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使用CoLoMoTo软件套件进行可重复的布尔模型分析与模拟:教程

Reproducible Boolean model analyses and simulations with the CoLoMoTo software suite: a tutorial.

作者信息

Noël Vincent, Naldi Aurélien, Calzone Laurence, Paulevé Loic, Thieffry Denis

机构信息

Institut Curie, Université PSL, 75005 Paris, France.

INSERM U1331, 75005 Paris, France.

出版信息

Interface Focus. 2025 Aug 22;15(3):20250002. doi: 10.1098/rsfs.2025.0002.

DOI:10.1098/rsfs.2025.0002
PMID:40862235
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12371346/
Abstract

This tutorial provides stepwise instructions to install over 20 tools, written in multiple languages. Their integration in the software suite makes them accessible with a single popular language (), thereby enabling reproducible and sophisticated dynamical analyses of logical models of complex cellular networks. The tutorial specifically focuses on the analysis of a previously published model of the regulatory network controlling mammalian cell proliferation. It includes chunks of code to reproduce several of the results and figures published in the original article, and further extends these results with the help of selected tools included in the suite. The tutorial covers the visualization of the network with the tool , an attractor analysis with , the computation of synchronous attractors with , the extraction of modules from the full model, stochastic simulations of the wild-type model and of selected perturbations with and finally the delineation of compressed probabilistic state transition graphs. The integration of all these analyses in an executable greatly eases their reproducibility, as well as the inclusion of further extensions. The notebook provided along with this tutorial further constitutes a template, which can be enriched with other tools, to develop comprehensive dynamical analyses of various biological network models.

摘要

本教程提供了逐步安装20多种工具的说明,这些工具用多种语言编写。它们在软件套件中的集成使得可以使用一种流行的语言来访问这些工具,从而能够对复杂细胞网络的逻辑模型进行可重复且复杂的动态分析。本教程特别关注对先前发表的控制哺乳动物细胞增殖的调控网络模型的分析。它包含代码片段,用于重现原始文章中发表的几个结果和图表,并借助套件中包含的选定工具进一步扩展这些结果。本教程涵盖了使用工具对网络进行可视化、使用进行吸引子分析、使用计算同步吸引子、从完整模型中提取模块、使用对野生型模型和选定扰动进行随机模拟,以及最后描绘压缩概率状态转移图。将所有这些分析集成到一个可执行文件中极大地简化了它们的可重复性以及进一步扩展的纳入。随本教程提供的笔记本进一步构成了一个模板,可以用其他工具进行扩充,以开发对各种生物网络模型的全面动态分析。

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