Published July 1, 2020
| Version v2
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Notebooks demonstrating Most Permissive Boolean Networks
Description
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
Files
bonesis-preview-20200701.zip
Files
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