New approach for understanding genome variations in KEGG

被引:1446
作者
Kanehisa, Minoru [1 ]
Sato, Yoko [2 ]
Furumichi, Miho [1 ]
Morishima, Kanae [1 ]
Tanabe, Mao [1 ]
机构
[1] Kyoto Univ, Inst Chem Res, Uji, Kyoto 6110011, Japan
[2] Fujitsu Kyushu Syst Ltd, Social ICT Solut Dept, Hakata Ku, Fukuoka, Fukuoka 8120007, Japan
基金
日本科学技术振兴机构;
关键词
HALLMARKS; DISEASES; CANCER;
D O I
10.1093/nar/gky962
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
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.
引用
收藏
页码:D590 / D595
页数:6
相关论文
共 13 条
[1]
Viral mimicry of cytokines, chemokines and their receptors [J].
Alcami, A .
NATURE REVIEWS IMMUNOLOGY, 2003, 3 (01) :36-50
[2]
COSMIC: somatic cancer genetics at high-resolution [J].
Forbes, Simon A. ;
Beare, David ;
Boutselakis, Harry ;
Bamford, Sally ;
Bindal, Nidhi ;
Tate, John ;
Cole, Charlotte G. ;
Ward, Sari ;
Dawson, Elisabeth ;
Ponting, Laura ;
Stefancsik, Raymund ;
Harsha, Bhavana ;
Kok, Chai Yin ;
Jia, Mingming ;
Jubb, Harry ;
Sondka, Zbyslaw ;
Thompson, Sam ;
De, Tisham ;
Campbell, Peter J. .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D777-D783
[3]
The hallmarks of cancer [J].
Hanahan, D ;
Weinberg, RA .
CELL, 2000, 100 (01) :57-70
[4]
Hallmarks of Cancer: The Next Generation [J].
Hanahan, Douglas ;
Weinberg, Robert A. .
CELL, 2011, 144 (05) :646-674
[5]
Kanehisa M, 2018, METHODS MOL BIOL, V1807, P225, DOI 10.1007/978-1-4939-8561-6_17
[6]
Kanehisa M, 2017, METHODS MOL BIOL, V1611, P135, DOI 10.1007/978-1-4939-7015-5_11
[7]
KEGG: new perspectives on genomes, pathways, diseases and drugs [J].
Kanehisa, Minoru ;
Furumichi, Miho ;
Tanabe, Mao ;
Sato, Yoko ;
Morishima, Kanae .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D353-D361
[8]
BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences [J].
Kanehisa, Minoru ;
Sato, Yoko ;
Morishima, Kanae .
JOURNAL OF MOLECULAR BIOLOGY, 2016, 428 (04) :726-731
[9]
KEGG as a reference resource for gene and protein annotation [J].
Kanehisa, Minoru ;
Sato, Yoko ;
Kawashima, Masayuki ;
Furumichi, Miho ;
Tanabe, Mao .
NUCLEIC ACIDS RESEARCH, 2016, 44 (D1) :D457-D462
[10]
KEGG for representation and analysis of molecular networks involving diseases and drugs [J].
Kanehisa, Minoru ;
Goto, Susumu ;
Furumichi, Miho ;
Tanabe, Mao ;
Hirakawa, Mika .
NUCLEIC ACIDS RESEARCH, 2010, 38 :D355-D360