Open Targets statistics

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Citations per year

Citations chart

Popular tool citations

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Tool usage distribution map

Tool usage distribution map

Associated diseases

Associated diseases

Open Targets specifications


Unique identifier OMICS_14227
Name Open Targets
Interface Web user interface
Restrictions to use None
Programming languages Javascript, Python, R
License Apache License version 2.0
Computer skills Basic
Version 2.0.5
Stability Stable
Maintained Yes



  • person_outline Gautier Koscielny <>

Publication for Open Targets

Open Targets in publications

PMCID: 5576250
PMID: 28851378
DOI: 10.1186/s12967-017-1285-6

[…] [] was used for text mining the medline database. all code was versioned using git and is available at, observations and features were collected from the open targets platform []. it utilises seven distinct data types to represent associations between genes and diseases: affected_pathway (the gene is part of a pathway that is affected in disease), […]

PMCID: 5461726
PMID: 28587637
DOI: 10.1186/s13326-017-0131-3

[…] previously analysed the coverage of efo against other 5 major disease/phenotype resources (ordo, umls, mp, hdo and hp) []. based on our previous finding, which is in line with the current finding, open targets is currently working on developing methods to expand efo’s coverage. the abbreviation name filtering performance alone was estimated to have an f-score value of 92.3% by evaluating […]

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Open Targets institution(s)
Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, UK; GSK, Medicines Research Center, Gunnels Wood Road, Stevenage, UK; Biogen, Cambridge, MA, USA; European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK; Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK; National Center for Protein Research, Changping District, Beijing, China
Open Targets funding source(s)
This work was funded by the Open Targets and an open innovation public-private partnership.

Open Targets review

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Platform dedicated to identify and rank targets for follow up in drug pipelines.
A sustainable, easy to use resource to find connections between gene and diseases.
(full disclosure: I contributed to the tool)