KEGG-based pathway visualization tool for complex omics data

Kazuharu Arakawa, Nobuaki Kono, Yohei Yamada, Hirotada Mori, Masaru Tomita

Research output: Contribution to journalArticle

67 Citations (Scopus)

Abstract

Pathway-level visualization of omics data provides an essential means for systems biology, to capture the systematic properties of the inner activities of cells. Here we describe a web-based resource consisting of a web-application for the visualization of complex omics data onto KEGG pathways to overview all entities in the context of cellular pathways, and databases created with the software to visualize a series of microarray data. The web-application accepts transcriptome, proteome, metabolome, or the combination of these data as input, and because of this scalability it is advantageous for the visualization of cell simulation results. The web server can be accessed at http://www.g-language.org/data/marray/.

Original languageEnglish
Pages (from-to)419-423
Number of pages5
JournalIn Silico Biology
Volume5
Issue number4
Publication statusPublished - 2005

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Pathway
Visualization
Systems Biology
Metabolome
Proteome
Web Application
Transcriptome
Language
Software
Databases
Microarrays
Scalability
Cell
Web Server
Servers
Microarray Data
Cells
Web-based
Proteins
Resources

Keywords

  • KEGG
  • Metabolome
  • Microarray
  • Pathway visualization
  • Systems biology
  • Transcriptome

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Cite this

KEGG-based pathway visualization tool for complex omics data. / Arakawa, Kazuharu; Kono, Nobuaki; Yamada, Yohei; Mori, Hirotada; Tomita, Masaru.

In: In Silico Biology, Vol. 5, No. 4, 2005, p. 419-423.

Research output: Contribution to journalArticle

Arakawa, K, Kono, N, Yamada, Y, Mori, H & Tomita, M 2005, 'KEGG-based pathway visualization tool for complex omics data', In Silico Biology, vol. 5, no. 4, pp. 419-423.
Arakawa, Kazuharu ; Kono, Nobuaki ; Yamada, Yohei ; Mori, Hirotada ; Tomita, Masaru. / KEGG-based pathway visualization tool for complex omics data. In: In Silico Biology. 2005 ; Vol. 5, No. 4. pp. 419-423.
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