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Related Experiment Videos

GIMS: an integrated data storage and analysis environment for genomic and functional data.

Michael Cornell1, Norman W Paton, Cornelia Hedeler

  • 1Department of Computer Science, University of Manchester, Manchester M13 9PL, UK.

Yeast (Chichester, England)
|November 18, 2003
PubMed
Summary

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The Genome Information Management System (GIMS) integrates diverse biological data for functional genomics analysis. This system aids researchers by enabling complex queries across genomic, transcriptomic, and protein interaction data.

Area of Science:

  • Functional genomics
  • Bioinformatics
  • Systems biology

Background:

  • Functional genomics analyses require integrated biological data (e.g., gene expression, protein interactions, pathways).
  • Data is often siloed in disparate formats and locations, hindering integrated analysis.
  • Existing systems lack comprehensive facilities for handling and interrelating diverse biological datasets.

Purpose of the Study:

  • To develop and present the Genome Information Management System (GIMS) for integrated biological data management.
  • To demonstrate the utility of GIMS in facilitating complex analyses in functional genomics.

Main Methods:

  • Developed GIMS as an object database integrating genomic, transcriptomic, protein-protein interaction, metabolic pathway, and annotation data.

Related Experiment Videos

  • Implemented comprehensive facilities for handling and interrelating analysis results.
  • Utilized complex queries to analyze integrated data, including Saccharomyces cerevisiae data.

    • Main Results:

    • GIMS successfully integrates diverse biological data types, including gene ontology terms.
    • Demonstrated the benefit of integrated data storage for analysis through complex queries.
    • Successfully used GIMS to analyze a collection of aryl alcohol dehydrogenase gene deletion mutants.

    Conclusions:

    • Integrated storage of diverse biological data in GIMS enhances functional genomics analysis.
    • GIMS provides a valuable resource for researchers needing to query and analyze complex biological datasets.
    • The GIMS database is accessible remotely via a downloadable Java application.