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An object model and database for functional genomics.

Andrew Jones1, Ela Hunt, Jonathan M Wastling

  • 1Department of Computing Science, University of Glasgow, Glasgow, UK. jonesa@dcs.gla.ac.uk

Bioinformatics (Oxford, England)
|May 18, 2004
PubMed
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A new Functional Genomics Experiment Object Model (FGE-OM) unifies data standards for microarrays and proteomics. This model supports the RNA And Protein Abundance Database (RAPAD), enabling better data sharing and analysis in functional genomics.

Area of Science:

  • Genomics
  • Proteomics
  • Bioinformatics

Background:

  • Large-scale functional genomics generates complex data requiring standardized analysis, storage, and querying.
  • Existing standards like MAGE-ML for microarrays and PEDRo for proteomics highlight the need for unified data formats.
  • Consistent annotation across diverse functional genomics experiments is crucial for data sharing and comparative analysis.

Purpose of the Study:

  • To develop a unified data model for functional genomics experiments.
  • To facilitate the creation of public data repositories and improve data interoperability.
  • To enable novel comparisons across multiple functional genomics datasets.

Main Methods:

  • Development of a Functional Genomics Experiment Object Model (FGE-OM) based on existing microarray and proteomics models.

Related Experiment Videos

  • Implementation of FGE-OM into a prototype database named RNA And Protein Abundance Database (RAPAD).
  • Population of RAPAD with data from microbial pathogenesis experiments.

    • Main Results:

    • Creation of FGE-OM, integrating common, microarray-specific, and proteomics-specific components.
    • Successful implementation and population of the RAPAD database using the FGE-OM schema.
    • Demonstration of a unified approach for annotating and managing functional genomics data.

    Conclusions:

    • FGE-OM provides a consistent framework for functional genomics data annotation.
    • The RAPAD database, built on FGE-OM, supports integrated analysis of diverse genomics and proteomics data.
    • FGE-OM is proposed to guide future development of MAGE and proteomics standards.