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KEGG for taxonomy-based analysis of pathways and genomes
Open accessAbstract
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.
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Cites
Database resources of the National Center for Biotechnology Information: update
Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,695
O'Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1189 · Cited by 6,357
Whole-Genome Random Sequencing and Assembly of Haemophilus influenzae Rd
Fleischmann, R. D., Adams, M. D., White, O. R., Clayton, R. A., Kirkness, E. F., Kerlavage, A. R., Bult, C. J., Tomb, J.-F., Dougherty, B. A., Merrick, J. M., et al. (1995) · Science · doi:10.1126/science.7542800 · Cited by 5,731
Toward understanding the origin and evolution of cellular organisms
Kanehisa, M. (2019) · Protein Science · doi:10.1002/pro.3715 · Cited by 5,509 · cited 2×
“It is hoped that this latter aspect will further be improved to enable a better understanding of more fundamental problems, such as how molecular network systems were developed in the cell, coevolved with the genome and transmitted to extant species (3).”
BackgroundSelf-citationKEGG: integrating viruses and cellular organisms
Kanehisa, M., Furumichi, M., Sato, Y., Ishiguro-Watanabe, M., & Tanabe, M. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa970 · Cited by 3,436
Self-citationDatabase resources of the national center for biotechnology information
Sayers, E. W., Bolton, E. E., Brister, J. R., Canese, K., Chan, J., Comeau, D. C., Connor, R., Funk, K., Kelly, C., Kim, S., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1112 · Cited by 2,812
Federhen, S. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1178 · Cited by 1,436
Virus taxonomy: the database of the International Committee on Taxonomy of Viruses (ICTV)
Lefkowitz, E. J., Dempsey, D. M., Hendrickson, R. C., Orton, R. J., Siddell, S. G., & Smith, D. B. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx932 · Cited by 1,230
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Huang, G., Li, M., Li, Y. J., & Mao, Y. (2022) · Laboratory Medicine · doi:10.1093/labmed/lmac041 · Cited by 933
KEGG mapping tools for uncovering hidden features in biological data
Kanehisa, M. I., Sato, Y., & Kawashima, M. (2021) · Protein Science · doi:10.1002/pro.4172 · Cited by 749
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Li, Y., Su, Z., Lin, Y., Xu, Z., Bao, H., Wang, F., Liu, J., Hu, S., Wang, Z., Yu, X., et al. (2024) · BMC Plant Biology · doi:10.1186/s12870-023-04712-y · Cited by 54
Compensatory evolution in NusG improves fitness of drug-resistant M. tuberculosis
Eckartt, K. A., Delbeau, M., Munsamy, V., DeJesus, M. A., Azadian, Z. A., Reddy, A. K., Chandanani, J., Poulton, N. C., Quiñones-García, S., Bosch, B., et al. (2024) · Nature · doi:10.1038/s41586-024-07206-5 · Cited by 54
Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes
Pekayvaz, K., Losert, C., Knottenberg, V., Gold, C., van Blokland, I. V., Oelen, R., Groot, H. E., Benjamins, J. W., Brambs, S., Kaiser, R. W. J., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02953-4 · Cited by 63
Tsenkova, M., Brauer, M., Pozdeev, V. I., Kasakin, M. F., Busi, S. B., Schmoetten, M., Cheung, D., Meyers, M., Rodriguez, F., Gaigneaux, A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56678-0 · Cited by 58
Han, M., Cui, R., Wang, D., Huang, H., Rui, C., Malik, W. A., Wang, J., Zhang, H., Xu, N., Liu, X., et al. (2023) · BMC Plant Biology · doi:10.1186/s12870-023-04258-z · Cited by 52
Unveiling the human nitroproteome: Protein tyrosine nitration in cell signaling and cancer
Griswold‐Prenner, I., Kashyap, A. K., Mazhar, S., Hall, Z. W., Fazelinia, H., & Ischiropoulos, H. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.105038 · Cited by 52
Discovering nanoparticle corona ligands for liver macrophage capture
Bussin, B., Macduff, M. G. G., Ngo, W., Wu, J. L. Y., Lin, Z. P., Farias, A. G., Stordy, B. P., Sepahi, Z., Ahmed, S., Moffat, J., et al. (2025) · Nature Nanotechnology · doi:10.1038/s41565-025-01903-6 · Cited by 53
Hoti, D., Nixha, A. R., Duran, H. E., Arslan, M., Yıldıztekin, G., Ece, A., & Türkeş, C. (2025) · Bioorganic & Medicinal Chemistry · doi:10.1016/j.bmc.2025.118416 · Cited by 52
Discovery of disease-adapted bacterial lineages in inflammatory bowel diseases
Kumbhari, A., Cheng, T. N. H., Ananthakrishnan, A. N., Kochar, B., Burke, K. E., Shannon, K., Lau, H., Xavier, R. J., & Smillie, C. S. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.05.022 · Cited by 54
Metabolomics-based study of potential biomarkers of sepsis
