Virginia Bioinformatics Institute, Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
Bioinformatics. 2010 Jul 1;26(13):1637-43. doi: 10.1093/bioinformatics/btq240. Epub 2010 May 6.
An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation.
This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis.
Supplementary data are available at Bioinformatics online.
系统生物学中发表的离散数学模型越来越多，从布尔网络模型到逻辑模型和 Petri 网。它们被用于模拟各种生化网络，如代谢网络、基因调控网络和信号转导网络。越来越多的证据表明，这些模型可以捕捉生物网络的关键动态特征，并成功地用于假设生成。
本文提供了一个统一的框架，可以帮助对布尔网络模型、逻辑模型和 Petri 网进行数学分析。它们可以表示为多项式动力系统，这允许使用来自计算机代数的各种数学工具对其进行分析。本文还提出了将其转换为多项式动力系统的算法。给出了多项式代数如何用于模型分析的示例。
补充数据可在“Bioinformatics”在线获取。
