随机酵母细胞周期网络的同步动力学和非平衡定态
Synchronized Dynamics and Nonequilibrium Steady States in a Stochastic Yeast Cell-Cycle Network
摘要：
应用马尔可夫链的数学循环理论，我们研究了酵母细胞周期调节的离散网络模型的同步随机动力学，其中随机性一直保持，而不是被平均。通过比较随机模型的网络动力学与相应的确定性网络动力学，我们证明了随机模型中的同步动力学可以用一个主导环来刻画，这是确定性系统中确定性极限环的自然推广.此外，在功率谱中的主峰的周期，这是在常用的同步动力学的特征，完美地对应于主循环中的状态的数量与占主导地位的循环。在主导的主循环和其余循环之间，环流幅度的这种大分离引起了随机同步现象。
英文摘要：
Applying the mathematical circulation theory of Markov chains, we investigate the synchronized stochastic dynamics of a discrete network model of yeast cell-cycle regulation where stochasticity has been kept rather than being averaged out. By comparing the network dynamics of the stochastic model with its corresponding deterministic network counterpart, we show that the synchronized dynamics can be soundly characterized by a dominant circulation in the stochastic model, which is the natural generalization of the deterministic limit cycle in the deterministic system. Moreover, the period of the main peak in the power spectrum, which is in common use to characterize the synchronized dynamics, perfectly corresponds to the number of states in the main cycle with dominant circulation. Such a large separation in the magnitude of the circulations, between a dominant, main cycle and the rest, gives rise to the stochastic synchronization phenomenon.
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