Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.
Social ICT Solutions Department, Fujitsu Kyushu Systems Ltd., Hakata-ku, Fukuoka, Japan.
Protein Sci. 2020 Jan;29(1):28-35. doi: 10.1002/pro.3711. Epub 2019 Aug 29.
KEGG is a reference knowledge base for biological interpretation of large-scale molecular datasets, such as genome and metagenome sequences. It accumulates experimental knowledge about high-level functions of the cell and the organism represented in terms of KEGG molecular networks, including KEGG pathway maps, BRITE hierarchies, and KEGG modules. By the process called KEGG mapping, a set of protein coding genes in the genome, for example, can be converted to KEGG molecular networks enabling interpretation of cellular functions and other high-level features. Here we report a new version of KEGG Mapper, a suite of KEGG mapping tools available at the KEGG website (https://www.kegg.jp/ or https://www.genome.jp/kegg/), together with the KOALA family tools for automatic assignment of KO (KEGG Orthology) identifiers used in the mapping.
KEGG 是一个用于大规模分子数据集(如基因组和宏基因组序列)的生物学解释的参考知识库。它以 KEGG 分子网络(包括 KEGG 途径图谱、BRITE 层次结构和 KEGG 模块)的形式积累有关细胞和生物体高级功能的实验知识。通过称为 KEGG 映射的过程,可以将基因组中的一组蛋白质编码基因转换为 KEGG 分子网络,从而能够解释细胞功能和其他高级特征。在这里,我们报告了 KEGG Mapper 的新版本,这是一套 KEGG 映射工具,可在 KEGG 网站(https://www.kegg.jp/ 或 https://www.genome.jp/kegg/)上获得,以及 KOALA 家族工具,用于自动分配用于映射的 KO(KEGG 直系同源)标识符。