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Related Experiment Videos

GEPAS: A web-based resource for microarray gene expression data analysis.

Javier Herrero1, Fátima Al-Shahrour, Ramón Díaz-Uriarte

  • 1Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas, c/Melchor Fernández Almagro 3, 28029, Madrid, Spain.

Nucleic Acids Research
|June 26, 2003
PubMed
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We developed Gene Expression Profile Analysis Suite (GEPAS), a web-based pipeline for analyzing microarray gene expression data. GEPAS offers tools for pre-processing, clustering, differential expression analysis, and data mining, aiding biological research.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray analysis is crucial for understanding gene expression patterns.
  • Existing tools may lack comprehensive functionalities or user-friendliness.

Purpose of the Study:

  • To present Gene Expression Profile Analysis Suite (GEPAS), a web-based pipeline for comprehensive microarray gene expression profile analysis.
  • To provide an integrated platform for various stages of gene expression data analysis.

Main Methods:

  • Development of a web-based pipeline integrating multiple analysis modules.
  • Inclusion of tools for data pre-processing, two-condition comparison, and both unsupervised and supervised clustering.
  • Implementation of differential gene expression tests and survival analysis.

Related Experiment Videos

  • Integration of a Gene Ontology-based data mining tool for result interpretation.

    • Main Results:

    • GEPAS offers a suite of interconnected modules for robust gene expression data analysis.
    • The pipeline supports popular and novel algorithms for clustering and differential expression analysis.
    • Integrated Gene Ontology analysis facilitates the interpretation of clustering results.

    Conclusions:

    • GEPAS provides a convenient and powerful web-based solution for microarray gene expression analysis.
    • The integrated approach simplifies complex data mining and interpretation workflows.
    • On-line tutorials enhance accessibility and user adoption.