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Related Experiment Videos

RESOURCERER: a database for annotating and linking microarray resources within and across species.

J Tsai1, R Sultana, Y Lee

  • 1The Institute for Genomic Research, Rockville, MD 20850, USA

Genome Biology
|September 22, 2005
PubMed
Summary
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Microarray expression analysis generates vast gene expression data. RESOURCERER is a new database that helps cross-reference this data across species and platforms for better disease insights.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Microarray expression analysis yields extensive gene expression data in humans and mammals.
  • Integrating data across species and platforms is a significant challenge for understanding gene expression and disease.
  • Existing databases lack comprehensive cross-referencing capabilities for diverse microarray data.

Purpose of the Study:

  • To develop a robust database for annotating and cross-referencing microarray resources.
  • To facilitate the integration of gene expression data from different species and experimental platforms.
  • To enhance the derivation of inferences regarding gene expression and disease states.

Main Methods:

  • Development of RESOURCERER, a novel microarray-resource annotation and cross-reference database.

Related Experiment Videos

  • Utilized expressed sequence tags (ESTs) and gene sequences from TIGR Gene Index (TGI).
  • Incorporated data from TIGR Orthologous Gene Alignment (TOGA) database, now Eukaryotic Gene Orthologs (EGO).

    • Main Results:

    • RESORCERER provides a centralized resource for microarray data annotation.
    • The database enables effective cross-referencing of gene expression data across species.
    • Facilitates comparative analysis of gene expression patterns and their relation to disease.

    Conclusions:

    • RESORCERER addresses the challenge of integrating diverse microarray expression data.
    • The database enhances the utility of genomic resources for biomedical research.
    • Enables more robust inferences about gene expression and disease states through cross-species data integration.