Abstract

Abstract KEGG (https://www.kegg.jp) is a manually curated database resource integrating various biological objects categorized into systems, genomic, chemical and health information. Each object (database entry) is identified by the KEGG identifier (kid), which generally takes the form of a prefix followed by a five-digit number, and can be retrieved by appending /entry/kid in the URL. The KEGG pathway map viewer, the Brite hierarchy viewer and the newly released KEGG genome browser can be launched by appending /pathway/kid, /brite/kid and /genome/kid, respectively, in the URL. Together with an improved annotation procedure for KO (KEGG Orthology) assignment, an increasing number of eukaryotic genomes have been included in KEGG for better representation of organisms in the taxonomic tree. Multiple taxonomy files are generated for classification of KEGG organisms and viruses, and the Brite hierarchy viewer is used for taxonomy mapping, a variant of Brite mapping in the new KEGG Mapper suite. The taxonomy mapping enables analysis of, for example, how functional links of genes in the pathway and physical links of genes on the chromosome are conserved among organism groups.

Keywords

BiologyKEGGComputational biologyTaxonomy (biology)GenomeEvolutionary biologyBioinformaticsGeneticsGeneGene ontologyZoologyGene expression

MeSH Terms

GenomeGenomicsDatabasesFactualDatabasesGenetic

Affiliated Institutions

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Publication Info

Year
2022
Type
article
Volume
51
Issue
D1
Pages
D587-D592
Citations
5892
Access
Closed

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298
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Cite This

Minoru Kanehisa, Miho Furumichi, Yoko Sato et al. (2022). KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research , 51 (D1) , D587-D592. https://doi.org/10.1093/nar/gkac963

Identifiers

DOI
10.1093/nar/gkac963
PMID
36300620
PMCID
PMC9825424

Data Quality

Data completeness: 90%