Rule-based modeling of signal transduction: a primer.
Rule-based modeling of signal transduction: a primer.
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DOI：
10.1007/978-1-61779-833-7_9
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发表时间：
2012
影响因子：
--
通讯作者：
John A. P. Sekar;J. Faeder
中科院分区：
文献类型：
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作者：
John A. P. Sekar;J. Faeder
生物细胞利用基因、蛋白质和其他生物分子的互连网络来实现其生理功能。生物信号网络中的大多数相互作用，例如双分子缔合或共价修饰，可以使用基本反应动力学以物理真实的方式进行建模。然而，这种反应网络的规模和组合复杂性阻碍了这种机械方法，导致许多人得出结论认为它还为时过早，并采用替代的统计或现象学方法。最近开发的基于规则的建模语言，例如 BioNetGen (BNG) 和 Kappa，使得大型反应网络的精确和简洁编码成为可能。再加上模拟方法的互补进步，这些语言绕过了组合障碍，并允许比以前更大的规模进行机械建模。这些语言对于生物学家来说也很直观，对于新手建模者来说也很容易理解。在本章中，我们提供了一个关于使用 BNG 语言和相关软件工具对信号转导网络进行建模的独立教程。我们回顾了该语言的基本语法，并展示了如何使用反应规则来表达生化知识，该规则可用于以简洁和模块化的方式捕获广泛的生化和生物物理现象。检查配体激活受体二聚化模型，并详细处理建模过程的每个步骤。其中包括讨论建模理论、隐式和显式模型假设以及模型参数化的部分，特别关注保留生物物理现实性和避免常见陷阱。我们还讨论了使用 BioNetGen 的区室扩展进行区室建模的更高级案例。此外，我们还提供了一套全面的示例反应规则，涵盖信号转导的各个方面，从膜信号传导到基因调控。读者可以修改这些反应规则来模拟自己感兴趣的系统。
Biological cells accomplish their physiological functions using interconnected networks of genes, proteins, and other biomolecules. Most interactions in biological signaling networks, such as bimolecular association or covalent modification, can be modeled in a physically realistic manner using elementary reaction kinetics. However, the size and combinatorial complexity of such reaction networks have hindered such a mechanistic approach, leading many to conclude that it is premature and to adopt alternative statistical or phenomenological approaches. The recent development of rule-based modeling languages, such as BioNetGen (BNG) and Kappa, enables the precise and succinct encoding of large reaction networks. Coupled with complementary advances in simulation methods, these languages circumvent the combinatorial barrier and allow mechanistic modeling on a much larger scale than previously possible. These languages are also intuitive to the biologist and accessible to the novice modeler. In this chapter, we provide a self-contained tutorial on modeling signal transduction networks using the BNG Language and related software tools. We review the basic syntax of the language and show how biochemical knowledge can be articulated using reaction rules, which can be used to capture a broad range of biochemical and biophysical phenomena in a concise and modular way. A model of ligand-activated receptor dimerization is examined, with a detailed treatment of each step of the modeling process. Sections discussing modeling theory, implicit and explicit model assumptions, and model parameterization are included, with special focus on retaining biophysical realism and avoiding common pitfalls. We also discuss the more advanced case of compartmental modeling using the compartmental extension to BioNetGen. In addition, we provide a comprehensive set of example reaction rules that cover the various aspects of signal transduction, from signaling at the membrane to gene regulation. The reader can modify these reaction rules to model their own systems of interest.