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Related Experiment Videos

New challenges in gene expression data analysis and the extended GEPAS.

Javier Herrero1, Juan M Vaquerizas, Fátima Al-Shahrour

  • 1Bioinformatics Unit, Biotechnology Programme, Centro Nacional de Investigaciones Oncológicas, Melchor Fernández Almagro, 3, E-28029 Madrid, Spain.

Nucleic Acids Research
|June 25, 2004
PubMed
Summary

GEPAS is a web-based pipeline for analyzing microarray gene expression data. It has evolved to address new challenges, including differential expression analysis and integrating genomic data with biological information.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray technology has evolved significantly since the late nineties.
  • Initial focus was on co-expression analysis using clustering techniques.
  • Recent advancements include differential expression analysis, clinical outcome correlation, and predictor building.

Purpose of the Study:

  • To present GEPAS, a web-based pipeline for microarray gene expression data analysis.
  • To address the increasing complexity and diversification of questions in microarray data analysis.
  • To integrate genomic data, such as CGH arrays, with expression data for chromosomal mapping.

Main Methods:

  • GEPAS offers a pipeline for analyzing microarray gene expression data.
  • It incorporates methods for differential expression analysis.

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  • The system supports the integration of genomic data and biological annotations.

    • Main Results:

    • GEPAS has evolved to meet new challenges in microarray data analysis.
    • It provides tools for analyzing differential gene expression and correlating with clinical outcomes.
    • The pipeline facilitates the mapping of expression and genomic data onto chromosomes.

    Conclusions:

    • GEPAS is a valuable resource for researchers analyzing complex microarray data.
    • It supports advanced analyses beyond traditional clustering methods.
    • The pipeline aids in transferring biological information to experimental results.