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ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated

Hee-Joon Chung1, Chan Hee Park, Mi Ryung Han

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

Nucleic Acids Research
|June 28, 2005
PubMed
Summary

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This summary is machine-generated.

ArrayXPath is a web tool that maps and visualizes gene expression data, integrating biological pathways and ontologies for enhanced interpretation. It aids in understanding gene-pathway-disease interactions through interactive visualizations.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray gene-expression data analysis requires sophisticated tools for interpretation.
  • Integrating biological pathways and biomedical ontologies can improve understanding of complex gene interactions.
  • Existing tools may lack comprehensive integration of diverse biological knowledge bases.

Purpose of the Study:

  • To develop ArrayXPath, a web-based service for mapping and visualizing gene-expression data.
  • To integrate biological pathway resources and biomedical ontologies for enhanced data interpretation.
  • To facilitate the deciphering of crosstalk among biological pathways and gene-pathway-disease interactions.

Main Methods:

  • Developed a web-based service utilizing Scalable Vector Graphics (SVG) for visualization.

Related Experiment Videos

  • Integrated gene-pathway, disease-pathway, drug-pathway, and pathway-pathway correlations.
  • Incorporated annotations from Gene Ontology, Medical Subject Headings (MeSH), and OMIM Morbid Map.
  • Applied Fisher's exact test and relative risk for statistical evaluation of correlations.

    • Main Results:

    • ArrayXPath provides interactive, Javascript-enabled SVG visualizations.
    • The service integrates gene-expression profiles with gene-pathway-disease interactions.
    • It leverages multiple biomedical ontologies and knowledge bases for enriched analysis.

    Conclusions:

    • ArrayXPath offers a powerful platform for visualizing and interpreting microarray gene-expression data.
    • The integration of pathway information and ontologies enhances biological insights.
    • The tool facilitates understanding of complex biological networks and disease associations.