Other Open Access

Notebooks demonstrating Most Permissive Boolean Networks

Paulevé, Loïc


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3936123", 
  "author": [
    {
      "family": "Paulev\u00e9, Lo\u00efc"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2020, 
        7, 
        1
      ]
    ]
  }, 
  "abstract": "<p>These notebooks demonstrate Most Permissive Boolean Networks (<a href=\"http://dx.doi.org/10.1101/2020.03.22.998377\">doi:10.1101/2020.03.22.998377</a>) on several case studies of biological networks.</p>\n\n<p>They can be executed interactively within the <a href=\"http://colomoto.org/notebook\">CoLoMoTo Docker</a> version <code>2020-07-01</code>:</p>\n\n<ul>\n\t<li>online, using myBinder service at <a href=\"https://mybinder.org/v2/zenodo/10.5281/zenodo.3936123/\">https://mybinder.org/v2/zenodo/10.5281/zenodo.3936123/</a></li>\n\t<li>or on your computer, provided you have <a href=\"https://docs.docker.com/get-docker/\">Docker</a> and Python 3 installed:\n\t<ol>\n\t\t<li>download the notebooks individually from below, or from <a href=\"https://github.com/pauleve/MPBNs-SI-Notebooks/archive/main.zip\">https://github.com/pauleve/MPBNs-SI-Notebooks/archive/main.zip</a> and extract the zip file</li>\n\t\t<li>execute the following commands, where <code>notebooks</code> is the folder in which you extracted the notebooks:\n\t\t<pre><code class=\"language-bash\">sudo pip install -U colomoto-docker # you may have to use pip3 instead of pip\ncolomoto-docker -V 2020-07-01 --bind notebooks</code></pre>\n\t\t</li>\n\t</ol>\n\t</li>\n</ul>\n\n<p>Visualize online:</p>\n\n<ul>\n\t<li><a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/3936123/files/MPBN%20applied%20to%20Bladder%20Tumorigenesis%20by%20Remy%20et%20al%202015.ipynb\">MPBN applied to Bladder Tumorigenesis by Remy et al 2015.ipynb</a></li>\n\t<li><a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/3936123/files/MPBN%20applied%20to%20T-Cell%20differentiation%20model%20by%20Abou-Jaoud%C3%A9%20et%20al.%202015.ipynb\">MPBN applied to T-Cell differentiation model by Abou-Jaoud&eacute; et al. 2015.ipynb</a></li>\n\t<li><a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/3936123/files/MPBN%20applied%20to%20Tumour%20invasion%20model%20by%20Cohen%20et%20al.%202015.ipynb\">MPBN applied to Tumour invasion model by Cohen et al. 2015.ipynb</a></li>\n\t<li><a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/3936123/files/I3FFL%20-%20compatible%20MPBNs.ipynb\">I3FFL - compatible MPBNs.ipynb</a></li>\n\t<li><a href=\"https://nbviewer.jupyter.org/urls/zenodo.org/record/3936123/files/Scalability%20on%20large%20random%20BNs.ipynb\">Scalability on large random BNs.ipynb</a></li>\n</ul>\n\n<p>The notebooks rely on the Python library <a href=\"https://github.com/pauleve/mpbn\">mpbn</a>, see the documentation for usage and examples at <a href=\"https://mpbn.readthedocs.io/\">https://mpbn.readthedocs.io</a></p>", 
  "title": "Notebooks demonstrating Most Permissive Boolean Networks", 
  "type": "article", 
  "id": "3936123"
}
225
185
views
downloads
All versions This version
Views 225115
Downloads 18594
Data volume 39.9 MB8.4 MB
Unique views 187101
Unique downloads 13261

Share

Cite as