Abstract
In this talk, I will present the Europe PMC literature component of Open Targets – a target validation platform that integrates various evidence to aid drug target identification and validation (https://targetvalidation.org/). The component identifies target-disease associations from the Europe PMC literature database, based on rules utilizing expert provided heuristic information and serves the platform regularly with the up-to-date data. Currently, there are a total number of 1,168,365 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 currently available evidence data in the platform revealed that 850,179 of these associations are exclusively identified by literature mining. This component helps the platform’s users by providing the most relevant literature hits for a given target and disease. All the evidence data is available for download in JSON format from https://www.targetvalidation.org/downloads/data.
Brief Biography
Senay Kafkas is a text mining specialist in EMBL-EBI’s Literature Services Team where she is working on biomedical text mining with a special focus on service provision. Shenay holds a Ph.D. in Computer Science. In recent years her work has facilitated the development of several projects including the development of the Europe PMC text mining pipeline and the literature component for Open Targets. Shenay is involved in supervising MSc and Ph.D. projects and served as a referee for several scientific journals and conferences.