Wang Jin, Zhang Kun, Wang Erkwang
State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China.
J Chem Phys. 2008 Oct 7;129(13):135101. doi: 10.1063/1.2985621.
We uncovered the underlying energy landscape of the mitogen-activated protein kinases signal transduction cellular network by exploring the statistical natures of the Brownian dynamical trajectories. We introduce a dimensionless quantity: The robustness ratio of energy gap versus local roughness to measure the global topography of the underlying landscape. A high robustness ratio implies funneled landscape. The landscape is quite robust against environmental fluctuations and variants of the intrinsic chemical reaction rates. As the environmental fluctuations or the variances of the inherent chemical reaction rates increase further more, the landscape becomes less robust and more flatter. We also show that more robust network has less dissipation costs. Our approach is quite general and can be applied to other cellular networks.
我们通过探索布朗动力学轨迹的统计特性，揭示了丝裂原活化蛋白激酶信号转导细胞网络的潜在能量景观。我们引入了一个无量纲量：能隙与局部粗糙度的稳健性比率，以测量潜在景观的全局地形。高稳健性比率意味着漏斗状景观。该景观对环境波动和内在化学反应速率的变化具有很强的稳健性。随着环境波动或内在化学反应速率的方差进一步增加，景观的稳健性降低且变得更加平坦。我们还表明，更稳健的网络具有更低的耗散成本。我们的方法非常通用，可应用于其他细胞网络。
