KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of online databases dealing with genomes, enzymatic pathways, and biological chemicals. The PATHWAY database records networks of molecular interactions in the cells, and variants of them specific to particular organisms.
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Introduction
The KEGG, the Kyoto Encyclopedia of Genes and Genomes, was initiated by the Japanese human genome programme in 1995[1]. According to the developers they consider KEGG to be a "computer representation" of the biological system[2]. The KEGG database can be utilized for modeling and simulation, browsing and retrieval of data. It is a part of the systems biology approach.
KEGG maintains five main databases [3]
- KEGG Atlas
- KEGG Pathway
- KEGG Genes
- KEGG Ligand
- KEGG BRITE
Databases
KEGG connects known information on molecular interaction networks, such as pathways and complexes (this is the Pathway Database), information about genes and proteins generated by genome projects (including the gene database) and information about biochemical compounds and reactions (including compound and reaction databases). These databases are different networks, known as the protein network, and the chemical universe respectively. There are efforts in progress to add to the knowledge of KEGG, including information regarding ortholog clusters in the KO (KEGG Orthology) database. [4]
KEGG Pathways:
- Metabolism
- Genetic Information Processing
- Environmental Information Processing
- Cellular Processes
- Human Diseases
- Drug development
Ligand Database:
- Compound
- Drug
- Glycan
- Reaction
- RPAIR (Reactant pair alignments)
- Enzyme
See also
- Comparative Toxicogenomics Database - CTD integrates KEGG pathways with toxicogenomic and disease data
- ConsensusPathDB, a molecular functional interaction database, integrating information from KEGG
- Uniprot
- Gene ontology
References
- ^ Minoru Kanehisa, "A database for post-genome analysis", Trends in Genetics Volume 13, Issue 9, September 1997, Pages 375-376
- ^ From genomics to chemical genomics:New development in KEGG.PubMed Link
- ^ Minoru Kanehisa, Susumu Goto, Shuichi Kawashima, Yasushi Okuno, and Masahiro Hattori. (2004). The KEGG Resource for Deciphering the Genome. In: Nucleic Acids Research, 32(1) Database Issue.
- ^ Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M., The KEGG resource for deciphering the genome, Nucleic Acids Res. 2004 Jan 1;32(Database issue):D277-80.
External links
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