Dataset Information

Open Targets: a platform for therapeutic target identification and validation.

ABSTRACT: We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.

SUBMITTER: Koscielny G

PROVIDER: S-EPMC5210543 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Open Targets: a platform for therapeutic target identification and validation.

Koscielny Gautier G An Peter P Carvalho-Silva Denise D Cham Jennifer A JA Fumis Luca L Gasparyan Rippa R Hasan Samiul S Karamanis Nikiforos N Maguire Michael M Papa Eliseo E Pierleoni Andrea A Pignatelli Miguel M Platt Theo T Rowland Francis F Wankar Priyanka P Bento A Patrícia AP Burdett Tony T Fabregat Antonio A Forbes Simon S Gaulton Anna A Gonzalez Cristina Yenyxe CY Hermjakob Henning H Hersey Anne A Jupe Steven S Kafkas Şenay Ş Keays Maria M Leroy Catherine C Lopez Francisco-Javier FJ Magarinos Maria Paula MP Malone James J McEntyre Johanna J Munoz-Pomer Fuentes Alfonso A O'Donovan Claire C Papatheodorou Irene I Parkinson Helen H Palka Barbara B Paschall Justin J Petryszak Robert R Pratanwanich Naruemon N Sarntivijal Sirarat S Saunders Gary G Sidiropoulos Konstantinos K Smith Thomas T Sondka Zbyslaw Z Stegle Oliver O Tang Y Amy YA Turner Edward E Vaughan Brendan B Vrousgou Olga O Watkins Xavier X Martin Maria-Jesus MJ Sanseau Philippe P Vamathevan Jessica J Birney Ewan E Barrett Jeffrey J Dunham Ian I

Nucleic acids research 20161129 D1

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a spec ...[more]

PMID: 27899665

Similar Datasets

Project description:BackgroundThe Open Targets (OT) Platform integrates a wide range of data sources on target-disease associations to facilitate identification of potential therapeutic drug targets to treat human diseases. However, due to the complexity that targets are usually functionally pleiotropic and efficacious for multiple indications, challenges in identifying novel target to indication associations remain. Specifically, persistent need exists for new methods for integration of novel target-disease association evidence and biological knowledge bases via advanced computational methods. These offer promise for increasing power for identification of the most promising target-disease pairs for therapeutic development. Here we introduce a novel approach by integrating additional target-disease features with machine learning models to further uncover druggable disease to target indications.ResultsWe derived novel target-disease associations as supplemental features to OT platform-based associations using three data sources: (1) target tissue specificity from GTEx expression profiles; (2) target semantic similarities based on gene ontology; and (3) functional interactions among targets by embedding them from protein-protein interaction (PPI) networks. Machine learning models were applied to evaluate feature importance and performance benchmarks for predicting targets with known drug indications. The evaluation results show the newly integrated features demonstrate higher importance than current features in OT. In addition, these also show superior performance over association benchmarks and may support discovery of novel therapeutic indications for highly pursued targets.ConclusionOur newly generated features can be used to represent additional underlying biological relatedness among targets and diseases to further empower improved performance for predicting novel indications for drug targets through advanced machine learning models. The proposed methodology enables a powerful new approach for systematic evaluation of drug targets with novel indications.

Dataset Information

Open Targets: a platform for therapeutic target identification and validation.

Publications

Open Targets: a platform for therapeutic target identification and validation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets