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Related Experiment Videos

Genesis: cluster analysis of microarray data.

Alexander Sturn1, John Quackenbush, Zlatko Trajanoski

  • 1Institute of Biomedical Engineering, Graz University of Technology, Krenngasse 37, 8010 Graz, Austria.

Bioinformatics (Oxford, England)
|February 12, 2002
PubMed
Summary
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Genesis is a Java software suite for analyzing gene expression data from microarrays. It offers various tools for data processing, clustering, and visualization, aiding in promoter analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Large-scale gene expression analysis is crucial for understanding biological processes.
  • Existing tools may lack versatility or platform independence.
  • Microarray data analysis requires robust computational methods.

Purpose of the Study:

  • To develop a versatile, platform-independent Java suite for large-scale gene expression analysis.
  • To integrate diverse tools for comprehensive microarray data analysis.
  • To facilitate promoter analysis and transcriptional control investigations.

Main Methods:

  • Development of the Genesis Java suite.
  • Integration of data filtering, normalization, and visualization tools.
  • Implementation of clustering algorithms: hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines.

Related Experiment Videos

  • Mapping of gene expression data onto chromosomal sequences.

    • Main Results:

    • Genesis provides a transparent and integrated environment for gene expression data analysis.
    • The suite supports multiple clustering algorithms, allowing comparative analysis.
    • Gene expression data can be mapped to chromosomal sequences for enhanced promoter analysis.

    Conclusions:

    • Genesis offers a user-friendly, versatile platform for large-scale gene expression analysis.
    • The integrated approach facilitates the investigation of transcriptional regulation.
    • The software enhances the analysis of microarray data through diverse computational tools.