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dc.contributor.authorAchar, Avinash
dc.contributor.authorSætrom, Pål
dc.date.accessioned2015-11-03T09:50:11Z
dc.date.accessioned2015-12-21T12:14:31Z
dc.date.available2015-11-03T09:50:11Z
dc.date.available2015-12-21T12:14:31Z
dc.date.issued2015
dc.identifier.citationBiology Direct 2015, 10(1)nb_NO
dc.identifier.issn1745-6150
dc.identifier.urihttp://hdl.handle.net/11250/2368696
dc.description.abstractGenomic studies have greatly expanded our knowledge of structural non-coding RNAs (ncRNAs). These RNAs fold into characteristic secondary structures and perform specific-structure dependent biological functions. Hence RNA secondary structure prediction is one of the most well studied problems in computational RNA biology. Comparative sequence analysis is one of the more reliable RNA structure prediction approaches as it exploits information of multiple related sequences to infer the consensus secondary structure. This class of methods essentially learns a global secondary structure from the input sequences. In this paper, we consider the more general problem of unearthing common local secondary structure based patterns from a set of related sequences. The input sequences for example could correspond to 3 ′ or 5 ′ untranslated regions of a set of orthologous genes and the unearthed local patterns could correspond to regulatory motifs found in these regions. These sequences could also correspond to in vitro selected RNA, genomic segments housing ncRNA genes from the same family and so on. Here, we give a detailed review of the various computational techniques proposed in literature attempting to solve this general motif discovery problem. We also give empirical comparisons of some of the current state of the art methods and point out future directions of research.nb_NO
dc.language.isoengnb_NO
dc.publisherBioMed Centralnb_NO
dc.titleRNA motif discovery: a computational overviewnb_NO
dc.typeJournal articlenb_NO
dc.typePeer revieweden_GB
dc.date.updated2015-11-03T09:50:11Z
dc.source.volume10nb_NO
dc.source.journalBiology Directnb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.1186/s13062-015-0090-5
dc.identifier.cristin1281015
dc.description.localcode© 2015 Achar and Sætrom. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.nb_NO


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