Literature evidence in open targets - a target validation platform

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Abstract

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. Conclusions: 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.organd all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data.

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Kafkas, Ş., Dunham, I., & McEntyre, J. (2017). Literature evidence in open targets - a target validation platform. Journal of Biomedical Semantics, 8(1). https://doi.org/10.1186/s13326-017-0131-3

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