New approach for understanding genome variations in KEGG.
New approach for understanding genome variations in KEGG.
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DOI：
10.1093/nar/gky962
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发表时间：
2019-01-08
影响因子：
14.9
通讯作者：
Tanabe M
中科院分区：
文献类型：
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作者：
Kanehisa M;Sato Y;Furumichi M;Morishima K;Tanabe M
KEGG（京都基因和基因组百科全书; https://www.kegg.jp/或https：//www.genome.jp/kegg/）是用于基因组序列和其他高通量数据的生物学解释的参考知识库。这是一个综合数据库，包括三大类系统信息、基因组信息和化学信息，以及另一类人类特有的健康信息。KEGG通路图、BRITE层次结构和KEGG模块已经被开发为具有功能直系同源物的KEGG直系同源节点的通用分子网络，使得KEGG通路图绘制和其他程序可以应用于任何细胞生物体。然而，不幸的是，这种通用方法不足以表示健康信息类别中的知识，其中必须考虑人类基因组的变异，特别是与疾病有关的变异。因此，我们引入了一种新的方法，在最近发布的KEGG NETWORK数据库中，将人类基因变体明确纳入我们所谓的“网络变体”中。这使得人们能够积累有关疾病相关的扰动分子网络的知识，这些扰动分子网络不仅由基因变异引起，而且也由病毒和其他病原体、环境因素和药物引起。我们期望KEGG网络将成为另一个参考知识库，用于基本了解疾病机制和临床测序和药物开发的实际应用。
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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DOI：
10.1007/978-1-4939-7015-5_11
发表时间：
2017-01-01
期刊：
PROTEIN FUNCTION PREDICTION: METHODS AND PROTOCOLS
影响因子：
--
作者：
Kanehisa, Minoru
通讯作者：
Kanehisa, Minoru
影响因子：
14.9
作者：
Sherry, ST;Ward, MH;Sirotkin, K
通讯作者：
Sirotkin, K
影响因子：
14.9
作者：
Kanehisa M;Sato Y;Kawashima M;Furumichi M;Tanabe M
通讯作者：
Tanabe M
影响因子：
14.9
作者：
Landrum MJ;Lee JM;Benson M;Brown G;Chao C;Chitipiralla S;Gu B;Hart J;Hoffman D;Hoover J;Jang W;Katz K;Ovetsky M;Riley G;Sethi A;Tully R;Villamarin-Salomon R;Rubinstein W;Maglott DR
通讯作者：
Maglott DR
DOI：
10.1007/978-1-4939-8561-6_17
发表时间：
2018-01-01
期刊：
DATA MINING FOR SYSTEMS BIOLOGY, 2 EDITION
影响因子：
--
作者：
Kanehisa, Minoru
通讯作者：
Kanehisa, Minoru