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Notebooks demonstrating Most Permissive Boolean Networks

Paulevé, Loïc

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  "description": "<p>These notebooks can be executed within <a href=\"\"><code>colomoto/colomoto-docker:2020-03-19</code></a> Docker image.</p>\n\n<p>They rely on the Python library <a href=\"\">mpbn</a>, see the documentation for usage and examples at <a href=\"\"></a></p>\n\n<p>Visualize online:</p>\n\n<ul>\n\t<li><a href=\"\">MPBN applied to Bladder Tumorigenesis by Remy et al 2015.ipynb</a></li>\n\t<li><a href=\"\">MPBN applied to T-Cell differentiation model by Abou-Jaoud&eacute; et al. 2015.ipynb</a></li>\n\t<li><a href=\"\">MPBN applied to Tumour invasion model by Cohen et al. 2015.ipynb</a></li>\n\t<li><a href=\"\">Scalability on large random BNs.ipynb</a></li>\n</ul>", 
  "license": "", 
  "creator": [
      "affiliation": "CNRS/LaBRI", 
      "@id": "", 
      "@type": "Person", 
      "name": "Paulev\u00e9, Lo\u00efc"
  "url": "", 
  "datePublished": "2020-03-20", 
  "version": "v1", 
  "keywords": [
    "Jupyter notebooks", 
    "Computational systems biology"
  "@context": "", 
  "identifier": "", 
  "@id": "", 
  "@type": "CreativeWork", 
  "name": "Notebooks demonstrating Most Permissive Boolean Networks"
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