Li, Y., Wang, C., & Chen, M. (2023) · Scientific Reports · doi:10.1038/s41598-022-24878-z · Cited by 49
Identifying potential biomarkers of idiopathic pulmonary fibrosis through machine learning analysis
Wu, Z., Chen, H., Ke, S., Mo, L., Qiu, M., Zhu, G., Zhu, W., & Liu, L. (2023) · Scientific Reports · doi:10.1038/s41598-023-43834-z · Cited by 53
Wang, X., Shi, H., Huang, S., Zhang, Y., He, X., Long, Q., Qian, B., Zhong, Y., Qi, Z., Zhao, Q., et al. (2023) · Biomaterials · doi:10.1016/j.biomaterials.2023.122364 · Cited by 53
Liu, T., Qiao, H., Wang, Z., Yang, X., Pan, X., Yu, Y., Ye, X., Sakurai, T., Lin, H., & Zhang, Y. (2024) · Advanced Science · doi:10.1002/advs.202400009 · Cited by 51
A fin-loop-like structure in GPX4 underlies neuroprotection from ferroptosis
Lorenz, S., Wahida, A., Bostock, M. J., Seibt, T., Mourão, A., Levkina, A., Trümbach, D., Soudy, M., Emler, D., Rothammer, N., et al. (2025) · Cell · doi:10.1016/j.cell.2025.11.014 · Cited by 61
Wongfaed, N., O‐Thong, S., Sittijunda, S., & Reungsang, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-29895-0 · Cited by 50
Yu, H., Wang, J., Zhang, K., Cheng, G., Mei, C., & Zan, L. (2023) · BMC Genomics · doi:10.1186/s12864-023-09452-9 · Cited by 50
Hintikka, J. E., Ahtiainen, J. P., Permi, P., Jalkanen, S., Lehtonen, M., & Pekkala, S. (2023) · Scientific Reports · doi:10.1038/s41598-023-38357-6 · Cited by 50
Nutritional Characteristics, Health Impact, and Applications of Kefir
Apalowo, O. E., Adegoye, G. A., Mbogori, T. N., Kandiah, J., & Obuotor, T. M. (2024) · Foods · doi:10.3390/foods13071026 · Cited by 54
Li, V. O. K., Yang, H., Kaistha, T., Zhang, Q., Downey, J., Gozes, I., & Lam, J. C. K. (2025) · Scientific Reports · doi:10.1038/s41598-025-85947-7 · Cited by 60
Liu, S., Liu, Z., Shang, A., Xun, J., Lv, Z., Zhou, S., Liu, C., Zhang, Q., & Yang, Y. (2023) · Scientific Reports · doi:10.1038/s41598-023-33915-4 · Cited by 53
Naithani, S., Deng, C. H., Sahu, S. K., & Jaiswal, P. (2023) · Biomolecules · doi:10.3390/biom13091403 · Cited by 51
Comprehensive multi-omics analysis of breast cancer reveals distinct long-term prognostic subtypes
Sharma, A., Debik, J., Naume, B., Ohnstad, H. O., Sahlberg, K. K., Borgen, E., Børresen‐Dale, A., Engebråten, O., Fritzman, B., Garred, Ø., et al. (2024) · Oncogenesis · doi:10.1038/s41389-024-00521-6 · Cited by 51
Wang, C., Yang, C., Western, D., Ali, M., Wang, Y., Phuah, C., Budde, J., Wang, L., Gorijala, P., Timsina, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01973-7 · Cited by 53
Aspartame carcinogenic potential revealed through network toxicology and molecular docking insights
Chen, D., & Hou, X. (2024) · Scientific Reports · doi:10.1038/s41598-024-62461-w · Cited by 47
Whole-genome duplication in an algal symbiont bolsters coral heat tolerance
Dougan, K. E., Bellantuono, A. J., Kahlke, T., Abbriano, R. M., Chen, Y., Shah, S., Granados‐Cifuentes, C., van Oppen, M. J. H., Bhattacharya, D., Suggett, D. J., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn2218 · Cited by 50
Zhang, J., Chen, B., Li, H., Wang, Y., Liu, X., Wong, K. Y., Chan, W. N., Chan, A. K., Cheung, A. H. K., Leung, K. T., et al. (2022) · The Journal of Pathology · doi:10.1002/path.6033 · Cited by 47
Xu, Z., Yang, L., Pi, P., Yi, Y., Tang, H., Zhang, Z., Xiong, H., Lei, B., Shi, Y., Li, J., et al. (2024) · Phytomedicine · doi:10.1016/j.phymed.2024.155817 · Cited by 46
Metadata
- Authors
- Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M., & Ishiguro-Watanabe, M.
- Affiliations
- Kyoto University (JP)
- Fujitsu (Japan) (JP)
- Network Support Co. Ltd., Hakata-ku , Fukuoka 812-0011, Japan
- Institute of Medical Science, The University of Tokyo (JP)
- Corresponding author
- Kanehisa, Minoru
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-10-27
- Volume
- 51
- Issue
- D1
- Pages
- D587-D592
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC9825424
- OpenAlex
- W4307425304
- Cited by
- 5,833
- References
- 12
- Citations by year
- 2026: 911 · 2025: 1421 · 2024: 1899 · 2023: 1560 · 2022: 39
- FWCI
- 461.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Institutional Repositories DataBase (IRDB) (submittedVersion)
- Kyoto University Research Information Repository (Kyoto University) (submittedVersion, cc-by-nc)
- Funders
- Japan Science and Technology Agency
- 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, pathway maps, genome annotation, KEGG Orthology, eukaryotic genomes, viruses, genome browser
- MeSH terms
- Databases, Factual, Genome, Genomics, Databases, Genetic
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