PyBEL is a pure Python package for parsing and handling biological networks encoded in the Biological Expression Language (BEL). It also facilitates data interchange between common formats and databases such as NetworkX, JSON, JGIF, CSV, SIF, Cytoscape, CX, NDEx, SQL, and Neo4J.
Its companion package, PyBEL Tools, contains a suite of functions and pipelines for analyzing the resulting biological networks.
We realize there we have a name conflict with the python wrapper for the cheminformatics package, OpenBabel. If you’re looking for their python wrapper, see here.
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Installation 
PyBEL can be installed easily from PyPI with the following code in your favorite terminal:
$ pip install pybelor from the latest code on GitHub with:
$ pip install git+https://github.com/pybel/pybel.gitSee the installation documentation for more advanced instructions. Also, check the change log at CHANGELOG.rst.
Getting Started
More examples can be found in the documentation and in the PyBEL Notebooks repository.
Compiling from the REPL
This example illustrates how the a BEL document from the Human Brain Pharmacome project can be loaded from GitHub.
>>> import pybel
>>> url = 'https://raw.githubusercontent.com/pharmacome/knowledge/master/hbp_knowledge/proteostasis/kim2013.bel'
>>> graph = pybel.from_url(url)Displaying a BEL Graph in Jupyter
After installing jinja2 and ipython, BEL graphs can be displayed in Jupyter notebooks.
>>> from pybel.examples import sialic_acid_graph
>>> from pybel.io.jupyter import to_jupyter
>>> to_jupyter(sialic_acid_graph)Using the CLI
PyBEL also installs a command line interface with the command pybel for simple utilities such as data
conversion. In this example, a BEL document is compiled then exported to GraphML
for viewing in Cytoscape.
$ pybel compile ~/Desktop/example.bel
$ pybel serialize ~/Desktop/example.bel --graphml ~/Desktop/example.graphmlIn Cytoscape, open with Import > Network > From File.
Contributing
Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.rst for more information on getting involved. Please add your name to AUTHORS.rst!
Acknowledgements
This package was originally developed as part of the master’s work of Charles Tapley Hoyt at Fraunhofer SCAI.
This software is proudly built with Paul McGuire’s PyParsing package.
Scott Colby designed our logo and provided sage advice
Christian Ebeling for supervision and consultation
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