%0 Journal Article
%T RNA Structural Homology Search with a Succinct Stochastic Grammar Model
%A Ying-Lei Song
%A Ji-Zhen Zhao
%A Chun-Mei Liu
%A Kan Liu
%A Russell Malmberg
%A Li-Ming Cai
%A <br>Ying-Lei Song
%A Ji-Zhen Zhao
%A Chun-MeiLiu
%A Kan Liu
%A Russell Malmberg
%A and Li-MingCai
%J 计算机科学技术学报
%D 2005
%I 
%X An increasing number of structural homology search tools, mostly based on profile stochastic context-free grammars (SCFGs) have been recently developed for the non-coding RNA gene identification. SCFGs can include statistical biases that often occur in RNA sequences, necessary to profile specific RNA structures for structural homology search. In this paper, a succinct stochastic grammar model is introduced for RNA that has competitive search effectiveness. More importantly, the profiling model can be easily extended to include pseudoknots, structures that are beyond the capability of profile SCFGs. In addition, the model allows heuristics to be exploited, resulting in a significant speed-up for the CYK algorithm-based search.
%K RNA structural homology search
%K stochastic context-free grammar (SCPG)
%K structure-sequence alignment
%K pseudoknot<br>RNA
%K 核糖核酸
%K SCFGs
%K 结构
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=F57FEF5FAEE544283F43708D560ABF1B&aid=8D64527311FC88B8A2A41E0A361F7EFA&yid=2DD7160C83D0ACED&vid=A04140E723CB732E&iid=E158A972A605785F&sid=B1989ED92BA7E896&eid=1A033C02510EFBE6&journal_id=1000-9000&journal_name=计算机科学技术学报&referenced_num=0&reference_num=23