KEGG for characterizing genomes and pathways in the biosphere

The KEGG database (https://www.kegg.jp) has been developed as a model of the biological systems. By organizing knowledge of cellular and organism-level functions in the form of molecular wiring diagrams, the model enables generating new knowledge and finding practical applications. The KO (KEGG Orthology) dataset plays the basic role of organizing knowledge. KO is an ortholog with functional relevance, generalizing experimental evidence in specific organisms to other organisms. KEGG molecular networks, including pathway maps and modules, are generic networks with KOs as network nodes, and thus KEGG mapping from genomes to pathways can be applied to any organism. As the number of KOs increases and the KO annotation rate improves, KEGG mapping is further expanded. A set of KOs in the genome and a set of modules in the metabolic pathways are now used to characterize various data objects in the biosphere, including organisms, organism groups, microbiomes, viruses, and their combinations, such as endosymbiont-host, microbiome-host, and virus-host relationships. Furthermore, a simple measure of similarity either by KO compositions or module compositions is introduced to compare organism groups. The resulting similarity dendrograms possibly reflect similarity of cellular functions or, more specifically, metabolic functions, which can be compared with phylogenetic trees.

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Publication Details

Journal
Nucleic Acids Research
Published
2026-10-27
DOI
https://doi.org/10.1093/nar/gkag1042
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

KEGG for characterizing genomes and pathways in the biosphere

Miho Furumichi, Minoru I. Kanehisa, Yuriko Matsuura, Mari Ishiguro-Watanabe et al.
2 links
Nucleic Acids Research
Bioinformatics and Genomic Networks
article

KEGG for characterizing genomes and pathways in the biosphere

Miho Furumichi, Minoru I. Kanehisa, Yuriko Matsuura, Mari Ishiguro-Watanabe, Yoko Sato
article en

Abstract

The KEGG database (https://www.kegg.jp) has been developed as a model of the biological systems. By organizing knowledge of cellular and organism-level functions in the form of molecular wiring diagrams, the model enables generating new knowledge and finding practical applications. The KO (KEGG Orthology) dataset plays the basic role of organizing knowledge. KO is an ortholog with functional relevance, generalizing experimental evidence in specific organisms to other organisms. KEGG molecular networks, including pathway maps and modules, are generic networks with KOs as network nodes, and thus KEGG mapping from genomes to pathways can be applied to any organism. As the number of KOs increases and the KO annotation rate improves, KEGG mapping is further expanded. A set of KOs in the genome and a set of modules in the metabolic pathways are now used to characterize various data objects in the biosphere, including organisms, organism groups, microbiomes, viruses, and their combinations, such as endosymbiont-host, microbiome-host, and virus-host relationships. Furthermore, a simple measure of similarity either by KO compositions or module compositions is introduced to compare organism groups. The resulting similarity dendrograms possibly reflect similarity of cellular functions or, more specifically, metabolic functions, which can be compared with phylogenetic trees.

Nucleic Acids Research
Kyoto University (JP), Kyoto University Institute for Chemical Research (JP), Institute of Medical Science, The University of Tokyo (JP), The University of Tokyo (JP)
Japan Science and Technology Agency
Openalex Percentile: Top 22%
Bioinformatics and Genomic Networks
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