|Description||Bioinformatics resource for deciphering the genome.|
|Research center||Kyoto University|
|Primary citation||PMID 10592173|
|Web service URL||REST see KEGG API|
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a collection of databases dealing with genomes, biological pathways, diseases, drugs, and chemical substances. KEGG is utilized for bioinformatics research and education, including data analysis in genomics, metagenomics, metabolomics and other omics studies, modeling and simulation in systems biology, and translational research in drug development.
- Introduction 1
- Systems information 2.1
- Genomic information 2.2
- Chemical information 2.3
- Health information 2.4
- Subscription model 3
- See also 4
- References 5
- External links 6
The KEGG database project was initiated in 1995 by Minoru Kanehisa, Professor at the Institute for Chemical Research, genes in the genome to gene products (mostly proteins) in the pathway. This has enabled the analysis called KEGG pathway mapping, whereby the gene content in the genome is compared with the KEGG PATHWAY database to examine which pathways and associated functions are likely to be encoded in the genome.
According to the developers, KEGG is a "computer representation" of the biological system. It integrates building blocks and wiring diagrams of the system — more specifically, genetic building blocks of genes and proteins, chemical building blocks of small molecules and reactions, and wiring diagrams of molecular interaction and reaction networks. This concept is realized in the following databases of KEGG, which are categorized into systems, genomic, chemical, and health information.
- PATHWAY — pathway maps for cellular and organismal functions
- MODULE — modules or functional units of genes
- BRITE — hierarchical classifications of biological entities
- Genomic information
- Chemical information
- Health information
The KEGG PATHWAY database, the wiring diagram database, is the core of the KEGG resource. It is a collection of pathway maps integrating many entities including genes, proteins, RNAs, chemical compounds, glycans, and chemical reactions, as well as disease genes and drug targets, which are stored as individual entries in the other databases of KEGG. The pathway maps are classified into the following sections:
- Genetic information processing (transcription, translation, replication and repair, etc.)
- Environmental information processing (membrane transport, signal transduction, etc.)
- Cellular processes (cell growth, cell death, cell membrane functions, etc.)
- Organismal systems (immune system, endocrine system, nervous system, etc.)
- Human diseases
- Drug development
The metabolism section contains aesthetically drawn global maps showing an overall picture of metabolism, in addition to regular metabolic pathway maps. The low-resolution global maps can be used, for example, to compare metabolic capacities of different organisms in genomics studies and different environmental samples in metagenomics studies. In contrast, KEGG modules in the KEGG MODULE database are higher-resolution, localized wiring diagrams, representing tighter functional units within a pathway map, such as subpathways conserved among specific organism groups and molecular complexes. KEGG modules are defined as characteristic gene sets that can be linked to specific metabolic capacities and other phenotypic features, so that they can be used for automatic interpretation of genome and metagenome data.
Another database that supplements KEGG PATHWAY is the KEGG BRITE database. It is an ontology database containing hierarchical classifications of various entities including genes, proteins, organisms, diseases, drugs, and chemical compounds. While KEGG PATHWAY is limited to molecular interactions and reactions of these entities, KEGG BRITE incorporates many different types of relationships.
Several months after the KEGG project was initiated in 1995, the first report of the completely sequenced annotations in the form of establishing correspondences to the wiring diagrams of KEGG pathway maps, KEGG modules, and BRITE hierarchies.
These correspondences are made using the concept of genome annotation procedure in KEGG.
The KEGG metabolic pathway maps are drawn to represent the dual aspects of the metabolic network: the genomic network of how genome-encoded metabolites identified in the metabolome will lead to the understanding of enzymatic pathways and enzyme genes involved.
The databases in the chemical information category, which are collectively called KEGG LIGAND, are organized by capturing knowledge of the chemical network. In the beginning of the KEGG project, KEGG LIGAND consisted of three databases: KEGG COMPOUND for chemical compounds, KEGG REACTION for chemical reactions, and KEGG ENZYME for reactions in the enzyme nomenclature. Currently, there are additional databases: KEGG GLYCAN for glycans and two auxiliary reaction databases called RPAIR (reactant pair alignments) and RCLASS (reaction class). KEGG COMPOUND has also been expanded to contain various compounds such as xenobiotics, in addition to metabolites.
