Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Relations in biomedical ontologies.

Barry Smith1, Werner Ceusters, Bert Klagges

  • 1Institute for Formal Ontology and Medical Information Science, Saarland University, D-66041 Saarbrücken, Germany. phismith@buffalo.edu

Genome Biology
|May 17, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Genomic polymorphism in North-western Indian population based on autosomal STR's: a population data study.

International journal of legal medicine·2020
Same author

Baseline Disease Activity and Steroid Therapy Stratify Risk of COVID-19 in Patients With Inflammatory Bowel Disease.

Gastroenterology·2020
Same author

Effect of yoga as add-on therapy in migraine (CONTAIN): A randomized clinical trial.

Neurology·2020
Same author

Defining the phenotype, pathogenesis and treatment of Crohn's disease associated spondyloarthritis.

Journal of gastroenterology·2020
Same author

Treatment in Disproportionately Minority Hospitals Is Associated With Increased Risk of Mortality in Sepsis: A National Analysis.

Critical care medicine·2020
Same author

Spatial genetic structure of black francolin (<i>Francolinus francolinus asiae</i>) in the North-Western Himalayan region based on mitochondrial control region.

Mitochondrial DNA. Part A, DNA mapping, sequencing, and analysis·2020
Same journal

Integrated lipidomic and transcriptomic profiling of the host response in human malaria.

Genome biology·2026
Same journal

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026
Same journal

Mapping the landscape of allele-specific expression in porcine genomes.

Genome biology·2026
Same journal

Genomic sequence evolution underlying human neocortical interareal diversification.

Genome biology·2026
Same journal

Regulatory mechanisms driven by functional 3'-UTR variants in alcohol use disorder and related traits.

Genome biology·2026
Same journal

A longitudinal single-nucleus transcriptomic atlas of bovine placentation reveals dynamic cellular hierarchies and regulatory programs.

Genome biology·2026
See all related articles

This study introduces a new methodology for defining relations in biomedical ontologies, improving consistency and reducing errors. The developed Relation Ontology enhances interoperability and enables advanced reasoning for biological and medical data.

Area of Science:

  • Biomedical Informatics
  • Ontology Engineering
  • Computational Biology

Background:

  • Biomedical ontologies are crucial for organizing complex biological and medical data.
  • Current methods for defining relations in ontologies can lead to inconsistencies and errors.
  • Lack of standardized relational definitions hinders ontology interoperability and advanced reasoning.

Purpose of the Study:

  • To develop a methodology for consistent and unambiguous formal definitions of relational expressions in biomedical ontologies.
  • To create a Relation Ontology that assists developers and users in avoiding coding and annotation errors.
  • To promote interoperability among biomedical ontologies and support automated reasoning.

Main Methods:

  • A novel methodology for formalizing relational expressions was advanced.

Related Experiment Videos

  • The methodology focuses on providing clear and consistent definitions for ontology relations.
  • The developed Relation Ontology serves as a standardized resource.

    • Main Results:

    • The methodology ensures consistent and unambiguous formal definitions of relational expressions.
    • The Relation Ontology facilitates error avoidance in coding and annotation.
    • Enhanced interoperability of ontologies is achieved through standardized relations.

    Conclusions:

    • The proposed methodology and Relation Ontology significantly enhance the treatment of relations in biomedical ontologies.
    • This approach supports improved accuracy in data coding and annotation.
    • The Relation Ontology is foundational for advanced automated reasoning on biological and medical data, particularly spatial and temporal aspects.