The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
KEGG as a reference resource for gene and protein annotation
Open accessAbstract
KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.
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In the citing paper
“These efforts then resulted in the identification of two important precursors for clavulanic acid—arginine (C5 precursor) and glutaraldehyde-3-phosphate (C3 precursor) (Romero et al., 1986; Kanehisa and Goto, 2000; Kanehisa et al., 2016).”
From Fermentation Conditions that Affect Clavulanic Acid Production in Streptomyces clavuligerus: A Systematic Review (2016) · cites this paper as Kanehisa et al., 2016
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“The latest update (v5.0), released September 2019, extends the analyses further, substantially increasing the scope of functional annotations through the addition of KEGG (23) orthologue predictions for reads and assembled contigs, and KEGG pathways and Genome Properties (24) annotations for assembled contigs.”
From MGnify: the microbiome analysis resource in 2020 (2019) · cites this paper as [23]
In the citing paper
“Additional functional analyses are also provided in the form of KEGG orthologue (KO) (23) annotations, which are calculated using HMMER (40) and the KOfam library (using a slightly modified form of the profile hidden Markov model (HMM) database of KEGG orthologues (41)) on the predicted protein sequences.”
From MGnify: the microbiome analysis resource in 2020 (2019) · cites this paper as [23]
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Citations
Cites
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Li, W.-Z., & Godzik, A. (2006) · Bioinform. · doi:10.1093/bioinformatics/btl158 · Cited by 10,996
UniProt: a hub for protein information
The UniProt Consortium (2015) · Nucleic Acids Research · doi:10.1093/nar/gku989 · Cited by 5,106
KAAS: an automatic genome annotation and pathway reconstruction server
Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A. C., & Kanehisa, M. I. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm321 · Cited by 4,128
Self-citationData, information, knowledge and principle: back to metabolism in KEGG
Kanehisa, M. I., Goto, S., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1076 · Cited by 3,103
Self-citationUpdated Functional Classification of β-Lactamases
Bush, K., & Jacoby, G. A. (2010) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01009-09 · Cited by 2,367
Federhen, S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1178 · Cited by 1,436
NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy
Pruitt, K. D., Tatusova, T., Brown, G. R., & Maglott, D. R. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1079 · Cited by 1,149 · cited 6×
“The genomic information category contains the GENOME and GENES databases for collections of organisms with complete genomes and their gene catalogs, which are mostly taken from RefSeq (2) and GenBank (3) databases.”
MethodInfluentialBenson, D. A., Clark, K., Karsch‐Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1216 · Cited by 407
Update on RefSeq microbial genomes resources
Tatusova, T. A., Ciufo, S. A., Federhen, S., Fedorov, B., McVeigh, R., O’Neill, K., Tolstoy, I., & Zaslavsky, L. Y. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1062 · Cited by 127
Fifty‐five years of enzyme classification: advances and difficulties
McDonald, A. G., & Tipton, K. F. (2013) · FEBS Journal · doi:10.1111/febs.12530 · Cited by 116
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csuWGCNA: a combination of signed and unsigned WGCNA to capture negative correlations
Dai, R., Xia, Y., Liu, C., & Chen, C. (2018) · doi:10.1101/288225 · Cited by 13
Liu, Y.-S., Pan, J.-Q., Pan, X.-B., Kong, F.-S., Zhang, J.-Q., Wei, Z.-Y., Xu, Z.-H., Rao, J.-H., Wang, J.-H., & Chen, J.-H. (2024) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.65.1.13 · Cited by 12
“R package clusterProfiler (version 3.10.1) 11 and the web tool Metascape 12 were used for analysis and visualization of gene ontology (GO), 13 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, 14 and Gene Set Enrichment Analysis (GSEA).”
MethodInfluentialGuild-based approach for mitigating information loss and distortion issues in microbiome analysis
Zhao, L., Wu, G., & Zhao, N. (2024) · Journal of Clinical Investigation · doi:10.1172/jci185395 · Cited by 9
Agolino, G., Cristofolini, M., Ronsivalle, M. A., Cattivelli, A., Tagliazucchi, D., Caggia, C., Solieri, L., & Randazzo, C. L. (2026) · Probiotics and Antimicrobial Proteins · doi:10.1007/s12602-025-10810-0 · Cited by 1
“A complementary functional analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) mapper/BLASTKOALA tool [42].”
Metadata
- Authors
- Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M.
- Affiliations
- Kyoto University (JP)
- Fujitsu (Japan) (JP)
- Corresponding author
- Kanehisa, Minoru
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-10-17
- Volume
- 44
- Issue
- D1
- Pages
- D457-D462
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC4702792
- OpenAlex
- W2110256992
- Cited by
- 7,387
- References
- 14
- Citations by year
- 2026: 608 · 2025: 846 · 2024: 766 · 2023: 726 · 2022: 819 · 2021: 811 · 2020: 636 · 2019: 621 · 2018: 638 · 2017: 581 · 2016: 320 · 2015: 6
- FWCI
- 224.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion, other-oa)
- HighWire Press Open Archive (submittedVersion)
- Kyoto University Research Information Repository (Kyoto University) (submittedVersion, cc-by-nc)
- Funders
- Japan Science and Technology Agency
- Institute for Chemical Research, Kyoto University
- National Bioscience Database Center
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- KEGG, KEGG Orthology, genome annotation, KEGG pathways, KEGG modules, orthogroups, pan-genome, drug interaction networks
- MeSH terms
- Amino Acid Sequence, Drug Resistance, Microbial, Genes, Plasmids, Proteins, Viruses, Genome, Databases, Genetic, Metabolic Networks and Pathways, Molecular Sequence Annotation
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