标题： 精确度和灵敏度在细致平衡反应网络中 显示英文标题

标题： Precision and Sensitivity in Detailed-Balance Reaction Networks

摘要： 我们研究了化学反应网络的两个特定质量度量标准，即精度和灵敏度。这两个度量标准出现在感官适应的研究中，在这种情况下，反应网络被视为一个输入-输出系统。给定输入的一个阶跃变化，灵敏度是对响应幅度的度量，而精度是对系统在长时间后返回到其原始输出的程度的度量。高质量的适应需要两者都有高值。我们关注的是没有耗散的反应网络，我们将这些网络解读为细致平衡的质量作用网络。我们通过结合拟阵理论和微分方程理论的思想，给出了灵敏度和精度最优值的各种上下限，这些界限以计量学为特征。除此之外，我们还表明，这类非耗散系统包含了灵敏度和精度都能达到任意高值的网络。然而，这种良好的性能是有代价的，因为某些浓度比需要很大，网络必须是大规模的，或者网络应该表现出明显不同的时间尺度。 显示英文摘要

摘要： We study two specific measures of quality of chemical reaction networks, Precision and Sensitivity. The two measures arise in the study of sensory adaptation, in which the reaction network is viewed as an input-output system. Given a step change in input, Sensitivity is a measure of the magnitude of the response, while Precision is a measure of the degree to which the system returns to its original output for large time. High values of both are necessary for high-quality adaptation. We focus on reaction networks without dissipation, which we interpret as detailed-balance, mass-action networks. We give various upper and lower bounds on the optimal values of Sensitivity and Precision, characterized in terms of the stoichiometry, by using a combination of ideas from matroid theory and differential-equation theory. Among other results, we show that this class of non-dissipative systems contains networks with arbitrarily high values of both Sensitivity and Precision. This good performance does come at a cost, however, since certain ratios of concentrations need to be large, the network has to be extensive, or the network should show strongly different time scales.