English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Biomedical researchers use ontologies to annotate their data with ontologyterms, enabling better data integration and interoperability. However, thenumber, variety and complexity of current biomedical ontologies make itcumbersome for researchers to determine which ones to reuse for their specificneeds. To overcome this problem, in 2010 the National Center for BiomedicalOntology (NCBO) released the Ontology Recommender, which is a service thatreceives a biomedical text corpus or a list of keywords and suggests ontologiesappropriate for referencing the indicated terms. We developed a new version ofthe NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a newrecommendation approach that evaluates the relevance of an ontology tobiomedical text data according to four criteria: (1) the extent to which theontology covers the input data; (2) the acceptance of the ontology in thebiomedical community; (3) the level of detail of the ontology classes thatcover the input data; and (4) the specialization of the ontology to the domainof the input data. Our evaluation shows that the enhanced recommender provideshigher quality suggestions than the original approach, providing bettercoverage of the input data, more detailed information about their concepts,increased specialization for the domain of the input data, and greateracceptance and use in the community. In addition, it provides users with moreexplanatory information, along with suggestions of not only individualontologies but also groups of ontologies. It also can be customized to fit theneeds of different scenarios. Ontology Recommender 2.0 combines the strengthsof its predecessor with a range of adjustments and new features that improveits reliability and usefulness. Ontology Recommender 2.0 recommends over 500biomedical ontologies from the NCBO BioPortal platform, where it is openlyavailable.

NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation