p53通路负反馈环的布尔网络方法：同步动力学和随机极限环
Boolean Network Approach to Negative Feedback Loops of the p53 Pathways: Synchronized Dynamics and Stochastic Limit Cycles
摘要：
建立了p53通路负反馈环动力学的确定性和随机布尔网络模型。结果表明，p53通路中负反馈的主要功能是保持p53在一个较低的稳态水平，并且负反馈回路中的每一个蛋白质状态序列在受到外界信号（如DNA损伤）的扰动后，都被全局吸引到p53动力学的一个闭合循环中。我们的理论和数值研究表明，生物定态和扰动后的生物振荡在很宽的噪声水平范围内都是稳定的。应用马尔可夫链的数学循环理论，研究了它们的随机同步动力学，通过比较随机模型的网络动力学和相应的确定性网络动力学，发现随机模型中的一个主导循环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。主导主循环和其余循环之间循环幅度的如此大的分离会引起随机同步现象。
英文摘要：
Deterministic and stochastic Boolean network models are build for the dynamics of negative feedback loops of the p53 pathways. It is shown that the main function of the negative feedback in the p53 pathways is to keep p53 at a low steady state level, and each sequence of protein states in the negative feedback loops, is globally attracted to a closed cycle of the p53 dynamics after being perturbed by outside signal (e.g. DNA damage). Our theoretical and numerical studies show that both the biological stationary state and the biological oscillation after being perturbed are stable for a wide range of noise level. Applying the mathematical circulation theory of Markov chains, we investigate their stochastic synchronized dynamics and by comparing the network dynamics of the stochastic model with its corresponding deterministic network counterpart, a dominant circulation in the stochastic model 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
