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      Finding consensus stable local optimal structures for aligned RNA sequences and its application to discovering riboswitch elements.

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          Abstract

          Many non-coding RNAs (ncRNAs) can fold into alternate native structures and perform different biological functions. The computational prediction of an ncRNA's alternate native structures can be conducted by analysing the ncRNA's energy landscape. Previously, we have developed a computational approach, RNASLOpt, to predict alternate native structures for a single RNA. In this paper, in order to improve the accuracy of the prediction, we incorporate structural conservation information among a family of related ncRNA sequences to the prediction. We propose a comparative approach, RNAConSLOpt, to produce all possible consensus SLOpt stack configurations that are conserved on the consensus energy landscape of a family of related ncRNAs. Benchmarking tests show that RNAConSLOpt can reduce the number of candidate structures compared with RNASLOpt, and can predict ncRNAs' alternate native structures accurately. Moreover, an application of the proposed pipeline to bacteria in Bacillus genus has discovered several novel riboswitch candidates.

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          Author and article information

          Journal
          Int J Bioinform Res Appl
          International journal of bioinformatics research and applications
          Inderscience Publishers
          1744-5485
          1744-5485
          2014
          : 10
          : 4-5
          Affiliations
          [1 ] Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida 32816, USA.
          Article
          K5G0143J3L7H328X NIHMS604148
          10.1504/IJBRA.2014.062997
          4156590
          24989865
          27a2eb77-2864-4813-b915-587c39d2bcf0
          History

          non–coding RNAs,bioinformatics,bacteria,RNA stable local optimal structure,RNA sequence alignment,RNA energy landscape,RNA consensus secondary structures,Bacillus genus,riboswitch,ncRNA sequences

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