Discovering common structural motifs from SSU 16 S ribosomal RNA secondary structures

Hsien-Da Huang, Shu-Fen Fang, Jorng-Tzong Horng, Cheng-Yan Kao
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Abstract

Some structural motifs, like tetra-loops, in ribosomal RNA are known to functionally implicate in virtually every aspect of protein synthesis. Our aim in this study is to discover common structural motifs (CSMs), which are related to specific domains or functions, within the secondary structures of ribosomal RNAs in a data set constructed. After applying data mining techniques to mine the common structural motifs, a machine learning approach is used to find significant discriminating common structural motifs from groups of organisms. By applying to several data sets constructed in this study, it suggests that the CSMs can provide effective information to classify organisms and help biologists understand the functions of ribosomal RNA. From the experiments of the classification of organisms and the construction of phylogenetic trees by CSMs mined, we find our approach is promising.
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从SSU 16s核糖体RNA二级结构中发现共同结构基序
核糖体RNA中的一些结构基序,如四环,在功能上几乎涉及蛋白质合成的各个方面。本研究的目的是在构建的数据集中发现核糖体rna二级结构中与特定结构域或功能相关的共同结构基序(csm)。在应用数据挖掘技术挖掘共同结构基序之后,使用机器学习方法从生物体群体中找到具有显著区别的共同结构基序。通过应用于本研究构建的多个数据集,表明csm可以为生物分类提供有效的信息,并帮助生物学家了解核糖体RNA的功能。从利用csm进行生物分类和构建系统发育树的实验来看,我们的方法是很有前途的。
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