Searching across hundreds of databases
Europe PMC (https://europepmc.org) is a comprehensive resource of biomedical research publications that offers advanced tools for search, retrieval, and interaction with the scientific literature. This article outlines new developments since 2014. In addition to delivering the core database and services, Europe PMC focuses on three areas of development: individual user services, data integration, and infrastructure to support text and data mining. Europe PMC now provides user accounts to save search queries and claim publications to ORCIDs, as well as open access profiles for authors based on public ORCID records. We continue to foster connections between scientific data and literature in a number of ways. All the data behind the paper - whether in structured archives, generic archives or as supplemental files - are now available via links to the BioStudies database. Text-mined biological concepts, including database accession numbers and data DOIs, are highlighted in the text and linked to the appropriate data resources. The SciLite community annotation platform accepts text-mining results from various contributors and overlays them on research articles as licence allows. In addition, text miners and developers can access all open content via APIs or via the FTP site.
Pubmed ID: 29161421 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Text mining tool from Europe PMC that allows biological terms or concepts to be highlighted for readers on full text articles. These terms and concepts are identified by text mining algorithms, which are developed by a variety of text mining groups. However, it is up to the reader to control which selection of highlighted concepts they see. Once concepts of interest have been identified within the text, they are formatted according to the W3C Web Annotation Data Model and stored in a triple store via the EMBL-EBI RDF Platform. As a reader views an article in a web browser, any annotations in the triple store associated with the article are made available in a menu alongside the article.
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