Conzelmann Holger, Gilles Ernst-Dieter
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
Methods Mol Biol. 2008;484:559-78. doi: 10.1007/978-1-59745-398-1_33.
Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.
生物过程的数学模型在生物学中变得越来越重要。目的是全面理解细胞通讯、细胞分裂、调节、稳态或适应等过程是如何运作的，它们是如何被调节的，以及它们如何对扰动做出反应。这些过程大多极其复杂，因此需要生成数学模型来解决这些问题。在本章中，我们介绍动态建模的基本原理，并强调生物学中动态建模的问题和机遇。主要重点将是信号转导途径的建模，这需要应用一种特殊的建模方法。一个常见的模式，尤其是在真核信号系统中，是多蛋白信号复合物的形成。即使对于少量相互作用的蛋白质，可区分的分子种类数量也可能极高。这种组合复杂性是由于信号转导中涉及的许多受体和支架蛋白具有大量不同的结合结构域。然而，使用一种新的面向结构域的建模方法可以克服这些问题，该方法使处理复杂和分支的信号通路成为可能。
