }_c$, below which the dynamics is 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.

14 pages, 4 figures

References in corpus (4)

• The Yeast Cell-Cycle Network Is Robustly Designed
• Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. II: construction of SDS with nonlinear force and multiplicative noise
• Calculating Biological Behaviors of Epigenetic States in Phage lambda Life Cycle
• Numerical and Theoretical Studies of Noise Effects in the Kauffman Model

Cited by in corpus (5)

• Stable stochastic dynamics in yeast cell cycle
• Generic Properties of Random Gene Regulatory Networks
• Funneled Potential and Flux Landscapes Dictate the Stabilities of both the States and the Flow: Fission Yeast Cell Cycle
• Synchronization in discrete-time, discrete-state Random Dynamical Systems
• Coherent regulation in yeast cell cycle network