In KEGG, diseases are viewed as perturbed states of the biological system caused by perturbants of genetic factors and environmental factors, and drugs are viewed as different types of perturbants. The KEGG PATHWAY database includes not only the normal states but also the perturbed states of the biological systems. However, disease pathway maps cannot be drawn for most diseases because molecular mechanisms are not well understood. An alternative approach is taken in the KEGG DISEASE database, which simply catalogs known genetic factors and environmental factors of diseases. These catalogs may eventually lead to more complete wiring diagrams of diseases.
The KEGG DRUG database contains active ingredients of approved drugs in Japan, the USA, and Europe. They are distinguished by chemical structures and/or chemical components and associated with target molecules, metabolizing enzymes, and other molecular interaction network information in the KEGG pathway maps and the BRITE hierarchies. This enables an integrated analysis of drug interactions with genomic information. Crude drugs and other health-related substances, which are outside of the category of approved drugs, are stored in the KEGG ENVIRON database. The databases in the health information category are collectively called KEGG MEDICUS, which also includes package inserts of all marketed drugs in Japan.
In July 2011 KEGG introduced a subscription model for FTP download due to a significant cutback of government funding. KEGG continues to be freely available through its website, but the subscription model has raised discussions about sustainability of bioinformatics databases.
- Comparative Toxicogenomics Database - CTDintegrates KEGG pathways with toxicogenomic and disease data
- ConsensusPathDB, a molecular functional interaction database, integrating information from KEGG
- Gene ontology
- Gene Disease Database
- Kanehisa M, Goto S (2000). "KEGG: Kyoto Encyclopedia of Genes and Genomes". Nucleic Acids Res 28 (1): 27–30.
- Kanehisa M (1997). "A database for post-genome analysis". Trends Genet 13 (9): 375–6.
- Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M (2006). "From genomics to chemical genomics: new developments in KEGG". Nucleic Acids Res 34 (Database issue): D354–7.
- Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M (2014). "Data, information, knowledge and principle: back to metabolism in KEGG". Nucleic Acids Res 42 (Database issue): D199–205.
- Fleischmann RD, Adams MD, White O, Clayton RA, Kirkness EF, Kerlavage AR, Bult CJ, Tomb JF, Dougherty BA, Merrick JM; et al. (1995). "Whole-genome random sequencing and assembly of Haemophilus influenzae Rd". Science 269 (5223): 496–512.
- Kanehisa M (2013). "Chemical and genomic evolution of enzyme-catalyzed reaction networks". FEBS Lett 587 (17): 2731–7.
- Goto S, Nishioka T, Kanehisa M (1999). "LIGAND database for enzymes, compounds and reactions". Nucleic Acids Res 27 (1): 377–9.
- Hashimoto K, Goto S, Kawano S, Aoki-Kinoshita KF, Ueda N, Hamajima M, Kawasaki T, Kanehisa M (2006). "KEGG as a glycome informatics resource". Glycobiology 16 (5): 63R–70R.
- Muto A, Kotera M, Tokimatsu T, Nakagawa Z, Goto S, Kanehisa M (2013). "Modular architecture of metabolic pathways revealed by conserved sequences of reactions". J Chem Inf Model 53 (3): 613–22.
- Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010). "KEGG for representation and analysis of molecular networks involving diseases and drugs". Nucleic Acids Res 38 (Database issue): D355–60.
- Galperin MY, Fernández-Suárez XM (2012). "The 2012 Nucleic Acids Research Database Issue and the online Molecular Biology Database Collection". Nucleic Acids Res 40 (Database issue): D1–8.
- Hayden, EC. "Popular plant database set to charge users".
- KEGG website
- GenomeNet mirror site
- The entry for KEGG in MetaBase