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        "author": "Charles Tapley Hoyt",
        "author_email": "charles.hoyt@scai.fraunhofer.de",
        "bugtrack_url": null,
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            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3 :: Only",
            "Topic :: Scientific/Engineering :: Bio-Informatics",
            "Topic :: Scientific/Engineering :: Chemistry"
        ],
        "description": "BEL Enrichment |build|\n======================\nA package for generating curation sheets for rationally enriching a BEL graph.\n\nIf you find ``bel_enrichment`` useful in your work, please consider citing [1]_:\n\n.. [1] Hoyt, C. T., *et al* (2019). `Re-curation and Rational Enrichment of Knowledge Graphs in\n       Biological Expression Language <https://doi.org/10.1093/database/baz068>`_. *Database*, Volume 2019, 2019, baz068.\n\nAdditionally, this package also heavily builds on INDRA [2]_ and PyBEL [3]_.\n\nInstallation |pypi_version| |python_versions| |pypi_license|\n------------------------------------------------------------\n``bel_enrichment`` can be installed from PyPI with the following command:\n\n.. code-block:: bash\n\n   $ pip install bel_enrichment\n\nThe latest version can be installed from GitHub with:\n\n.. code-block:: bash\n\n   $ pip install git+https://github.com/bel-enrichment/bel-enrichment.git\n\nUsage\n-----\nGenerate a folder full of curation sheets based on the given BEL graph that has been pre-compiled by PyBEL.\nUse ``--info-cutoff`` to specify the minimum information density cutoff. 1.0 means that the node has no edges, .5 means\none edge, and so on. Use ``--belief-cutoff`` to specify the minimum belief score from INDRA for adding the statement\nto the sheet. Higher belief means the more chance a statement is already right.\n\n.. code-block:: bash\n\n   $ bel-enrichment make_sheet zhang2011.bel --directory ~/Desktop/zhang-enrichment\n\nGenerate a ranking for genes based on the information content in a given BEL graph that has been pre-compiled by PyBEL.\n\n.. code-block:: bash\n\n   $ bel-enrichment ranks zhang2011.bel\n\nReferences\n----------\n.. [2] Gyori, B. M., *et al.* (2017). `From word models to executable models of signaling networks using automated\n       assembly <https://doi.org/10.15252/msb.20177651>`_. Molecular Systems Biology, 13(11), 954.\n.. [3] Hoyt, C. T., Konotopez, A., Ebeling, C., (2017). `PyBEL: a computational framework for Biological Expression\n       Language <https://doi.org/10.1093/bioinformatics/btx660>`_. Bioinformatics (Oxford, England), 34(4), 703\u2013704.\n\n.. |build| image:: https://travis-ci.com/bel-enrichment/bel-enrichment.svg?branch=master\n    :target: https://travis-ci.com/bel-enrichment/bel-enrichment\n\n.. |python_versions| image:: https://img.shields.io/pypi/pyversions/bel_enrichment.svg\n    :alt: Stable Supported Python Versions\n\n.. |pypi_version| image:: https://img.shields.io/pypi/v/bel_enrichment.svg\n    :alt: Current version on PyPI\n\n.. |pypi_license| image:: https://img.shields.io/pypi/l/bel_enrichment.svg\n    :alt: License\n\n\n",
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        "keywords": "Biological Expression Language,BEL,Domain Specific Language,DSL,Systems Biology,Networks Biology",
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        "maintainer": "Charles Tapley Hoyt",
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