Concepedia

KEGG for linking genomes to life and the environment

Minoru Kanehisa, Michihiro Araki, Susumu Goto, Masahiro Hattori, Mika Hirakawa, Masumi Itoh, Tsutomu Katayama, Shuichi Kawashima, Shujiro Okuda, Toshiaki Tokimatsu,

Nucleic Acids Research · 2007 · 6.9K citations · 8 references

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TL;DR

KEGG is a comprehensive database that integrates genomic, chemical, and systemic functional information to link genomes to biological life and environmental contexts through pathway and BRITE mapping. The authors aim to expand KEGG to meet practical application needs. KEGG expands its data architecture by adding a global metabolic pathway map, modular pathway components, a drug database of US and Japanese approvals, and a disease database linking genes, pathways, drugs, and diagnostic markers.

Abstract

KEGG ( http://www.genome.jp/kegg/ ) is a database of biological systems that integrates genomic, chemical and systemic functional information. KEGG provides a reference knowledge base for linking genomes to life through the process of PATHWAY mapping, which is to map, for example, a genomic or transcriptomic content of genes to KEGG reference pathways to infer systemic behaviors of the cell or the organism. In addition, KEGG provides a reference knowledge base for linking genomes to the environment, such as for the analysis of drug-target relationships, through the process of BRITE mapping. KEGG BRITE is an ontology database representing functional hierarchies of various biological objects, including molecules, cells, organisms, diseases and drugs, as well as relationships among them. KEGG PATHWAY is now supplemented with a new global map of metabolic pathways, which is essentially a combined map of about 120 existing pathway maps. In addition, smaller pathway modules are defined and stored in KEGG MODULE that also contains other functional units and complexes. The KEGG resource is being expanded to suit the needs for practical applications. KEGG DRUG contains all approved drugs in the US and Japan, and KEGG DISEASE is a new database linking disease genes, pathways, drugs and diagnostic markers.

References

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KAAS: an automatic genome annotation and pathway reconstruction server

Yuki Moriya, Masumi Itoh, Shujiro Okuda et al. · Nucleic Acids Research · 2007

4.2K citations

Computational Assignment of the EC Numbers for Genomic-Scale Analysis of Enzymatic Reactions

Masaaki Kotera, Yasushi Okuno, Masahiro Hattori et al. · Journal of the American Chemical Society · 2004

+24

153 citations