KEGG mapping tools for uncovering hidden features in biological data
KEGG mapping tools for uncovering hidden features in biological data
复制标题
DOI：
10.1002/pro.4172
复制
发表时间：
2021-08-26
期刊：
影响因子：
8
通讯作者：
Kawashima, Masayuki
中科院分区：
文献类型：
--
作者：
Kanehisa, Minoru;Sato, Yoko;Kawashima, Masayuki
与人工智能和机器学习方法相比，KEGG（）依赖于人类智能来开发生物系统的“模型”，特别是通过从已发表文献中获取知识手动创建的KEGG通路图的形式。然后，KEGG模型可用于生物大数据分析，例如，通过KEGG映射的简单程序来揭示隐藏在其基因组序列中的生物体的系统功能。在这里，我们提出了KEGG Mapper的更新版本，这是一套先前报道的KEGG作图工具（Kanehisa和Sato，Protein Sci 2020; 29：28-35），以及KEGG途径图查看器和BRITE层次结构查看器的新版本。对BRITE映射进行了显著的增强，其中可以通过对分层树的操作（例如修剪和缩放）来检查映射结果。在分类学映射工具中也实现了树操作功能，用于将KO（KEGG Orthology）组和模块与表型联系起来。
In contrast to artificial intelligence and machine learning approaches, KEGG () has relied on human intelligence to develop "models" of biological systems, especially in the form of KEGG pathway maps that are manually created by capturing knowledge from published literature. The KEGG models can then be used in biological big data analysis, for example, for uncovering systemic functions of an organism hidden in its genome sequence through the simple procedure of KEGG mapping. Here we present an updated version of KEGG Mapper, a suite of KEGG mapping tools reported previously (Kanehisa and Sato, Protein Sci 2020; 29:28-35), together with the new versions of the KEGG pathway map viewer and the BRITE hierarchy viewer. Significant enhancements have been made for BRITE mapping, where the mapping result can be examined by manipulation of hierarchical trees, such as pruning and zooming. The tree manipulation feature has also been implemented in the taxonomy mapping tool for linking KO (KEGG Orthology) groups and modules to phenotypes.