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GBA server: EST-based digital gene expression profiling.

Xin Wu1, Michael G Walker, Jingchu Luo

  • 1Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, P. R. China.

Nucleic Acids Research
|June 28, 2005
PubMed
Summary
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This study introduces the Guilt-by-Association (GBA) web server for large-scale co-expression analysis of genes. It helps discover functionally linked genes, aiding in identifying disease-related genes.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Expressed Sequence Tag (EST)-based gene expression profiling enables large-scale discovery of functionally associated genes.
  • Existing bioinformatics tools primarily focus on differential gene expression, not co-expression analysis.

Purpose of the Study:

  • To develop a web server for identifying co-expressed genes using the Guilt-by-Association (GBA) algorithm.
  • To address the gap in tools for large-scale co-expression analysis.

Main Methods:

  • Implementation of the Guilt-by-Association (GBA) co-expression algorithm.
  • Development of a web server for gene co-expression analysis.
  • Annotation of UniGene clusters with links to external databases (GO, KEGG, OMIM, Gene, IPI, HomoloGene).

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Main Results:

  • A novel web server implementing the GBA algorithm for co-expression analysis has been developed.
  • The server facilitates the discovery of functionally associated genes.
  • UniGene clusters are annotated with comprehensive database links.

Conclusions:

  • The GBA web server effectively identifies co-expressed genes, aiding in the discovery of disease-related genes.
  • This tool enhances large-scale gene expression profiling capabilities.
  • The server is accessible and downloadable for broader research use.