Conib

<p align="center"> <img src="https://docs.google.com/drawings/d/e/2PACX-1vSYe8SA8J1ulLRFqFjX2bne_L-5fxb-yHFcj1B2JYLksJS90qz8y2swPZPNSrw9Zj3tljrZikb5KWOg/pub?w=150&amp;h=150" /> </p> <h1 align="center"> Curation of Neurodegeneration in BEL (CONIB)<br> <a href="https://travis-ci.com/pharmacome/conib"> <img src="https://travis-ci.com/pharmacome/conib.svg?branch=master" alt="Travis CI"> </a> <a href="https://pypi.org/project/conib"> <img alt="PyPI" src="https://img.shields.io/pypi/v/conib"> </a> <a href="https://doi.org/10.5281/zenodo.3385895"> <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.3385895.svg" alt="DOI"> </a> <br> </h1> <p align="center"> This knowledge repository, developed during the <a href="https://pharmacome.github.io">Human Brain Pharmacome project</a>, contains documents in Biological Expression Language (BEL) describing neurodegenerative disease phenomena such as tauopathies. </p> <p align="center"> <a href="#installation">Installation</a> • <a href="#usage">Usage</a> • <a href="#contributing">Contributing</a> • <a href="#license">License</a> </p>

Content

• conib: This folder contains curated BEL documents. Most have been organized by category (protein of interest, biological process of interest, pathway, etc.). Almost BEL documents correspond to a single publication, but a select few contain content from several due to topic-based curation.
• docs: This folder contains automatically generated HTML summaries of the content that can best be accesed through https://pharmacome.github.io/conib.
• notebooks: This folder contains various Jupyter notebooks associated with the repository. Since many of them use PyBEL-Jupyter, they may be best viewed using NBViewer.

Curation Planning

Here are a few links for navigating the GitHub issues and pull requests:

• Pull requests for curation
• Pull requests for recuration approved by a reviewer

Installation

conib can be installed from PyPI with the following command:

$ pip install conib

or the latest version can be installed from GitHub with:

$ pip install git+https://github.com/pharmacome/conib.git

Usage

The graph can be loaded with:

import conib

# Get a dictionary of names to graphs
graphs = conib.get_graphs()

# Get all BEL documents as a single graph
graph = conib.get_graph()

# Get all knowledge as INDRA statements
stmts = conib.get_indra_statements()

The latest compiled version of the graph can be retrieved remotely with:

import requests
import pybel

URL = 'https://github.com/pharmacome/conib/raw/master/conib/_cache.bel.nodelink.json'
res_json = requests.get(URL).json()

graph = pybel.from_nodelink(res_json)

# Get INDRA statements
from indra.sources.bel import process_pybel_graph
pbp = process_pybel_graph(graph)
pbp.get_statements()
stmts = pbp.statements

# Quick version
stmts = pybel.to_indra_statements(graph)

Contributing

Contributions are welcome! Please submit all pull requests to https://github.com/pharmacome/conib.

License

• BEL scripts in this repository are licensed under the CC0 1.0 Universal.
• Python source code in this repository is licensed under the MIT license.

More BEL Content

See A Listing of Publicly Available Content in the Biological Expression Language (BEL) on Charles Tapley Hoyt's blog for more BEL content.