Rsite2: an efficient computational method to predict the functional sites of noncoding RNAs

被引:23
|
作者
Zeng, Pan [1 ]
Cui, Qinghua [1 ]
机构
[1] Peking Univ, Sch Basic Med Sci, Ctr Noncoding RNA Med, Dept Biomed Informat, Beijing 100191, Peoples R China
来源
SCIENTIFIC REPORTS | 2016年 / 6卷
基金
国家高技术研究发展计划(863计划);
关键词
HUMAN MICRORNA; DATABASE; IDENTIFICATION; RESIDUES; PRINCIPLES; PROSITE; SHAPE;
D O I
10.1038/srep19016
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Noncoding RNAs (ncRNAs) represent a big class of important RNA molecules. Given the large number of ncRNAs, identifying their functional sites is becoming one of the most important topics in the post-genomic era, but available computational methods are limited. For the above purpose, we previously presented a tertiary structure based method, Rsite, which first calculates the distance metrics defined in Methods with the tertiary structure of an ncRNA and then identifies the nucleotides located within the extreme points in the distance curve as the functional sites of the given ncRNA. However, the application of Rsite is largely limited because of limited RNA tertiary structures. Here we present a secondary structure based computational method, Rsite2, based on the observation that the secondary structure based nucleotide distance is strongly positively correlated with that derived from tertiary structure. This makes it reasonable to replace tertiary structure with secondary structure, which is much easier to obtain and process. Moreover, we applied Rsite2 to three ncRNAs (tRNA (Lys), Diels-Alder ribozyme, and RNase P) and a list of human mitochondria transcripts. The results show that Rsite2 works well with nearly equivalent accuracy as Rsite but is much more feasible and efficient. Finally, a web-server, the source codes, and the dataset of Rsite2 are available at http://www.cuialb.cn/rsite2.
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页数:9
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