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具有合成与降解的拉普拉斯动力学

Laplacian Dynamics with Synthesis and Degradation.

作者信息

Mirzaev Inom, Bortz David M

机构信息

Applied Mathematics, University of Colorado, Boulder, CO, 80309-0526, USA,

出版信息

Bull Math Biol. 2015 Jun;77(6):1013-45. doi: 10.1007/s11538-015-0075-7. Epub 2015 Mar 21.

Abstract

Analyzing qualitative behaviors of biochemical reactions using its associated network structure has proven useful in diverse branches of biology. As an extension of our previous work, we introduce a graph-based framework to calculate steady state solutions of biochemical reaction networks with synthesis and degradation. Our approach is based on a labeled directed graph G and the associated system of linear non-homogeneous differential equations with first-order degradation and zeroth-order synthesis. We also present a theorem which provides necessary and sufficient conditions for the dynamics to engender a unique stable steady state. Although the dynamics are linear, one can apply this framework to nonlinear systems by encoding nonlinearity into the edge labels. We answer an open question from our previous work concerning the non-positiveness of the elements in the inverse of a perturbed Laplacian matrix. Moreover, we provide a graph theoretical framework for the computation of the inverse of such a matrix. This also completes our previous framework and makes it purely graph theoretical. Lastly, we demonstrate the utility of this framework by applying it to a mathematical model of insulin secretion through ion channels in pancreatic β-cells.

摘要

利用生化反应的相关网络结构分析其定性行为已被证明在生物学的各个分支中都很有用。作为我们先前工作的扩展,我们引入了一个基于图的框架来计算具有合成和降解的生化反应网络的稳态解。我们的方法基于一个带标签的有向图G以及与之相关的具有一阶降解和零阶合成的线性非齐次微分方程组。我们还提出了一个定理,该定理为动力学产生唯一稳定稳态提供了充分必要条件。尽管动力学是线性的,但通过将非线性编码到边标签中,可以将此框架应用于非线性系统。我们回答了我们先前工作中关于扰动拉普拉斯矩阵逆矩阵元素非正性的一个开放性问题。此外,我们提供了一个用于计算此类矩阵逆的图论框架。这也完善了我们先前的框架并使其完全基于图论。最后,我们通过将其应用于胰腺β细胞中通过离子通道的胰岛素分泌数学模型来证明该框架的实用性。

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Laplacian Dynamics with Synthesis and Degradation.具有合成与降解的拉普拉斯动力学
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本文引用的文献

5
Laplacian dynamics on general graphs.图上的拉普拉斯动力系统。
Bull Math Biol. 2013 Nov;75(11):2118-49. doi: 10.1007/s11538-013-9884-8. Epub 2013 Sep 10.
9
Oscillations in biochemical reaction networks arising from pairs of subnetworks.生化反应网络中由两个子网产生的波动。
Bull Math Biol. 2011 Oct;73(10):2277-304. doi: 10.1007/s11538-010-9620-6. Epub 2011 Jan 22.

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