hetionet — Hetionet biomedical knowledge graph (v1.0, 2017)

Description

Hetionet is a heterogeneous network ("hetnet") of biomedical knowledge, built by Himmelstein et al. for Project Rephetio, which predicted new uses of existing drugs. It integrates data from 29 public resources (e.g. Entrez Gene, Gene Ontology, DrugBank, SIDER, Disease Ontology, Uberon, Reactome, WikiPathways, LINCS L1000, Bgee, MEDLINE topic co-occurrence), and contains nodes of 11 kinds: genes (20,945), biological processes (11,381), side effects (5,734), molecular functions (2,884), pathways (1,822), compounds (1,552, approved small-molecule drugs), cellular components (1,391), symptoms (438), anatomical structures (402), pharmacologic classes (345) and diseases (137). This is version 1.0 of the network.

The edges are of 24 kinds (metaedges), each a relation between nodes of two given kinds, e.g. a compound treats a disease, a gene participates in a pathway, an anatomical structure expresses a gene, or a gene regulates another gene. A directed edge from node $i$ to node $j$ means that $i$ has the relation to $j$ (the source and target nodes of the data); only the relation regulates (between genes) is directional, while the others are symmetric relations, stated in the order of the kinds of their nodes. Pairs of nodes may be connected by several edges of different kinds.

Some edges are "unbiased", i.e. come from systematic, genome-wide data (e.g. high-throughput experiments), rather than from the literature, which is biased towards well-studied genes. The original content of Hetionet is released into the public domain (CC0), but the integrated resources have their own licenses, recorded for each node and edge where known; some of them restrict the use of their data, e.g. to noncommercial purposes (CC BY-NC 4.0 for DrugBank, CC BY-NC-SA 4.0 for SIDER), and for some resources without a license, the authors obtained permission to include their data.

The network has the following properties:

kind: the kind of the node (Gene, Compound, Disease, ...).
identifier: the identifier of the node in its source resource (e.g. the Entrez Gene id of a gene, the DrugBank id of a compound, the Disease Ontology id of a disease).
name: the name of the node.
source: the resource of the node.
license: the license of the node's data.
url: a web page of the node in its source resource (empty if absent).
description and chromosome: the description of a gene, and the chromosome where it is located (empty for other nodes).
inchikey and inchi: the InChIKey and InChI chemical identifiers of a compound (empty for other nodes).
mesh_id and bto_id: the Medical Subject Headings and BRENDA Tissue Ontology identifiers of an anatomical structure (empty for other nodes or if absent).
class_type: the type of a pharmacologic class (empty for other nodes).
Edge kind: the relation (treats, participates, regulates, ...); together with the kinds of its nodes, it gives the kind of the edge (metaedge).
Edge sources: the resources that the edge comes from.
Edge license: the license of the edge's data (empty if not given).
Edge unbiased: whether the edge comes from systematic, unbiased data.
Edge urls: web pages of the evidence for the edge (empty if absent).
Edge pubmed_ids: the PubMed identifiers of the publications supporting a compound-gene binding (empty if absent).
Edge actions: the actions of a compound on the gene it binds (e.g. inhibitor, agonist; empty if absent).
Edge affinity_nm: the binding affinity of a compound and a gene, in nanomolar (NaN if absent).
Edge similarity: the chemical similarity (Dice coefficient of extended connectivity fingerprints) of two compounds that resemble each other (NaN for other edges).
Edge z_score: the consensus z-score of the up- or downregulation of a gene by a compound in LINCS L1000 (NaN for other edges).
Edge log2_fold_change: the log2 fold change of the up- or downregulation of a gene by a disease (NaN for other edges).
Edge method: the LINCS L1000 method for the regulation of genes (measured or imputed; empty for other edges).
Edge subtypes: the kinds of perturbation of a gene that regulate another (e.g. knockdown downregulates; empty for other edges).

Tags

Biological Protein interactions Gene regulation Drug interactions Unweighted Multigraph Metadata

Citation

D. S. Himmelstein, A. Lizee, C. Hessler, L. Brueggeman, S. L. Chen, D. Hadley, A. Green, P. Khankhanian, S. E. Baranzini, "Systematic integration of biomedical knowledge prioritizes drugs for repurposing." eLife 6, e26726 (2017) 10.7554/eLife.26726 Sci-Hub

Upstream URL OK

https://het.io
https://github.com/hetio/hetionet

Upstream license

CC0 1.0 (the integrated resources have their own licenses), https://github.com/dhimmel/integrate/blob/d482033bcaa913a976faf4a6ee08497281c739c3/licenses/README.md

Networks

Tip: hover over a column header for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
hetionet	47,031	2,250,197	47.84	471.93	695.15	13.26	-0.18	0.01	8	0.96	Directed	Unipartite	kind identifier name source license url description chromosome inchikey inchi mesh_id bto_id class_type	kind sources license unbiased urls pubmed_ids actions affinity_nm similarity z_score log2_fold_change method subtypes	9.6 MiB	20.5 MiB	20.0 MiB	16.1 MiB