These notebooks demonstrate Most Permissive Boolean Networks (doi:10.1101/2020.03.22.998377) on several case studies of biological networks. They can be executed interactively within the CoLoMoTo Docker version 2020-07-01: online, using myBinder service at https://mybinder.org/v2/zenodo/10.5281/zenodo.3936123/ or on your computer, provided you have Docker and Python 3 installed: download the notebooks individually from below, or from https://github.com/pauleve/MPBNs-SI-Notebooks/archive/main.zip and extract the zip file execute the following commands, where notebooks is the folder in which you extracted the notebooks: sudo pip install -U colomoto-docker # you may have to use pip3 instead of pip colomoto-docker -V 2020-07-01 --bind notebooks Visualize online: MPBN applied to Bladder Tumorigenesis by Remy et al 2015.ipynb MPBN applied to T-Cell differentiation model by Abou-Jaoudé et al. 2015.ipynb MPBN applied to Tumour invasion model by Cohen et al. 2015.ipynb I3FFL - compatible MPBNs.ipynb Scalability on large random BNs.ipynb The notebooks rely on the Python library mpbn, see the documentation for usage and examples at https://mpbn.readthedocs.io