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Related Experiment Videos

MADGE: scalable distributed data management software for cDNA microarrays.

Richard A McIndoe1, Aaron Lanzen, Kimberly Hurtz

  • 1Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville 32610, USA. rmcindoe@mail.mcg.edu

Bioinformatics (Oxford, England)
|December 25, 2002
PubMed
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A new software package manages complex data from cDNA microarray experiments, improving data access, analysis, and troubleshooting for researchers. This tool supports efficient disease mechanism studies and therapy evaluation.

Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology
  • Biotechnology

Background:

  • High-throughput technologies, including gene expression profiling via nucleic acid microarrays, offer significant opportunities for disease research.
  • In-house production of cDNA microarrays provides flexibility but generates vast amounts of data requiring effective management.
  • Efficient data management is crucial for accessing, analyzing, and evaluating microarray experiments.

Purpose of the Study:

  • To develop a software package for comprehensive data management in cDNA microarray facilities.
  • To facilitate efficient tracking and storage of diverse experimental data.
  • To support researchers in managing and analyzing large-scale gene expression data.

Main Methods:

  • Development of a distributable software package using a 3-tier client-server model.

Related Experiment Videos

  • Implementation of a relational database system for high transaction support in the data access layer.
  • Creation of a distributed COM server for the data services layer and an internet-based user interface for the application layer.

    • Main Results:

    • The software package effectively tracks and stores clone collection, annotation, workflow, microarray, and sample submission data.
    • The 3-tier architecture ensures robust data management and dynamic user interaction.
    • The system is designed to handle the large volume of information generated by cDNA microarray facilities.

    Conclusions:

    • The developed software provides essential data management capabilities for cDNA microarray facilities.
    • This tool enhances the efficiency of accessing, analyzing, and troubleshooting microarray experiments.
    • The software is freely available to academic and non-profit institutions, promoting wider research application.