dc.contributor.author | Achar, Avinash | |
dc.contributor.author | Sætrom, Pål | |
dc.date.accessioned | 2015-11-03T09:50:11Z | |
dc.date.accessioned | 2015-12-21T12:14:31Z | |
dc.date.available | 2015-11-03T09:50:11Z | |
dc.date.available | 2015-12-21T12:14:31Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Biology Direct 2015, 10(1) | nb_NO |
dc.identifier.issn | 1745-6150 | |
dc.identifier.uri | http://hdl.handle.net/11250/2368696 | |
dc.description.abstract | Genomic 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.iso | eng | nb_NO |
dc.publisher | BioMed Central | nb_NO |
dc.title | RNA motif discovery: a computational overview | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | en_GB |
dc.date.updated | 2015-11-03T09:50:11Z | |
dc.source.volume | 10 | nb_NO |
dc.source.journal | Biology Direct | nb_NO |
dc.source.issue | 1 | nb_NO |
dc.identifier.doi | 10.1186/s13062-015-0090-5 | |
dc.identifier.cristin | 1281015 | |
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 |