Janes Kevin A, Lauffenburger Douglas A
Biological Engineering Division and Cell Decision Processes Center, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Curr Opin Chem Biol. 2006 Feb;10(1):73-80. doi: 10.1016/j.cbpa.2005.12.016. Epub 2006 Jan 6.
Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions about the measurement, definition and function of proteomic networks. Here, we place these biological questions at the forefront in reviewing the computational strategies that are available to analyze proteomic networks. Recent examples illustrate how models can extract more information from proteomic data, test possible interactions between network proteins and link networks to cellular behavior. No single model can achieve all these goals, however, which is why it is critical to prioritize biological questions before specifying a particular modeling approach.
计算建模作为一种整合和检验我们对蛋白质及网络所了解知识的手段很有用。模型有助于解决有关蛋白质组网络的测量、定义和功能的关键问题。在此，我们在回顾可用于分析蛋白质组网络的计算策略时，将这些生物学问题置于首位。近期的实例说明了模型如何能够从蛋白质组数据中提取更多信息、测试网络蛋白质之间可能的相互作用以及将网络与细胞行为联系起来。然而，没有单一的模型能够实现所有这些目标，这就是为什么在指定特定建模方法之前对生物学问题进行优先级排序至关重要的原因。
