TY - JOUR T1 - Literature Evidence in Open Targets – a target validation platform JF - bioRxiv DO - 10.1101/124719 SP - 124719 AU - Şenay Kafkas AU - Ian Dunham AU - Johanna McEntyre Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/06/124719.abstract N2 - 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 and 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.Conclusion This component helps the platform’s users by providing the most relevant literature hits for a given target and disease. The text mining evidence along with the other types of evidence can be explored visually through https://www.targetvalidation.org and all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data.EFOExperimental Factor OntologyEurope PMCEurope PubMed CentralPMIDPubMed IdentifierCSConfidence ScoreMAPMean Average PrecisionRNARibonucleic AcidsGSKGlaxoSmithKline ER -