KEGG Database

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a database resource that integrates genomic, chemical and systemic functional information. In particular, gene catalogs from completely sequenced genomes are linked to higher-level systemic functions of the cell, the organism and the ecosystem.

Major efforts have been undertaken to manually create a knowledge base for such systemic functions by capturing and organizing experimental knowledge in computable forms; namely, in the forms of molecular networks called KEGG pathway maps, BRITE functional hierarchies and KEGG modules. Continuous efforts have also been made to develop and improve the cross-species annotation procedure for linking genomes to the molecular networks through the KEGG Orthology (KO) system.

As the result, KEGG is widely used as a reference knowledge base for integration and interpretation of large-scale datasets generated by genome sequencing and other high-throughput experimental technologies. In addition to maintaining the aspects to support basic research, KEGG is being expanded towards more practical applications integrating human diseases, drugs and other health-related substances.

KEGG is developed by Kanehisa Laboratories.

Please cite the following article(s) when using KEGG.
  • Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M.; KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457-D462 (2016). [pubmed] [pdf]
  • Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000). [pubmed] [pdf]
Please see the following for background and basic concepts of KEGG.
Copyright permision of KEGG pathway maps, etc. in academic publications may be requested through the feedback form.

References on KEGG

  1. Kanehisa, M.; Toward pathway engineering: a new database of genetic and molecular pathways. Science & Technology Japan, No. 59, pp. 34-38 (1996). [pdf]
  2. Goto, S., Bono, H., Ogata, H., Fujibuchi, W., Nishioka, T., Sato, K., and Kanehisa, M.; Organizing and computing metabolic pathway data in terms of binary relations. Pacific Symp. Biocomputing 1997, 175-186 (1996). [pubmed] [pdf]
  3. Kanehisa, M.; A database for post-genome analysis. Trends Genet. 13, 375-376 (1997). [pubmed]
  4. Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., and Kanehisa, M.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29-34 (1999). [pubmed] [pdf]
  5. Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000). [pubmed] [pdf]
  6. Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A.; The KEGG databases at GenomeNet. Nucleic Acids Res. 30, 42-46 (2002). [pubmed] [pdf]
  7. Kanehisa, M.; The KEGG database. Novartis Found. Symp. 247, 91-103 (2002). [pubmed] [pdf]
  8. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., and Hattori, M.; The KEGG resources for deciphering the genome. Nucleic Acids Res. 32, D277-D280 (2004). [pubmed] [pdf]
  9. Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., and Hirakawa, M.; From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 34, D354-357 (2006). [pubmed] [pdf] [Thomson]
  10. Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., and Yamanishi, Y.; KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36, D480-D484 (2008). [pubmed] [pdf]
  11. Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., and Hirakawa, M.; KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38, D355-D360 (2010). [pubmed] [pdf]
  12. Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., and Tanabe, M.; KEGG for integration and interpretation of large-scale molecular datasets. Nucleic Acids Res. 40, D109-D114 (2012). [pubmed] [pdf]
  13. Kanehisa, M., Goto, S., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M.; Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Res. 42, D199–D205 (2014). [pubmed] [pdf]
  14. Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M.; KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457-D462 (2016). [pubmed] [pdf]

