dvklopfenstein / ReactomePy

Explore biomolecular pathways in Reactome from the command-line or a Python script

Reactome, Python, and Neo4j

Explore biomolecular pathways in the Reactome graph database from the command-line or a Python script.

Reactome

In addition to biomolecular pathways, Reactome contains expert-authored and peer-reviewed reactions, molecular complex ingredients and structure, and protein-protein interactions.

Reactome also provides links from pathways, reactions, and molecules to biological models, associated research papers, URLs, and books.

Use this Python3 library to:

1. Run Reactome's Neo4j Tutorial from one of the Jupyter notebooks or a plain Python script

2. Find enriched pathways from the command line, accessing Reactome's online Pathway Analysis Service

3. Write your own Python scripts accessing the Reactome database through Neo4j

Links

• Official Reactome Help

  • Reactome Documentation
  • Support: [e-mail]
  • Or open an issue on GitHub like this one or driver

• Unofficial user's download hints

  • 1) Install Neo4j
  • 2) Download Reactome Knowledgebase

• Reactome Publications

  • 2018 | Reactome graph database: Efficient access to complex pathway data

• Reactome Documentation

  • Data Schema
  • Glossary Data Model
  • Icon library
  • Reactome Graph Database on GitHub

• This project uses the Neo4j Python driver that is officially supported by Neo4j

  • https://github.com/neo4j/neo4j-python-driver

To Cite

Please cite if this repo is used in your research:

Klopfenstein DV, Dampier W ReactomePy Zenodo | (2019) | DOI: 10.5281/zenodo.2634376

BibLaTeX citation

@online{klopfenstein2019reactomepy,
  author = {Klopfenstein, DV and 
            Dampier, W},
  title = {ReactomePy},
  year = 2019,
  month = apr,
  url = {https://github.com/dvklopfenstein/ReactomePy},
  doi = {10.5281/zenodo.2634376},
}

Copyright (C) 2018-present, DV Klopfenstein. All rights reserved.