绝对浓度稳健性代数与几何

Luis David García Puente, Elizabeth Gross, Heather A Harrington, Matthew Johnston, Nicolette Meshkat, Mercedes Pérez Millán, Anne Shiu
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引用次数: 0

摘要

受生物系统如何在变化环境中保持平衡这一问题的启发,Shinar 和 Feinberg 于 2010 年提出了绝对浓度稳健性(ACR)的概念。如果一个生化系统中某些物种的稳态值不依赖于初始条件,那么该物种就表现出绝对浓度稳健性。因此,即使环境发生变化,具有 ACR 的系统也能保持某一物种的恒定水平。尽管近年来人们对 ACR 产生了浓厚的兴趣,但以下基本问题仍然悬而未决:我们如何才能快速确定一个给定的生化系统是否具有 ACR?尽管已经提出了解决这一问题的各种方法,但我们发现这些方法都是不完整的。因此,我们提出了利用计算代数来判定 ACR 的新方法。我们将在几个生化信号网络中说明我们的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Absolute concentration robustness: Algebra and geometry
Motivated by the question of how biological systems maintain homeostasis in changing environments, Shinar and Feinberg introduced in 2010 the concept of absolute concentration robustness (ACR). A biochemical system exhibits ACR in some species if the steady-state value of that species does not depend on initial conditions. Thus, a system with ACR can maintain a constant level of one species even as the environment changes. Despite a great deal of interest in ACR in recent years, the following basic question remains open: How can we determine quickly whether a given biochemical system has ACR? Although various approaches to this problem have been proposed, we show that they are incomplete. Accordingly, we present new methods for deciding ACR, which harness computational algebra. We illustrate our results on several biochemical signaling networks.
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