University of Cambridge > > Computational and Systems Biology Seminar Series 2023 - 24 > Finding Target-Disease-Drug evidences from Literature and supporting curators. Please note: the details of this talk have changed

Finding Target-Disease-Drug evidences from Literature and supporting curators. Please note: the details of this talk have changed

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  • UserMatthew Jeffryes and Santosh Tirunagari, EMBL-EBI
  • ClockWednesday 15 March 2023, 14:00-15:00
  • HouseCMS, Meeting Room 15.

If you have a question about this talk, please contact Samantha Noel.

Our intention is to deliver all Seminars in person. Seminars are aimed mainly at MPhil CompBio students, but are open to anyone who wishes to attend by pre-booking with the Administrator

Europe PMC is a repository of life sciences research, including peer reviewed research articles and preprints – all freely available for use via the website ( The repository contains over 42 million abstracts and 8.6 million full text research articles. Assisting researchers with the difficult task of trying to “keep up with the literature” as output has grown year on year has become a priority in the machine learning community. As a result, the important area of “scientific services” as a foundation for modern biomedical science is increasing and the associated use of computation to service this. This talk covers how machine learning can be applied directly to the literature but also how it can be used to assist people whose role it is to curate the bioinformatic content. We present the Europe PMC ’s framework for extracting evidences from the scientific research articles. These evidences are currently being submitted to Open Targets (, a target validation platform that integrates various evidences to aid drug target identification and validation. The Europe PMC ’s framework harnesses the deep learning methodologies to identify Gene/Protein, Disease and Chemical/Drug associations from the scientific articles and it ranks the articles based on their confidence from the Europe PMC literature database. We also present the biocuration toolkit, a combination of machine learning with software engineering to develop applications to support biocuration workflows. Bioinformatics relies on the provision of databases like UniProt, PDB , InterPro, IntAct and many others. To varying extents, these databases rely on “curation”: the manual integration of information into a structured format. The curators who perform this task are domain experts, extracting information from the biomedical literature and other sources and making it accessible to computational methods. Identifying relevant information from the literature becomes more difficult as the rate of growth for the literature increases year on year. This tool will assist biocurators with this process to increase their biocuration capabilities.

This talk is part of the Computational and Systems Biology Seminar Series 2023 - 24 series.

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