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ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources

Hee-Joon Chung1, Mingoo Kim, Chan Hee Park

  • 1Seoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.

Nucleic Acids Research
|June 25, 2004
PubMed
Summary
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ArrayXPath is a web tool that maps gene expression data to biological pathways. It aids in understanding biological systems by visualizing gene expression profiles within pathway contexts.

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Biological pathways are crucial for understanding biological system organization.
  • Microarray gene expression data analysis requires effective tools for pathway integration.

Purpose of the Study:

  • To introduce ArrayXPath, a web-based service for mapping and visualizing gene expression data within biological pathways.
  • To enable interactive visualization of gene expression profiles integrated with pathway resources.

Main Methods:

  • ArrayXPath integrates major bio-databases and pathway resources.
  • It automatically maps identifiers from microarray probes and pathway elements.
  • Statistical significance is assessed using Fisher's exact test and false discovery rate (FDR).

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Main Results:

  • ArrayXPath maps gene expression clusters to relevant biological pathways.
  • It generates a ranked list of matching pathways for each input cluster.
  • The service produces Javascript-enabled Scalable Vector Graphics (SVG) for interactive visualization.

Conclusions:

  • ArrayXPath facilitates the interpretation of gene expression data by linking it to biological pathways.
  • The tool enhances biological systems analysis through integrated visualization.
  • It provides a statistically robust method for identifying pathway-gene expression associations.