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Foundations of static and dynamic absolute concentration robustness

机译:静态和动态绝对浓度鲁棒性的基础

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摘要

Absolute Concentration Robustness (ACR) was introduced by Shinar and Feinberg (Science 327:1389-1391, 2010) as robustness of equilibrium species concentration in a mass action dynamical system. Their aim was to devise a mathematical condition that will ensure robustness in the function of the biological system being modeled. The robustness of function rests on what we refer to as empirical robustness-the concentration of a species remains unvarying, when measured in the long run, across arbitrary initial conditions. Even simple examples show that the ACR notion introduced in Shinar and Feinberg (Science 327:1389-1391, 2010) (here referred to as static ACR) is neither necessary nor sufficient for empirical robustness. To make a stronger connection with empirical robustness, we define dynamic ACR, a property related to long-term, global dynamics, rather than only to equilibrium behavior. We discuss general dynamical systems with dynamic ACR properties as well as parametrized families of dynamical systems related to reaction networks. We find necessary and sufficient conditions for dynamic ACR in complex balanced reaction networks, a class of networks that is central to the theory of reaction networks.
机译:Shinar 和 Feinberg (Science 327:1389-1391, 2010) 引入了绝对浓度鲁棒性 (ACR) 作为质量作用动力系统中平衡物质浓度的鲁棒性。他们的目标是设计一个数学条件,以确保被建模的生物系统功能的稳健性。功能的鲁棒性取决于我们所说的经验鲁棒性——从长远来看,在任意初始条件下,物种的浓度保持不变。即使是简单的例子也表明,Shinar 和 Feinberg (Science 327:1389-1391, 2010) 中引入的 ACR 概念(这里称为静态 ACR)对于经验稳健性既不必要也不充分。为了与经验鲁棒性建立更紧密的联系,我们定义了动态ACR,这是一种与长期全局动力学相关的属性,而不仅仅是与平衡行为有关。我们讨论了具有动态ACR属性的一般动力系统以及与反应网络相关的参数化动力系统族。我们在复杂的平衡反应网络中发现了动态ACR的必要和充分条件,这是一类网络,是反应网络理论的核心。

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