Open Targets: a platform for therapeutic target identification and validation

Koscielny, Gautier; An, Peter; Carvalho-Silva, Denise; Cham, Jennifer A.; Fumis, Luca; Gasparyan, Rippa; Hasan, Samiul; Karamanis, Nikiforos; Maguire, Michael E.; Papa, Eliseo; Pierleoni, Andrea; Pignatelli, Miguel; Platt, Theo; Rowland, Francis; Wankar, Priyanka; Bento, A. Patrícia; Burdett, Tony; Fabregat, Antonio; Forbes, Simon; Gaulton, Anna; González, Cristina; Hermjakob, Henning; Hersey, Anne; Jupe, S; Kafkas, Şenay; Keays, Maria; Leroy, Catherine; Lopez, Francisco-Javier; Magariños, María Paula; Malone, James; McEntyre, Johanna; Fuentes, Alfonso Muñoz-Pomer; O′Donovan, Claire; Papatheodorou, Irene; Parkinson, Helen; Palka, Barbara; Paschall, Justin; Petryszak, Robert; Pratanwanich, Naruemon; Sarntivijal, Sirarat; Saunders, Gary; Sidiropoulos, Konstantinos; Smith, Thomas B.; Sońdka, Zbysław; Stegle, Oliver; Tang, Y. Amy; Turner, E. B.; Vaughan, Brendan; Vrousgou, Olga; Watkins, Xavier; Martin, Maria-Jesus; Sanséau, Philippe; Vamathevan, Jessica; Birney, Ewan; Barrett, Jeffrey C.; Dunham, Ian

doi:10.1093/nar/gkw1055

Cited by 423 publications

(387 citation statements)

References 52 publications

Supporting

Mentioning

384

Contrasting

Unclassified

Order By: Relevance

“…pathway, expression or disease information). ChEMBL data is incorporated into a wide range of other resources including PubChem BioAssay (52), BindingDB (11), CanSAR (53), Open PHACTS (54), Open Targets (55) and the Target Central Resource Database/PHAROS (http://juniper.health.unm.edu/tcrd/, 56), so can also be accessed via these routes. However, since these other resources are different in scope, they do not all incorporate ChEMBL in full (e.g.…”

Section: Data Accessmentioning

confidence: 99%

The ChEMBL database in 2017

et al. 2016

Self Cite

View full text Add to dashboard Cite

ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 and 2014 Nucleic Acids Research Database Issues. Since then, alongside the continued extraction of data from the medicinal chemistry literature, new sources of bioactivity data have also been added to the database. These include: deposited data sets from neglected disease screening; crop protection data; drug metabolism and disposition data and bioactivity data from patents. A number of improvements and new features have also been incorporated. These include the annotation of assays and targets using ontologies, the inclusion of targets and indications for clinical candidates, addition of metabolic pathways for drugs and calculation of structural alerts. The ChEMBL data can be accessed via a web-interface, RDF distribution, data downloads and RESTful web-services.

show abstract

Section: Data Accessmentioning

confidence: 99%

The ChEMBL database in 2017

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore, the update paper from OGEE, the gene essentiality database, includes an interesting focus on genes that are differentially essential in different cancers. More generally, DisGeNET and Open Targets [another new database designated as a ‘Breakthrough’ paper, (3)], both offer comprehensive resources linking pathogenic gene variants to a variety of other data.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 24th annualNucleic Acids Researchdatabase issue: a look back and upcoming changes

2017

View full text Add to dashboard Cite

This year's Database Issue of Nucleic Acids Research contains 152 papers that include descriptions of 54 new databases and update papers on 98 databases, of which 16 have not been previously featured in NAR. As always, these databases cover a broad range of molecular biology subjects, including genome structure, gene expression and its regulation, proteins, protein domains, and protein–protein interactions. Following the recent trend, an increasing number of new and established databases deal with the issues of human health, from cancer-causing mutations to drugs and drug targets. In accordance with this trend, three recently compiled databases that have been selected by NAR reviewers and editors as ‘breakthrough’ contributions, denovo-db, the Monarch Initiative, and Open Targets, cover human de novo gene variants, disease-related phenotypes in model organisms, and a bioinformatics platform for therapeutic target identification and validation, respectively. We expect these databases to attract the attention of numerous researchers working in various areas of genetics and genomics. Looking back at the past 12 years, we present here the ‘golden set’ of databases that have consistently served as authoritative, comprehensive, and convenient data resources widely used by the entire community and offer some lessons on what makes a successful database. The Database Issue is freely available online at the https://academic.oup.com/nar web site. An updated version of the NAR Molecular Biology Database Collection is available at http://www.oxfordjournals.org/nar/database/a/.

show abstract

“…(Please refer to [1] for further information about how the other types of evidence data are gathered.) In the current release (release 1.2) of the platform, there are a total number of 2,485,000 distinct target-disease associations.…”

Section: Resultsmentioning

confidence: 99%

Literature evidence in open targets - a target validation platform

2017

Self Cite

View full text Add to dashboard Cite

Background: We present the Europe PMC literature component of Open Targets -a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confidence from the Europe PMC literature database, by using rules utilising expert-provided heuristic information. The confidence score of a given document represents how valuable the document is in the scope of target validation for a given target-disease association by taking into account the credibility of the association based on the properties of the text. The component serves the platform regularly with the up-to-date data since December, 2015. Results: Currently, there are a total number of 1168365 distinct target-disease associations text mined from >26 million PubMed abstracts and >1.2 million Open Access full text articles. Our comparative analyses on the current available evidence data in the platform revealed that 850179 of these associations are exclusively identified by literature mining.

show abstract

Open Targets: a platform for therapeutic target identification and validation

Cited by 423 publications

References 52 publications

The ChEMBL database in 2017

The ChEMBL database in 2017

The 24th annualNucleic Acids Researchdatabase issue: a look back and upcoming changes

Literature evidence in open targets - a target validation platform

Contact Info

Product

Resources

About