ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.
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.
Chung
Hee-Joon
HJ
Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Korea.
Park
Chan Hee
CH
Han
Mi Ryung
MR
Lee
Seokho
S
Ohn
Jung Hun
JH
Kim
Jihoon
J
Kim
Jihun
J
Kim
Ju Han
JH
D016000:Cluster Analysis; D003196:Computer Graphics; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D020022:Genetic Predisposition to Disease; D020407:Internet; D046650:Medical Subject Headings; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface