Kotera Masaaki, Hirakawa Mika, Tokimatsu Toshiaki, Goto Susumu, Kanehisa Minoru
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.
Methods Mol Biol. 2012;802:19-39. doi: 10.1007/978-1-61779-400-1_2.
In this chapter, we demonstrate the usability of the KEGG (Kyoto encyclopedia of genes and genomes) databases and tools, especially focusing on the visualization of the omics data. The desktop application KegArray and many Web-based tools are tightly integrated with the KEGG knowledgebase, which helps visualize and interpret large amount of data derived from high-throughput measurement techniques including microarray, metagenome, and metabolome analyses. Recently developed resources for human disease, drug, and plant research are also mentioned.
在本章中，我们展示了KEGG（京都基因与基因组百科全书）数据库及工具的可用性，尤其着重于组学数据的可视化。桌面应用程序KegArray以及许多基于网络的工具与KEGG知识库紧密集成，这有助于对源自高通量测量技术（包括微阵列、宏基因组和代谢组分析）的大量数据进行可视化和解读。我们还提及了最近开发的用于人类疾病、药物和植物研究的资源。
