Bernhart Stephan H, Hofacker Ivo L
Department of Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria.
Brief Funct Genomic Proteomic. 2009 Nov;8(6):461-71. doi: 10.1093/bfgp/elp043.
Reliable structure prediction is a prerequisite for most types of bioinformatical analysis of RNA. Since the accuracy of structure prediction from single sequences is limited, one often resorts to computing the consensus structure for a set of related RNA sequences. Since functionally important RNA structures are expected to evolve much more slowly than the underlying sequences, the pattern of sequence (co-)variation can be exploited to dramatically improve structure prediction. Since a conserved common structure is only expected when the RNA structure is under selective pressure, consensus structure prediction also provides an ideal starting point for the de novo detection of structured non-coding RNAs. Here, we review different strategies for the prediction of consensus secondary structures, and show how these approaches can be used to predict non-coding RNA genes.
可靠的结构预测是大多数类型RNA生物信息学分析的先决条件。由于从单序列进行结构预测的准确性有限,人们常常求助于计算一组相关RNA序列的共有结构。由于功能上重要的RNA结构预计比其基础序列进化得慢得多,因此可以利用序列(共)变异模式来显著提高结构预测的准确性。由于只有当RNA结构受到选择压力时才会出现保守的共同结构,共有结构预测也为从头检测结构化非编码RNA提供了理想的起点。在这里,我们综述了预测共有二级结构的不同策略,并展示了如何使用这些方法来预测非编码RNA基因。