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      KEGG: integrating viruses and cellular organisms

      1 , 1 , 2 , 3 , 1
      Nucleic Acids Research
      Oxford University Press (OUP)

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          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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          Most cited references10

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          The Hallmarks of Cancer

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            Toward understanding the origin and evolution of cellular organisms

            In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.
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              • Record: found
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              New approach for understanding genome variations in KEGG

              Abstract KEGG (Kyoto Encyclopedia of Genes and Genomes; https://www.kegg.jp/ or https://www.genome.jp/kegg/) is a reference knowledge base for biological interpretation of genome sequences and other high-throughput data. It is an integrated database consisting of three generic categories of systems information, genomic information and chemical information, and an additional human-specific category of health information. KEGG pathway maps, BRITE hierarchies and KEGG modules have been developed as generic molecular networks with KEGG Orthology nodes of functional orthologs so that KEGG pathway mapping and other procedures can be applied to any cellular organism. Unfortunately, however, this generic approach was inadequate for knowledge representation in the health information category, where variations of human genomes, especially disease-related variations, had to be considered. Thus, we have introduced a new approach where human gene variants are explicitly incorporated into what we call ‘network variants’ in the recently released KEGG NETWORK database. This allows accumulation of knowledge about disease-related perturbed molecular networks caused not only by gene variants, but also by viruses and other pathogens, environmental factors and drugs. We expect that KEGG NETWORK will become another reference knowledge base for the basic understanding of disease mechanisms and practical use in clinical sequencing and drug development.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Nucleic Acids Research
                Oxford University Press (OUP)
                0305-1048
                1362-4962
                January 08 2021
                January 08 2021
                October 30 2020
                January 08 2021
                January 08 2021
                October 30 2020
                : 49
                : D1
                : D545-D551
                Affiliations
                [1 ]Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
                [2 ]Social ICT Solutions Department, Fujitsu Kyushu Systems Ltd., Hakata-ku, Fukuoka 812-0007, Japan
                [3 ]Human Genome Center, Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo 108-8639, Japan
                Article
                10.1093/nar/gkaa970
                69a77414-2ee4-47f8-b98d-baaf25143593
                © 2020

                http://creativecommons.org/licenses/by-nc/4.0/

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