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Random Network Based Dynamic Analysis for Biochemical Reaction System

机译:基于随机网络的生化反应系统动力学分析

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Complex networks are studied across many fields of science, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in gene regulation network, but so far the resulting networks have only been analyzed statically. In this paper, the biochemical reaction network (BRN) model is proposed based on the random graph theory and the dynamics of the network is analyzed on the molecular-scale. Given the initial state and the evolution rules of the biochemical network, we demonstrated how the biochemical reaction network achieving homeostasis via simulation. We also studied the dynamics of the biochemical reaction network in perspective of average degree and edges. The network features of biochemical reaction system were analyzed in both its initial state and equilibrium state. Further more, we compared the network features of the biochemical reaction network with those of the original random graph.
机译:对复杂网络的研究涉及许多科学领域,提供了一种统一的语言来描述从社交互动到电网的各种系统。它最近已用于基因调控网络中,但到目前为止,所得网络仅是静态分析的。本文基于随机图论提出了生化反应网络(BRN)模型,并在分子尺度上分析了网络的动力学。给定生化网络的初始状态和演化规则,我们演示了生化反应网络如何通过模拟实现稳态。我们还从平均程度和边缘角度研究了生化反应网络的动力学。分析了生化反应系统的初始状态和平衡状态的网络特征。此外,我们将生化反应网络的网络特征与原始随机图的网络特征进行了比较。

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