Okabe Yurie, Yagi Yuu, Sasai Masaki
Department of Computational Science and Engineering, Nagoya University, Nagoya 464-8603, Japan.
J Chem Phys. 2007 Sep 14;127(10):105107. doi: 10.1063/1.2768353.
A dynamical mean-field theory is developed to analyze stochastic single-cell dynamics of gene expression. By explicitly taking account of nonequilibrium and nonadiabatic features of the DNA state fluctuation, two-time correlation functions and response functions of single-cell dynamics are derived. The method is applied to a self-regulating gene to predict a rich variety of dynamical phenomena such as an anomalous increase of relaxation time and oscillatory decay of correlations. The effective "temperature" defined as the ratio of the correlation to the response in the protein number is small when the DNA state change is frequent, while it grows large when the DNA state change is infrequent, indicating the strong enhancement of noise in the latter case.
发展了一种动态平均场理论来分析基因表达的随机单细胞动力学。通过明确考虑DNA状态波动的非平衡和非绝热特征,推导了单细胞动力学的双时关联函数和响应函数。该方法应用于一个自调节基因,以预测丰富多样的动力学现象,如弛豫时间的异常增加和关联的振荡衰减。当DNA状态变化频繁时,定义为蛋白质数量中关联与响应之比的有效“温度”较小,而当DNA状态变化不频繁时,它会变大,这表明在后一种情况下噪声会强烈增强。