ArticleJournal of biomedical semantics2017
NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.
Article in Journal of biomedical semantics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- I-ETL: an interoperability-aware health (meta)data pipeline to enable federated analyses.BMC medical informatics and decision making · 2025Article
- Creating an Interactive Web Interface for Networks Stored in Knowledge Graph Databases.Current protocols · 2025Article
- Pisces: A multi-modal data augmentation approach for drug combination synergy prediction.Cell genomics · 2025Article
- BioPortal: an open community resource for sharing, searching, and utilizing biomedical ontologies.Nucleic acids research · 2025Article
- Pheno-Ranker: a toolkit for comparison of phenotypic data stored in GA4GH standards and beyond.BMC bioinformatics · 2024Article
- Zebrafish reveal new roles for Fam83f in hatching and the DNA damage-mediated autophagic response.Open biology · 2024Article
- Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT.Patterns (New York, N.Y.) · 2024Article
- Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT.ArXiv · 2023Article
- Processing genome-wide association studies within a repository of heterogeneous genomic datasets.BMC genomic data · 2023Article
- Knowledge Graph Embeddings for ICU readmission prediction.BMC medical informatics and decision making · 2023Article
- GenomicKB: a knowledge graph for the human genome.Nucleic acids research · 2023Article
- [Ontologies Applied in Clinical Decision Support Systems for Diabetes].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023Review
- PPIntegrator: semantic integrative system for protein-protein interaction and application for host-pathogen datasets.Bioinformatics advances · 2023Article
- A genetic map of the chromatin regulators to drug response in cancer cells.Journal of translational medicine · 2022Article
- Performance assessment of ontology matching systems for FAIR data.Journal of biomedical semantics · 2022Article
- The Sickle Cell Disease Ontology: recent development and expansion of the universal sickle cell knowledge representation.Database : the journal of biological databases and curation · 2022Article
- A biomedical open knowledge network harnesses the power of AI to understand deep human biology.AI magazine · 2022Article
- TrendyGenes, a computational pipeline for the detection of literature trends in academia and drug discovery.Scientific reports · 2021Article
- Lantern: an integrative repository of functional annotations for lncRNAs in the human genome.BMC bioinformatics · 2021Article
- A Second Look at FAIR in Proteomic Investigations.Journal of proteome research · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundOntologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms.
methodsWe developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data.
resultsOur evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios.
conclusionsOntology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available (both via the user interface at http://bioportal.bioontology.org/recommender , and via a Web service API).
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.