New approach for understanding genome variations in KEGG
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- Minoru Kanehisa
- Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
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- Yoko Sato
- Social ICT Solutions Department, Fujitsu Kyushu Systems Ltd., Hakata-ku, Fukuoka 812-0007, Japan
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- Miho Furumichi
- Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
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- Kanae Morishima
- Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
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- Mao Tanabe
- Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
Description
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.
Journal
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- Nucleic Acids Research
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Nucleic Acids Research 47 (D1), D590-D595, 2018-10-13
Oxford University Press (OUP)
