Metadata-Version: 2.1
Name: mpbn
Version: 1.5
Summary: Simple implementation of Most Permissive Boolean networks
Home-page: https://github.com/pauleve/mpbn
Author: Loïc Paulevé
Author-email: loic.pauleve@ens-cachan.org
License: CeCILL
Description: 
        The `mpbn` Python module offers a simple implementation of reachability and attractor analysis in *Most Permissive Boolean Networks* ([doi:10.1038/s41467-020-18112-5](https://doi.org/10.1038/s41467-020-18112-5)).
        
        It is built on the `minibn` module from [colomoto-jupyter](https://github.com/colomoto/colomoto-jupyter) which allows importation of Boolean networks in many formats. See http://colomoto.org/notebook.
        
        ## Installation
        
        ### CoLoMoTo Notebook environment
        
        `mpbn` is distributed in the [CoLoMoTo docker](http://colomoto.org/notebook).
        
        ### Using pip
        
        #### Extra requirements
        * [clingo](https://github.com/potassco/clingo) and its Python module
        
        ```
        pip install mpbn
        ```
        
        ### Using conda
        ```
        conda install -c colomoto -c potassco mpbn
        ```
        
        ## Documentation
        
        Documentation is available at https://mpbn.readthedocs.io.
        
        Example notebooks:
        * https://nbviewer.jupyter.org/github/pauleve/mpbn/tree/master/examples/
        * http://doi.org/10.5281/zenodo.3719097
        
        
        [1]: https://arxiv.org/abs/1808.10240
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
