Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive capabilities. In this review, we present an overview of the relevant mathematical frameworks for kinetic formulation, construction and analysis. Starting with kinetic formalisms, we next review statistical methods for parameter inference, as well as recent computational frameworks applied to the construction and analysis of kinetic models. Finally, we discuss opportunities and limitations hindering the development of larger kinetic reconstructions.

动力学模型对于预测代谢网络的动态行为至关重要。由于难以拟合其参数，大型网络的力学动力学模型仍然不常见。最新的建模框架有望在保持预测能力的同时克服这一障碍的新方法。在这篇综述中，我们对动力学公式，构造和分析的相关数学框架进行了概述。从动力学形式主义开始，我们接下来回顾用于参数推断的统计方法，以及应用于动力学模型的构建和分析的最新计算框架。最后，我们讨论了阻碍大型动力学重建发展的机遇和局限性。