Porter Joshua R, Batchelor Eric
Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Building 10, Room B1B42, 10 Center Dr., MSC 1500, Bethesda, MD, 20892, USA.
Methods Mol Biol. 2015;1244:259-76. doi: 10.1007/978-1-4939-1878-2_12.
This chapter describes approaches for using computational modeling of synthetic biology perturbations to analyze endogenous biological circuits, with a particular focus on signaling and metabolic pathways. We describe a bottom-up approach in which ordinary differential equations are constructed to model the core interactions of a pathway of interest. We then discuss methods for modeling synthetic perturbations that can be used to investigate properties of the natural circuit. Keeping in mind the importance of the interplay between modeling and experimentation, we next describe experimental methods for constructing synthetic perturbations to test the computational predictions. Finally, we present a case study of the p53 tumor-suppressor pathway, illustrating the process of modeling the core network, designing informative synthetic perturbations in silico, and testing the predictions in vivo.
本章描述了利用合成生物学扰动的计算模型来分析内源性生物回路的方法，特别关注信号传导和代谢途径。我们描述了一种自下而上的方法，即构建常微分方程来模拟感兴趣途径的核心相互作用。然后，我们讨论了用于模拟合成扰动的方法，这些方法可用于研究天然回路的特性。考虑到建模与实验之间相互作用的重要性，接下来我们描述构建合成扰动以测试计算预测的实验方法。最后，我们给出了p53肿瘤抑制途径的案例研究，阐述了核心网络建模、在计算机上设计信息丰富的合成扰动以及在体内测试预测的过程。
