Université Côte d'Azur, Inria, INRAE, CNRS, Sorbonne Université, Biocore Team, Sophia Antipolis, France.
Université Grenoble Alpes, Inria, Grenoble, Montbonnot, Saint Ismier Cedex, France.
Methods Mol Biol. 2021;2229:1-40. doi: 10.1007/978-1-0716-1032-9_1.
Qualitative modeling approaches are promising and still underexploited tools for the analysis and design of synthetic circuits. They can make predictions of circuit behavior in the absence of precise, quantitative information. Moreover, they provide direct insight into the relation between the feedback structure and the dynamical properties of a network. We review qualitative modeling approaches by focusing on two specific formalisms, Boolean networks and piecewise-linear differential equations, and illustrate their application by means of three well-known synthetic circuits. We describe various methods for the analysis of state transition graphs, discrete representations of the network dynamics that are generated in both modeling frameworks. We also briefly present the problem of controlling synthetic circuits, an emerging topic that could profit from the capacity of qualitative modeling approaches to rapidly scan a space of design alternatives.
定性建模方法是分析和设计合成电路的有前途且尚未充分利用的工具。它们可以在缺乏精确、定量信息的情况下对电路行为进行预测。此外，它们还可以直接了解反馈结构与网络动态特性之间的关系。我们通过关注两种特定的形式主义，布尔网络和分段线性微分方程，来回顾定性建模方法，并通过三个著名的合成电路来说明它们的应用。我们描述了分析状态转换图的各种方法，这是在这两个建模框架中生成的网络动态的离散表示。我们还简要介绍了合成电路控制的问题，这是一个新兴的话题，可以从定性建模方法快速扫描设计方案空间的能力中受益。
