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Related Experiment Videos

Annotation and query of tissue microarray data using the NCI Thesaurus.

Nigam H Shah1, Daniel L Rubin, Inigo Espinosa

  • 1Stanford Medical Informatics, School of Medicine, Stanford University, Stanford, CA 94305, USA. nigam@stanford.edu

BMC Bioinformatics
|August 10, 2007
PubMed
Summary
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Mapping free-text pathological diagnoses from the Stanford Tissue Microarray Database (TMAD) to the National Cancer Institute Thesaurus (NCI-T) enables data integration. This approach successfully annotates 86% of samples, facilitating advanced querying of tissue microarray data.

Area of Science:

  • Bioinformatics
  • Pathology
  • Data Science

Background:

  • The Stanford Tissue Microarray Database (TMAD) contains free-text pathological diagnoses for tissue samples.
  • Current annotations lack a standardized ontology, hindering data integration with other biological and clinical resources.

Purpose of the Study:

  • To develop methods for mapping TMAD's free-text annotations to a standardized ontology.
  • To enable ontology-driven integration and querying of tissue microarray data.

Main Methods:

  • Developed methods to map free-text pathological diagnoses to the National Cancer Institute Thesaurus (NCI-T).
  • Applied mapping techniques to the Stanford Tissue Microarray Database (TMAD).

Main Results:

Related Experiment Videos

  • Successfully mapped annotations for approximately 86% of samples in TMAD to the NCI-T.
  • Demonstrated ontology-driven integration and querying capabilities for tissue microarray data.
  • Deployed mapping and querying tools on the TMAD website for public use.

    • Conclusions:

    • The NCI Thesaurus provides broad coverage for mapping TMAD annotations.
    • Ontology-based mapping facilitates the integration of TMAD with other biological data resources.
    • The developed tools enhance the utility and accessibility of tissue microarray data.