pybel

PyBEL is a Python software package that parses BEL scripts, validates their semantics, applies common graph algorithms, and facilitates data interchange between common formats and database systems like JSON, CSV, SQL, and Neo4J.

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Development

Biological Expression Language (BEL) is a domain-specific language that enables the expression of complex molecular relationships and their context in a machine-readable form. Its simple grammar and expressive power have led to its successful use in the IMI project, AETIONOMY, to describe complex disease networks with several thousands of relationships.

PyBEL provides a simple API so bioinformaticians and scientists with limited programming knowledge can easily use it to interface with BEL graphs, but is built on a rich framework that can be extended to develop new algorithms.

>>> import pybel, networkx
>>> g = pybel.from_url('http://resource.belframework.org/belframework/1.0/knowledge/small_corpus.bel')
>>> networkx.draw(g)  # NOTE: requires matplotlib as a dependency, which isn't automatically installed

PyBEL also installs a command line interface with the command pybel for simple utilities such as data conversion. Need help? All logs go to ~/.pybel or add -v for verbose output to the standard error stream. In this example, a BEL file is exported to GraphML for viewing in Cytoscape.

$ pybel convert --path ~/Desktop/example.bel --graphml ~/Desktop/example.graphml

In Cytoscape, open with Import > Network > From File.

Installation

Current version on PyPI Stable Supported Python Versions Apache 2.0 License

PyBEL can be installed easily from PyPI with the following code in your favorite terminal:

pip install pybel

See the installation documentation for more advanced instructions. Also, check the change log at CHANGELOG.rst.

Contributing

Contributions, whether filing an issue, making a pull request, or forking, are appreciated. See CONTRIBUTING.rst for more information on getting involved.

Acknowledgements

This software is proudly built with Paul McGuire’s PyParsing package.
Scott Colby designed our logo and provided sage advice
Core Team: Charles Tapley Hoyt, Andrej Konotopez, and Christian Ebeling

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