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

This tutorial provides stepwise instructions to install over 20 tools, written in multiple languages. Their integration in the <i>CoLoMoTo</i> software suite makes them accessible with a single popular language (<i>Python</i>), 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 <i>Python</i> 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 <i>CoLoMoTo</i> suite. The tutorial covers the visualization of the network with the tool <i>GINsim</i>, an attractor analysis with <i>bioLQM</i>, the computation of synchronous attractors with <i>BNS</i>, the extraction of modules from the full model, stochastic simulations of the wild-type model and of selected perturbations with <i>MaBoSS</i> and finally the delineation of compressed probabilistic state transition graphs. The integration of all these analyses in an executable <i>Jupyter Notebook</i> 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 <i>ColoMoTo</i> tools, to develop comprehensive dynamical analyses of various biological network models.