Knowledgebase · FAIRsharing

Open Targets

Open Targets is a data integration platform for access to and visualisation of potential drug targets associated with disease. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources.

Website
Record in FAIRsharing (doi:10.25504/FAIRsharing.3f9n4y)
Subjects: Biomedical Science, Drug Discovery, Epigenetics, Genetics, Genomics, Human Genetics, Molecular biology, Transcriptomics

Documentation, events and training

bio.tools API and tool documentation

Open Targets Platform API documentation (same homepage)
Open Targets (same name)

TeSS Training materials (8)

TeSS Events (23)

From variant to drug target: using the expanded Open Targets Platform to explore the genetics of target discovery 2025-04-23
LLMs in bioinformatics Q&A session 2025-04-16
Large Language Models and their applications in Bioinformatics 2025-02-26
WEBINAR: Global data resources for human genomics and health 2024-09-20 (linked to the bio.tools entry)
Exploring target-disease associations with the Open Targets Platform’s new interface 2024-01-31
Discover drug targets with Europe PMC Machine Learning Dataset and Open Targets 2023-03-21
Getting started with the Open Targets Platform GraphQL API 2021-09-15
A guide to identifying and prioritising drug targets with the Open Targets Platform 2021-05-19
Open Targets at University of Copenhagen for BRIDGE - Translational Excellence Programme 2020-08-20
Open Targets at King Abdulaziz University in Jeddah 2020-08-18
and 13 more

What is known per question

The questions of the decision tree, with what FAIRsharing says about this repository. ✓ supported, ✗ excluded, ? not known.

What kind of data do you want to archive?

? Spectra
? Crystal structures
? Computational chemistry
? Catalysis
? Compounds and reactions
? Bioassays and chemical biology
? Materials and polymers
? Images and microscopy
? Something else

Subjects: Biomedical Science; Drug Discovery; Epigenetics; Genetics; Genomics; Human Genetics; Molecular biology; Transcriptomics

Domains: Approved drug; Gene report; Rare Disorder; Text mining; disease; disease course; disease phenotype; gene-disease association; phenotype; target