KEGG Atlas mapping for global analysis of metabolic pathways

By Shujiro Okuda, Takuji Yamada, Masami Hamajima, Masumi Itoh, Toshiaki Katayama, Peer Bork, Susumu Goto, Minoru Kanehisa. Nucleic Acids Res., 2008

501 citations recorded by the source corpus.

KEGG Atlas is a new graphical interface to the KEGG suite of databases, especially to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an associated viewer for metabolism, covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technology. The mapping of high-throughput experimental data onto the global map is the main use of KEGG Atlas. In the global metabolism map, the node (circle) is a chemical compound and the edge (line) is a set of reactions linked to a set of KEGG Orthology (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K number identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chemical compounds are converted to the C number identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/fc3036810247cd3c2aec46d7126c1dad000b80dc

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Citations in the corpus

Data Mining Techniques for the Life Sciences (2010, methodology): “Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., Yamanishi Y. (2008) KEGG for linking genomes to life and the environment.”
Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks (2010, background): “The first one was directly taken from KEGG (ID: hsa04330) (Figure 3A), which is probably the most complete, well-integrated, and annotated database of biological pathways [33,34].”
Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology (2010, methodology): “Development, visualization and web publishing of organism-specific DBs Metabolic pathway information Other software systems for managing metabolic pathway information are KEGG [89, 90], PUMA2 [91] (inactive), Amaze [92] (inactive), GenMAPP [93, 94], PathCase [95, 96], VisANT [97], and Reactome [98–1”
SMPDB: The Small Molecule Pathway Database (2009, background): “To check that the pathway illustrations (especially for metabolic and small molecule signaling pathways) were as correct and as comprehensive as possible, the SMPDB pathway artists and annotators were also required to consult a variety of sources including biochemistry textbooks, the Boerhinger–Manh”
A Parsimony Approach to Biological Pathway Reconstruction/Inference for Genomes and Metagenomes (2009, background): “The partition of pathways (as the entire cellular network is partitioned into several hundreds of biological pathway entities in KEGG database) is extremely important for understanding of biological processes, even though there is only a single large biological network within any cell and all pathwa”
PathVisio 3: An Extendable Pathway Analysis Toolbox (2015, methodology): “A feature comparison table with other tools like Vanted [16], ProMeTra [17], KEGG Atlas [18] or Ingenuity [19] is available in S1 Table.”
iPath2.0: interactive pathway explorer (2011, methodology): “The KEGG database provides hand-curated pathway diagrams, and recently made their overview pathway diagram for metabolism publicly available in SVG (scalable vector graphics) format (3,4).”
miRTarBase: a database curates experimentally validated microRNA–target interactions (2010, methodology): “This work also examines the functions of these target genes involved in human MTIs collected in the database by performing gene ontology (GO) and KEGG (19) pathway enrichment annotation using the DAVID gene annotation scheme (20).”