Selected references on analysis tools

See also the publication list of Minoru Kanehisa.
(Genome analysis tools)
  1. Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A., and Kanehisa, M.; KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 35, W182-W185 (2007). [pubmed] [pdf]
  2. Okuda, S., Yamada, T., Hamajima, M., Itoh, M., Katayama, T., Bork, P., Goto, S., and Kanehisa, M.; KEGG Atlas mapping for global analysis of metabolic pathways. Nucleic Acids Res. 36, W423-W426 (2008). [pubmed] [pdf]
  3. Kotera, M., Yamanishi, Y., Moriya, Y., Kanehisa, M., and Goto, S.; GENIES: gene network inference engine based on supervised analysis. Nucleic Acids Res. 40, W162-W167 (2012). [pubmed] [pdf]
  4. Nakaya, A., Katayama, T., Itoh, M., Hiranuka, K., Kawashima, S., Moriya, Y., Okuda, S., Tanaka, M., Tokimatsu, T., Yamanishi, Y., Yoshizawa, A.C., Kanehisa, M., and Goto, S.; KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters. Nucleic Acids Res. 41, D353-D357 (2013). [pubmed] [pdf]
  5. Kanehisa, M., Sato, Y., and Morishima, K.; BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726-731 (2016). [pubmed] [pdf]
(Chemical analysis tools)
  1. Hattori, M., Okuno, Y., Goto, S., and Kanehisa, M.; Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. J. Am. Chem. Soc. 125, 11853-11865 (2003). [pubmed]
    Hattori, M., Tanaka, N., Kanehisa, M., and Goto, S.; SIMCOMP/SUBCOMP: chemical structure search servers for network analyses. Nucleic Acids Res. 38, W652-W656 (2010). [pubmed] [pdf]
  2. Kotera, M., Okuno, Y., Hattori, M., Goto, S., and Kanehisa, M.; Computational assignment of the EC numbers for genomic-scale analysis of enzymatic reactions. J. Am. Chem. Soc. 126, 16487-16498 (2004). [pubmed]
    Yamanishi, Y., Hattori, M., Kotera, M., Goto, S., and Kanehisa, M.; E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs. Bioinformatics 25, i79-i86 (2009). [pubmed] [pdf]
  3. Oh, M., Yamada, T., Hattori, M., Goto, S., and Kanehisa, M.; Systematic analysis of enzyme-catalyzed reaction patterns and prediction of microbial biodegradation pathways. J. Chem. Inf. Model. 47, 1702-1712 (2007). [pubmed]
    Moriya, Y., Shigemizu, D., Hattori, M., Tokimatsu, T., Kotera, M., Goto, S., and Kanehisa, M.; PathPred: an enzyme-catalyzed metabolic pathway prediction server. Nucleic Acids Res. 38, W138-W143 (2010). [pubmed] [pdf]
  4. Muto, A., Kotera, M., Tokimatsu, T., Nakagawa, Z., Goto, S., and Kanehisa, M.; Modular architecture of metabolic pathways revealed by conserved sequences of reactions. J. Chem. Inf. Model. 53, 613-622 (2013). [pubmed] [pdf]
(Glycan analysis tools)
  1. Hashimoto, K., Goto, S., Kawano, S., Aoki-Kinoshita, K.F., Ueda, N., Hamajima, M., Kawasaki, T., and Kanehisa, M.; KEGG as a glycome informatics resource. Glycobiology 16, 63R-70R (2006). [pubmed] [pdf]
  2. Aoki, K.F., Yamaguchi, A., Ueda, N., Akutsu, T., Mamitsuka, H., Goto, S., and Kanehisa, M.; KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains. Nucleic Acids Res. 32, W267-W272 (2004). [pubmed] [pdf]
(DBGET/LinkDB)
  1. Akiyama, Y., Goto, S., Uchiyama, I., and Kanehisa, M.; WebDBGET: an integrated database retrieval system which provides hyper-links among related entries. MIMBD'95: Second Meeting on the Interconnection of Molecular Biology Databases (1995). [pdf]
  2. Goto, S., Akiyama, Y., and Kanehisa, M.; LinkDB: a database of cross links between molecular biology databases. MIMBD'95: Second Meeting on the Interconnection of Molecular Biology Databases (1995). [pdf]
  3. Kanehisa, M.; Linking databases and organisms: GenomeNet resources in Japan. Trends Biochem Sci. 22, 442-444 (1997). [pubmed]
  4. Fujibuchi, W., Goto, S., Migimatsu, H., Uchiyama, I., Ogiwara, A., Akiyama, Y., and Kanehisa, M.; DBGET/LinkDB: an integrated database retrieval system. Pacific Symp. Biocomputing 1998, 683-694 (1997). [pubmed] [pdf]

Acknowledgments

The KEGG project is partially supported by:
The computational resources are provided by:
Past supports include:
  • Grand-in-aid for scientific research on the priority area "Genome Informatics" (1995) from the Ministry of Education
  • Grand-in-aid for scientific research on the priority area "Genome Science" (1996-2000) from the Ministry of Education
  • Research for the Future Program (2000-2004) from the Japan Society for the Promotion of Science
  • Bioinformatics Research and Development (2001-2005) of the Japan Science and Technology Agency
  • 21st Century COE Program "Genome Science" (2003-2007) from the Ministry of Education
  • Grant-in-aid for scientific research on the priority area "Comprehensive Genomics" (2005-2009) from the Ministry of Education
  • Bioinformatics Research and Development (2006-2010) of the Japan Science and Technology Agency
  • Life Science Database Integration Project (2011-2013) of the National Bioscience Database Center, Japan Science and Technology Agency
More details of each project can be found in the Kanehisa Laboratories Archive.

Last updated: March 4, 2016