Open Targets Platform: new developments and updates two years on

By D. Carvalho-Silva, Andrea Pierleoni, Miguel Pignatelli, C. Ong, Luca Fumis, Nikiforos Karamanis, M. Carmona, Adam Faulconbridge, Andrew Hercules, Elaine McAuley and 8 more. Nucleic Acids Res., 2018

422 citations recorded by the source corpus.

Abstract The Open Targets Platform integrates evidence from genetics, genomics, transcriptomics, drugs, animal models and scientific literature to score and rank target-disease associations for drug target identification. The associations are displayed in an intuitive user interface (https://www.targetvalidation.org), and are available through a REST-API (https://api.opentargets.io/v3/platform/docs/swagger-ui) and a bulk download (https://www.targetvalidation.org/downloads/data). In addition to target-disease associations, we also aggregate and display data at the target and disease levels to aid target prioritisation. Since our first publication two years ago, we have made eight releases, added new data sources for target-disease associations, started including causal genetic variants from non genome-wide targeted arrays, added new target and disease annotations, launched new visualisations and improved existing ones and released a new web tool for batch search of up to 200 targets. We have a new URL for the Open Targets Platform REST-API, new REST endpoints and also removed the need for authorisation for API fair use. Here, we present the latest developments of the Open Targets Platform, expanding the evidence and target-disease associations with new and improved data sources, refining data quality, enhancing website usability, and increasing our user base with our training workshops, user support, social media and bioinformatics forum engagement.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4992d87ff038ae3bcdf8efdf805464d6f9db93a0

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Citations in the corpus

Open Targets Platform: supporting systematic drug–target identification and prioritisation (2020, neutral): “genetic association, known drugs), a weighted harmonic sum is estimated for each of the data types (3).”
Expression Atlas update: from tissues to single cells (2019, background): “European Molecular Biology Laboratory (EMBL) member states; Single Cell Gene Expression Atlas and PRIDE grants from the Wellcome Trust [108437/Z/15/Z and 208391/Z/17/Z]; National Science Foundation of USA grant to Gramene database [NSF IOS #1127112]; Open Targets; Chan Zuckerberg Initiative; Cesar A”
Utilizing graph machine learning within drug discovery and development (2021, methodology): “[47], whereby a knowledge graph link prediction approach was used to beat the in house algorithms of open targets [161] to rediscover drug targets within clinical trials for Parkinson’s disease.”
UniProt: the universal protein knowledgebase in 2021 (2020, methodology): “The ProtVista viewer has already been implemented by the Open Targets (43) and the Pharos (44) databases of unstudied and understudied drug targets amongst others.”
Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics (2020, methodology): “This stand-alone genetics resource within the Open Targets ecosystem complements the existing Open Targets Platform and provides underlying genetic evidence to aid drug target identification and prioritisation.”
Artificial intelligence to deep learning: machine intelligence approach for drug discovery (2021, methodology): ““OpenTargets” (https:// www. opent argets. org/) [374], a freeware and ML-based tool, used for prioritizing potential therapeutic drug targets with over 71% accuracy.”
In silico methods and tools for drug discovery (2021, background): “The platform then ranks genes according to their association with disease [46].”
Machine learning applications in drug development (2019, neutral): “…a drug development setting, statistical methods, random forests, and gradient boosting algorithms helped to successfully predict therapeutic targets from selected features linking genes and diseases of the Open Targets platform [97], or based on gene expression proﬁles of the LINCS database [92].”
BIOPEP-UWM Database of Bioactive Peptides: Current Opportunities (2019, background): “Information about associations between abnormal enzyme activity and diseases may be found in the OpenTargets database [42].”