Foundations of static and dynamic absolute concentration robustness
Foundations of static and dynamic absolute concentration robustness
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静态和动态绝对浓度鲁棒性的基础
DOI：
10.1007/s00285-022-01823-2
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发表时间：
2021
影响因子：
1.9
通讯作者：
G. Craciun
中科院分区：
文献类型：
--
作者：
Badal Joshi;G. Craciun
绝对浓度稳健性(ACR)是Shina和Feinberg(Science 327：1389-1391,2010)提出的质量作用动力系统中平衡物种浓度的稳健性。他们的目的是设计一种数学条件，以确保被建模的生物系统的功能具有健壮性。函数的稳健性取决于我们所说的经验稳健性--当长期衡量一个物种在任意初始条件下的浓度时，它保持不变。即使是简单的例子也表明，Shina和Feinberg(Science 327：1389-1391,2010)中引入的ACR概念(这里称为静态ACR)既不是经验稳健性的必要条件，也不是充分条件。为了与经验稳健性建立更强的联系，我们定义了动态ACR，这是一个与长期、全球动态有关的属性，而不仅仅是与均衡行为有关。我们讨论了具有动态ACR性质的一般动力系统以及与反应网络有关的动力系统的参数化族。我们在复杂平衡反应网络中找到了动态ACR的充要条件，这类网络是反应网络理论的核心。
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.
用于静态和动态绝对浓度稳健性的反应网络基序
影响因子：
2.1
作者：
Joshi, Badal;Craciun, Gheorghe
通讯作者：
Craciun, Gheorghe
影响因子：
3.9
作者：
Kim, Jinsu;Enciso, German
通讯作者：
Enciso, German