RESUMO
Europe PMC (https://europepmc.org) is a database of research articles, including peer reviewed full text articles and abstracts, and preprints - all freely available for use via website, APIs and bulk download. This article outlines new developments since 2017 where work has focussed on three key areas: (i) Europe PMC has added to its core content to include life science preprint abstracts and a special collection of full text of COVID-19-related preprints. Europe PMC is unique as an aggregator of biomedical preprints alongside peer-reviewed articles, with over 180 000 preprints available to search. (ii) Europe PMC has significantly expanded its links to content related to the publications, such as links to Unpaywall, providing wider access to full text, preprint peer-review platforms, all major curated data resources in the life sciences, and experimental protocols. The redesigned Europe PMC website features the PubMed abstract and corresponding PMC full text merged into one article page; there is more evident and user-friendly navigation within articles and to related content, plus a figure browse feature. (iii) The expanded annotations platform offers â¼1.3 billion text mined biological terms and concepts sourced from 10 providers and over 40 global data resources.
Assuntos
Disciplinas das Ciências Biológicas/estatística & dados numéricos , COVID-19/prevenção & controle , Curadoria de Dados/estatística & dados numéricos , Mineração de Dados/estatística & dados numéricos , Bases de Dados Factuais/estatística & dados numéricos , PubMed , SARS-CoV-2/isolamento & purificação , Disciplinas das Ciências Biológicas/métodos , Pesquisa Biomédica/métodos , Pesquisa Biomédica/estatística & dados numéricos , COVID-19/epidemiologia , COVID-19/virologia , Curadoria de Dados/métodos , Mineração de Dados/métodos , Epidemias , Europa (Continente) , Humanos , Internet , SARS-CoV-2/fisiologiaRESUMO
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.
Assuntos
Pesquisa Biomédica , Bases de Dados Bibliográficas , Mineração de Dados , Internet , Publicações Seriadas , Interface Usuário-ComputadorRESUMO
BACKGROUND: As the availability of open access full text research articles increases, so does the need for sophisticated search services that make the most of this new content. Here, we present a new feature available in Europe PMC that allows selected sections of full text articles to be searched, including figures and reference lists. Users can now search particular parts of an article, reducing noise and allowing fine-tuning of searches. RESULTS: To the best of our knowledge, Europe PMC is the first service that provides a granular literature search by allowing users to target their search to particular sections of articles. This new functionality is based on a heuristic algorithm that identifies and categorises article sections into 17 pre-defined categories based on the section heading. The tagger's performance is measured against a manually curated dataset consisting of 100 full text articles with an F-score of 98.02%. CONCLUSIONS: The section search is available from the advanced search within Europe PMC (http://europepmc.org). The source code is freely available from http://europepmc.org/ftp/oa/SectionTagger/.
RESUMO
BACKGROUND: In this study, we present an analysis of data citation practices in full text research articles and their corresponding supplementary data files, made available in the Open Access set of articles from Europe PubMed Central. Our aim is to investigate whether supplementary data files should be considered as a source of information for integrating the literature with biomolecular databases. RESULTS: Using text-mining methods to identify and extract a variety of core biological database accession numbers, we found that the supplemental data files contain many more database citations than the body of the article, and that those citations often take the form of a relatively small number of articles citing large collections of accession numbers in text-based files. Moreover, citation of value-added databases derived from submission databases (such as Pfam, UniProt or Ensembl) is common, demonstrating the reuse of these resources as datasets in themselves. All the database accession numbers extracted from the supplementary data are publicly accessible from http://dx.doi.org/10.5281/zenodo.11771. CONCLUSIONS: Our study suggests that supplementary data should be considered when linking articles with data, in curation pipelines, and in information retrieval tasks in order to make full use of the entire research article. These observations highlight the need to improve the management of supplemental data in general, in order to make this information more discoverable and useful.
RESUMO
The GenitoUrinary Development Molecular Anatomy Project (GUDMAP) is an international consortium working to generate gene expression data and transgenic mice. GUDMAP includes data from large-scale in situ hybridisation screens (wholemount and section) and microarray gene expression data of microdissected, laser-captured and FACS-sorted components of the developing mouse genitourinary (GU) system. These expression data are annotated using a high-resolution anatomy ontology specific to the developing murine GU system. GUDMAP data are freely accessible at www.gudmap.org via easy-to-use interfaces. This curated, high-resolution dataset serves as a powerful resource for biologists, clinicians and bioinformaticians interested in the developing urogenital system. This paper gives examples of how the data have been used to address problems in developmental biology and provides a primer for those wishing to use the database in their own research.