Name
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/. |
Year | Venue | Field |
|---|---|---|
2005 | In Silico Biology | Metabolome,Data mining,Biology,Visualization,Systems biology,KEGG,Proteome,Software,Bioinformatics,Computational biology,Computer graphics,Scalability |
DocType | Volume | Issue |
Journal | 5 | 4 |
ISSN | Citations | PageRank |
1386-6338 | 12 | 1.28 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuharu Arakawa | 1 | 120 | 10.46 |
| Nobuaki Kono | 2 | 34 | 3.61 |
| Yohei Yamada | 3 | 56 | 5.82 |
| H Mori | 4 | 22 | 3.67 |
| Masaru Tomita | 5 | 1009 | 180.20 |