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 that we have a name conflict with the python wrapper for the cheminformatics package, OpenBabel. If you’re looking for their python wrapper, see here.
Citation
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Installation 
PyBEL can be installed easily from PyPI with the following code in your favorite shell:
$ 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.
Note: while PyBEL works on the most recent versions of Python 3.5, it does not work on 3.5.3 or below due to changes in the typing module.
Getting Started
More examples can be found in the documentation and in the PyBEL Notebooks repository.
Compiling and Saving a BEL Graph
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)PyBEL can handle BEL 1.0 and BEL 2.0+ simultaneously.
After you have a BEL graph, there are numerous ways to save it. The pybel.dump function knows how to output it in many formats based on the file extension you give. For all of the possibilities, check the I/O documentation.
>>> import pybel
>>> graph = ...
>>> # write as BEL
>>> pybel.dump(graph, 'my_graph.bel')
>>> # write as Node-Link JSON for network viewers like D3
>>> pybel.dump(graph, 'my_graph.bel.nodelink.json')
>>> # write as GraphDati JSON for BioDati
>>> pybel.dump(graph, 'my_graph.bel.graphdati.json')
>>> # write as CX JSON for NDEx
>>> pybel.dump(graph, 'my_graph.bel.cx.json')Grounding the Graph
Not all BEL graphs contain both the name and identifier for each entity. Some even use non-standard prefixes (also called namespaces in BEL). Usually, BEL graphs are validated against controlled vocabularies, so the following demo shows how to add the corresponding identifiers to all nodes.
from urllib.request import urlretrieve
url = 'https://github.com/cthoyt/selventa-knowledge/blob/master/selventa_knowledge/large_corpus.bel.nodelink.json.gz'
urlretrieve(url, 'large_corpus.bel.nodelink.json.gz')
import pybel
graph = pybel.load('large_corpus.bel.nodelink.json.gz')
import pybel.grounding
pybel.grounding.ground(covid19_graph)Note: you have to install pyobo for this to work and be running Python 3.7+.
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.
Acknowledgements
Supporters
This project has been supported by several organizations:
Logo
The PyBEL logo was designed by Scott Colby.
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