title: ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.
abstract: Biological pathways can provide key information on the organization of biological systems. ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data for integrated biological pathway resources using Scalable Vector Graphics (SVG). By integrating major bio-databases and searching pathway resources, ArrayXPath automatically maps different types of identifiers from microarray probes and pathway elements. When one inputs gene-expression clusters, ArrayXPath produces a list of the best matching pathways for each cluster. We applied Fisher's exact test and the false discovery rate (FDR) to evaluate the statistical significance of the association between a cluster and a pathway while correcting the multiple-comparison problem. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of pathways integrated with gene-expression profiles.
authors.affiliation: Seoul National University Biomedical Informatics, Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.
authors.forename: Hee-Joon
authors.initials: HJ
authors.lastname: Chung
authors.forename: Mingoo
authors.initials: M
authors.lastname: Kim
authors.forename: Chan Hee
authors.initials: CH
authors.lastname: Park
authors.forename: Jihoon
authors.initials: J
authors.lastname: Kim
authors.forename: Ju Han
authors.initials: JH
authors.lastname: Kim
mesh_terms: D016000:Cluster Analysis; D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis; D015398:Signal Transduction; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface