Parameter estimation using Simulated Annealing for S-system models of biochemical networks
Parameter estimation using Simulated Annealing for S-system models of biochemical networks
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DOI：
10.1093/bioinformatics/btl522
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发表时间：
2007-02-15
期刊：
影响因子：
5.8
通讯作者：
Mendoza, Eduardo
中科院分区：
文献类型：
--
作者：
Gonzalez, Orland R.;Kueper, Christoph;Mendoza, Eduardo
动机：高通量技术现在允许以前所未有的速度获取生物数据，例如全面的生化时间过程。这些时间剖面携带着有关生物化学网络的拓扑和动力学信息。检索这些信息需要系统地应用实验和计算方法。结果：s系统是基于幂律形式的非线性数学近似模型。它们为展示复杂动态的综合生物系统的模拟提供了一个总体框架，例如遗传电路、信号转导和代谢网络。我们描述了如何将启发式优化技术模拟退火（SA）有效地用于从时间过程生化数据估计s -系统的参数。我们使用三个人工网络来模拟不同的网络拓扑和行为来演示我们的方法。最后，我们通过在大肠杆菌中创建cadBA系统的工作模型，将其应用于实际的生化网络。可用性：用c++编写的源代码可在http://www.engg.upd.edu.ph/similar上获得naval/bioinformcode.html。所有必要的程序，包括所需的编译器，都在与源代码一起存档的文档中描述。联系方式：gonzalez@bio.ifi.lmu.deSupplementary信息：补充材料可在Bioinformatics在线获取。
Motivation: High-throughput technologies now allow the acquisition of biological data, such as comprehensive biochemical time-courses at unprecedented rates. These temporal profiles carry topological and kinetic information regarding the biochemical network from which they were drawn. Retrieving this information will require systematic application of both experimental and computational methods.Results: S-systems are non-linear mathematical approximative models based on the power-law formalism. They provide a general framework for the simulation of integrated biological systems exhibiting complex dynamics, such as genetic circuits, signal transduction and metabolic networks. We describe how the heuristic optimization technique simulated annealing (SA) can be effectively used for estimating the parameters of S-systems from time-course biochemical data. We demonstrate our methods using three artificial networks designed to simulate different network topologies and behavior. We then end with an application to a real biochemical network by creating a working model for the cadBA system in Escherichia coli.Availability: The source code written in C++ is available at http://www.engg.upd.edu.ph/similar to naval/bioinformcode.html. All the necessary programs including the required compiler are described in a document archived with the source code.Contact: gonzalez@bio.ifi.lmu.deSupplementary information: Supplementary material is available at Bioinformatics online.