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Hetionet

Daniel S Himmelstein
,
Antoine Lizee
,
Christine Hessler
,
Leo Brueggeman
,
Sabrina L Chen
,
Dexter Hadley
,
Ari Green
,
Pouya Khankhanian
,
Sergio E Baranzini

An integrative disease network. Hetionet is an integrative network of biomedical knowledge assembled from 29 different databases of genes, compounds, diseases, and more.

Updated on July 23, 2020 (Version 2, Revision 1)

Corresponding Contributor:

Joost Wagenaar
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47 Files
3.52 GB
47,031 Records

Dataset Overview

Hetionet: an integrative network of disease

Hetionet is a hetnet — network with multiple node and edge (relationship) types — which encodes biology. The hetnet was designed for Project Rephetio, which aims to systematically identify why drugs work and predict new therapies for drugs. The research article describing Project Rephetio and Hetionet v1.0 is:

Systematic integration of biomedical knowledge prioritizes drugs for repurposing Daniel S Himmelstein, Antoine Lizee, Christine Hessler, Leo Brueggeman, Sabrina L Chen, Dexter Hadley, Ari Green, Pouya Khankhanian, Sergio E Baranzini eLife (2017-09-22) DOI: 10.7554/eLife.26726

For more information, please visit the project website at: https://het.io/

Using the Dataset

This dataset was sourced from hetio/hetionet on Github. The Github repository contains more information about how to use Hetionet and how the data was integrated.

The data is available for download in four formats:

  • JSON
  • Neo4j (see this guide for instructions)
  • TSV
  • matrix

In addition, five versions of hetionet are included which have randomized graph edges.

A Note on licensing

Taken from the original Github repository:

All original content in this repository is released as CC0. However, the hetnet integrates data from many resources and users should consider the licensing of each source (see this table). We apply a license attribute on a per node and per edge basis for sources with defined licenses. However, some resources don't provide any license, so for those we've requested permission. More information is available on Thinklab.

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About this dataset

Publishing history

July 1, 2019
Originally Published
July 23, 2020 (Version 2)
Last Updated

Cite this dataset