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KEGG: integrating viruses and cellular organisms

Kanehisa, Minoru, Furumichi, Miho, Sato, Yoko, Ishiguro-Watanabe, Mari, Tanabe, Mao·2021·Nucleic Acids Research

Abstract

KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.

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Research works printed but not linked: 8

  1. Kanehisa, 2019, New approach for understanding genome variations in KEGG, Nucleic Acids Res., 47, D590, 10.1093/nar/gky962 · DOI
  2. Sunagawa, 2015, Ocean plankton. Structure and function of the global ocean microbiome, Science, 348, 1261359, 10.1126/science.1261359 · DOI
  3. Kanehisa, 2020, KEGG Mapper for inferring cellular functions from protein sequences, Protein Sci., 29, 28, 10.1002/pro.3711 · DOI
  4. Hanahan, 2000, The hallmarks of cancer, Cell, 100, 57, 10.1016/S0092-8674(00)81683-9 · DOI · Paper page
  5. Jellinger, 2009, Recent advances in our understanding of neurodegeneration, J. Neural Transm. (Vienna), 116, 1111, 10.1007/s00702-009-0240-y · DOI · Paper page
  6. Baltimore, 1971, Expression of animal virus genomes, Bacteriol. Rev., 35, 235, 10.1128/BR.35.3.235-241.1971 · DOI
  7. Lefkowitz, 2018, Virus taxonomy: the database of the International Committee on Taxonomy of Viruses (ICTV), Nucleic Acids Res., 46, D708, 10.1093/nar/gkx932 · DOI
  8. Kanehisa, 2014, Data, information, knowledge and principle: back to metabolism in KEGG, Nucleic Acids Res., 42, D199, 10.1093/nar/gkt1076 · DOI

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Metadata

Authors
Kanehisa, M., Furumichi, M., Sato, Y., Ishiguro-Watanabe, M., & Tanabe, M.
Affiliations
  • Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
  • Social ICT Solutions Department, Fujitsu Kyushu Systems Ltd., Hakata-ku, Fukuoka 812-0007, Japan
  • Human Genome Center, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo 108-8639, Japan
Venue
Nucleic Acids Research
Published
2020-10-30
Volume
49
Issue
D1
Pages
D545-D551
ISSN
  • 0305-1048
  • 1362-4962
Cited by
3,436
References
2
Language
en
Funders
National Bioscience Database Center

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