Automating Mathematical Modeling of Biochemical Reaction Networks
Automating Mathematical Modeling of Biochemical Reaction Networks
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DOI：
10.1007/978-1-4419-5797-9_7
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发表时间：
2010-01-01
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影响因子：
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通讯作者：
Zell, Andreas
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文献类型：
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作者：
Draeger, Andreas;Schroeder, Adrian;Zell, Andreas
在本章中，我们将介绍一个五步建模流程，最终导致生化反应系统的数学描述。我们将讨论如何自动化每个步骤以及如何将这些步骤组合在一起。首先，我们创建一个拓扑结构的相互转换过程和相互影响的反应物种。系统生物学标记语言（SBML）以计算机可读的形式编码模型，并允许我们将语义信息添加到模型的每个组件中。其次，从这样一个注释的网络，被称为SBMLsqueezer的程序生成动力学方程的上下文敏感的方式。然后，可以将生成的模型与现有模型相结合。第三，我们估计每个创建的速率律中所有新引入的参数的值。这个过程需要一个时间序列的定量测量的活性物质在这个系统是可用的，因为我们校准的参数，目的是该模型将适合这些实验数据。第四，实验验证所产生的模型是可取的。第五，自动生成模型报告，以记录模型及其所有组件。为了更好地理解，我们将开始介绍当前系统生物学的标准化尝试和通用速率方程的一般化方法，然后讨论计算机辅助建模，参数估计和自动报告生成。在本章结束时，我们将讨论对我们的建模管道可能进行的进一步改进。
In this chapter we introduce a five-step modeling pipeline that ultimately leads to a mathematical description of a biochemical reaction system. We discuss how to automate each individual step and how to put these steps together. First, we create a topology of interconversion processes and mutual influences between reactive species. The Systems Biology Markup Language (SBML) encodes the model in a computer-readable form and allows us to add semantic information to each component of the model. Second, from such an annotated network, the procedure known as SBMLsqueezer generates kinetic equations in a context-sensitive manner. The resulting model can then be combined with already existing models. Third, we estimate the values of all newly introduced parameters in each created rate law. This procedure requires that a time series of quantitative measurements of the reactive species within this system be available, because we calibrate the parameters with the aim that the model will fit these experimental data. Fourth, an experimental validation of the resulting model is advisable. Fifth, a model report is generated automatically to document the model with all of its components. For a better understanding, we will begin with an introduction to current standardization attempts in systems biology and generalized approaches for common rate equations before discussing computer-aided modeling, parameter estimation, and automatic report generation. We complete this chapter with a discussion of possible further improvements to our modeling pipeline.