MacLean Adam L, Harrington Heather A, Stumpf Michael P H, Byrne Helen M
Mathematical Institute, University of Oxford, Oxford, UK.
Department of Life Sciences, Imperial College London, London, UK.
Methods Mol Biol. 2016;1386:405-39. doi: 10.1007/978-1-4939-3283-2_18.
The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non-exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.
在过去十年中,描述系统医学现象的模型呈爆发式增长。此类模型对于研究信号通路(如Wnt通路)尤为有用。在本章中,我们将以Wnt通路为例,展示当前的数学和统计技术,这些技术使建模者能够深入了解基因调控(模型)并生成可检验的预测。我们介绍了一系列建模框架,但重点关注常微分方程(ODE)模型,因为它们仍然是系统生物学和医学中使用最广泛的方法,并且继续具有巨大潜力。我们介绍了分析单个模型的方法,包括应用标准动力系统方法,如无量纲化、稳态、渐近和敏感性分析,以及用于将模型与数据进行比较的最新统计和代数方法。我们介绍了参数估计和模型比较技术,重点是贝叶斯分析和通过代数几何的共面性。我们的目的是,这篇(非详尽的)综述可以作为系统医学中模型分析的一个有用起点。