Enzyme Annotation and Metabolic Reconstruction Using KEGG
Enzyme Annotation and Metabolic Reconstruction Using KEGG
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DOI：
10.1007/978-1-4939-7015-5_11
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发表时间：
2017-01-01
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通讯作者：
Kanehisa, Minoru
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作者：
Kanehisa, Minoru
KEGG是一个整合的数据库资源，用于将序列与从分子到更高水平的生物功能联系起来。关于分子功能的知识存储在KO（KEGG Orthology）数据库中，而细胞和生物体水平的功能则存储在PATHWAY和MOTORY数据库中。存储在GENES数据库中的完整基因组中的基因通过内部注释程序被赋予KO标识符，从而能够重建KEGG途径和模块以解释更高水平的功能。这是可能的，因为所有KEGG通路和模块都表示为KO节点的网络。在这里，我们提出了基于知识的预测方法，使用KEGG资源的氨基酸序列的功能表征。具体来说，我们展示了如何在KEGG网站上提供的工具，包括BlastKOALA和KEGG Mapper可以用于酶注释和代谢重建。
KEGG is an integrated database resource for linking sequences to biological functions from molecular to higher levels. Knowledge on molecular functions is stored in the KO (KEGG Orthology) database, while cellular-and organism-level functions are represented in the PATHWAY and MODULE databases. Genes in the complete genomes, which are stored in the GENES database, are given KO identifiers by the internal annotation procedure, enabling reconstruction of KEGG pathways and modules for interpretation of higher-level functions. This is possible because all the KEGG pathways and modules are represented as networks of KO nodes. Here we present knowledge-based prediction methods for functional characterization of amino acid sequences using the KEGG resource. Specifically we show how the tools available at the KEGG website including BlastKOALA and KEGG Mapper can be utilized for enzyme annotation and metabolic reconstruction.