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ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.

Hee-Joon Chung·Chan Hee Park·Mi Ryung Han·Seokho Lee·Jung Hun Ohn·Jihoon Kim·Jihun Kim·Ju Han Kim
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Abstract

SUMMARY: ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics (SVG). Deciphering the crosstalk among pathways and integrating biomedical ontologies and knowledge bases may help biological interpretation of microarray data. ArrayXPath is empowered by integrating gene-pathway, disease-pathway, drug-pathway and pathway-pathway correlations with integrated Gene Ontology, Medical Subject Headings and OMIM Morbid Map-based annotations. We applied Fisher's exact test and relative risk to evaluate the statistical significance of the correlations. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of gene-expression profiles integrated with gene-pathway-disease interactions enriched by biomedical ontologies.

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Cluster AnalysisComputer GraphicsDatabases, GeneticGene Expression ProfilingGenetic Predisposition to DiseaseInternetMedical Subject HeadingsOligonucleotide Array Sequence AnalysisSoftwareSystems IntegrationUser-Computer InterfaceJournal ArticleResearch Support, Non-U.S. Gov't

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BibTeXRIS

Hee-Joon Chung, Chan Hee Park, Mi Ryung Han, Seokho Lee, Jung Hun Ohn, Jihoon Kim, Jihun Kim, Ju Han Kim. 2005-07-01. ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.. https://doi.org/10.1093/nar%2Fgki450

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