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Genome Annotation and Assembly

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Related Experiment Video

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Representing annotation compositionality and provenance for the Semantic Web.

Kevin M Livingston1, Michael Bada1, Lawrence E Hunter1

  • 1Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Journal of Biomedical Semantics
|November 26, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new ontological model for detailed annotation provenance. It enables complex annotations to be built from simpler ones, improving data traceability and error tracking in digital artifacts.

Keywords:
AnnotationConceptual data modelingMarkupOWLOntologyProvenanceRDF

Related Experiment Videos

Last Updated: May 5, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

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Area of Science:

  • Computer Science
  • Information Science
  • Ontology Engineering

Background:

  • Traditional metadata annotation links single terms to single targets.
  • Expanding annotation complexity requires referencing atomic knowledge structures.
  • Current Semantic Web provenance tracks whole triples, lacking element-level detail.

Purpose of the Study:

  • To develop a flexible ontological model for capturing complex annotations and their provenance.
  • To enable annotations to link to singular concepts or complex knowledge representations.
  • To provide detailed provenance for compositional annotations.

Main Methods:

  • Developed a task- and domain-independent ontological model.
  • Implemented the model as an extension of the Information Artifact Ontology in OWL.
  • Demonstrated integration with existing annotation and provenance models.

Main Results:

  • The model captures annotations and their linkage to knowledge representations (concepts or assertions).
  • It allows provenance tracking at the annotation or individual RDF triple element level.
  • Successfully applied to linguistic annotation and genome sequence disease-association annotation.

Conclusions:

  • Enables progressive composition of complex annotations from simpler ones.
  • Facilitates evidence-based inference and error tracking through precise provenance recording.
  • Supports richer annotations by leveraging and detailing previous annotation efforts.