KEGG工具用于病毒蛋白的分类和分析
Zhao Jin1,2, Yoko Sato2, Masayuki Kawashima3
1Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.
Protein science : a publication of the Protein Society
|October 26, 2023
概括
现在,KEGG正统学 (KO) 系统包括病毒正统学集群 (VOCs),以改善病毒基因组和蛋白质的分析. 这增强了对KEGG内的病毒关系和基因功能的理解.
科学领域:
- 生物信息学是一种生物信息学.
- 病毒学 病毒学
- 基因组学就是基因组学.
背景情况:
- 凯格数据库有助于理解细胞生物的基因和基因组,使用凯格正统学 (KO).
- 病毒蛋白具有较低的KO分配率,限制了它们与KEGG分析工具的整合.
- 现有的KEGG工具需要加强,以进行全面的病毒基因组分析.
研究的目的:
- 引入病毒正统集群 (VOCs) 作为病毒蛋白分析的KOs的补充.
- 为了证明VOCs在KEGG绘制中的实用性,用于病毒分类学和基因顺序识别.
- 介绍KEGG工具扩展用于病毒蛋白质分析的概述.
主要方法:
- 计算生成的病毒正统群集 (VOCs) 覆盖了KEGG中的90%的病毒蛋白质.
- 利用VOC用于分类学映射,以确定序列相似性和分类学群体之间的关系.
- 采用选定的VOC来定义用于描述病毒蛋白功能的初步KOs.
主要成果:
- 挥发性有机物在KEGG框架内显著增加了病毒蛋白的覆盖范围.
- 挥发性有机化合物使得病毒基因组中保存的基因序列的有效分类绘图和识别成为可能.
- 扩展的KEGG工具为分析病毒蛋白功能提供了新的能力.
结论:
- 挥发性有机物是KEGG的宝贵补充,大大改善了病毒基因组的分析.
- 增强的KEGG工具有助于更深入地了解病毒蛋白功能和进化关系.
- 这项工作将病毒数据更有效地集成到KEGG中,推进基因组和蛋白质组研究.
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