On the connectedness of multistationarity regions of small reaction networks

IF 0.6 4区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS Journal of Symbolic Computation Pub Date : 2024-03-15 DOI:10.1016/j.jsc.2024.102323
Allison McClure, Anne Shiu
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Abstract

A multistationarity region is the part of a reaction network's parameter space that gives rise to multiple steady states. Mathematically, this region consists of the positive parameters for which a parametrized family of polynomial equations admits two or more positive roots. Much recent work has focused on analyzing multistationarity regions of biologically significant reaction networks and determining whether such regions are connected; indeed, a better understanding of the topology and geometry of such regions may help elucidate how robust multistationarity is to perturbations. Here we focus on the multistationarity regions of small networks, those with few species and few reactions. For two families of such networks – those with one species and up to three reactions, and those with two species and up to two reactions – we prove that the resulting multistationarity regions are connected. We also give an example of a network with one species and six reactions for which the multistationarity region is disconnected. Our proofs rely on the formula for the discriminant of a trinomial, a classification of small multistationary networks, and a recent result of Feliu and Telek that partially generalizes Descartes' rule of signs.

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论小型反应网络多稳态区域的连通性
多稳态区域是指反应网络参数空间中产生多个稳态的部分。在数学上,该区域由正参数组成,参数化的多项式方程组在该区域有两个或两个以上的正根。最近的许多工作都集中在分析具有生物学意义的反应网络的多稳态区域,并确定这些区域是否相互连接;事实上,更好地了解这些区域的拓扑结构和几何形状可能有助于阐明多稳态对扰动的稳健性。在此,我们将重点研究小型网络的多稳态区域,即那些只有少数物种和少数反应的网络。对于此类网络的两个家族--只有一个物种和最多三个反应的网络,以及只有两个物种和最多两个反应的网络--我们证明了由此产生的多稳态区域是相连的。我们还举例说明了一个有一个物种和六个反应的网络,其多稳态区域是断开的。我们的证明依赖于三项式的判别式、小型多稳态网络的分类,以及 Feliu 和 Telek 部分推广笛卡尔符号规则的最新成果。
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来源期刊
Journal of Symbolic Computation
Journal of Symbolic Computation 工程技术-计算机:理论方法
CiteScore
2.10
自引率
14.30%
发文量
75
审稿时长
142 days
期刊介绍: An international journal, the Journal of Symbolic Computation, founded by Bruno Buchberger in 1985, is directed to mathematicians and computer scientists who have a particular interest in symbolic computation. The journal provides a forum for research in the algorithmic treatment of all types of symbolic objects: objects in formal languages (terms, formulas, programs); algebraic objects (elements in basic number domains, polynomials, residue classes, etc.); and geometrical objects. It is the explicit goal of the journal to promote the integration of symbolic computation by establishing one common avenue of communication for researchers working in the different subareas. It is also important that the algorithmic achievements of these areas should be made available to the human problem-solver in integrated software systems for symbolic computation. To help this integration, the journal publishes invited tutorial surveys as well as Applications Letters and System Descriptions.
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