Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies.

BMC bioinformatics - 9 Oct 2007

Hoehndorf Robert, Loebe Frank, Kelso Janet, Herre Heinrich

Abstract excerpt

BACKGROUND: Current efforts within the biomedical ontology community focus on achieving interoperability between various biomedical ontologies that cover a range of diverse domains. Achieving this interoperability will contribute to the creation of a rich knowledge base that can be used for querying, as well as generating and testing novel hypotheses. The OBO Foundry principles, as applied to a number of...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Artificial Intelligence
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Natural Language Processing

Share to Reproducibility of Results

Share to Semantics

Share to Software

Share to Vocabulary, Controlled

Source

Open in PubMed Open full text

Identifiers

PMID: 17925014
DOI: 10.1186/1471-2105-8-377
PMCID: PMC2180186

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Representing default knowledge in biomedical ontologies: application to the integration of anatomy and phenotype ontologies.PMID 17925014Read ↗

Integrating phenotype ontologies with PhenomeNET.Semantic proximity Read ↗

Integrating phenotype ontologies across multiple species.Semantic proximity Read ↗

Interoperability between phenotype and anatomy ontologies.Semantic proximity Read ↗

The Xenopus Phenotype Ontology: bridging model organism phenotype data to human health and developmentSemantic proximity Read ↗

Using ontologies to describe mouse phenotypes.Semantic proximity Read ↗

Analysis of Causal Relationships in Integrated Ontologies of Diseases, Phenotypes, and Radiological Diagnosis.Semantic proximity Read ↗

The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development.Semantic proximity Read ↗

Methodology for the inference of gene function from phenotype data.Semantic proximity Read ↗

k-BOOM: A Bayesian approach to ontology structure inference, with applications in disease ontology constructionSemantic proximity Read ↗

Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.Semantic proximity Read ↗

Investigating the importance of anatomical homology for cross-species phenotype comparisons using semantic similaritySemantic proximity Read ↗

Mouse, man, and meaning: bridging the semantics of mouse phenotype and human disease.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.