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TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots

We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. TT2NE is guaranteed to find the minimum free energy structure regardless of pseudoknot topology. This unique profici...

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Detalles Bibliográficos
Autores principales: Bon, Michaël, Orland, Henri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152363/
https://www.ncbi.nlm.nih.gov/pubmed/21593129
http://dx.doi.org/10.1093/nar/gkr240
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author Bon, Michaël
Orland, Henri
author_facet Bon, Michaël
Orland, Henri
author_sort Bon, Michaël
collection PubMed
description We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. TT2NE is guaranteed to find the minimum free energy structure regardless of pseudoknot topology. This unique proficiency is obtained at the expense of the maximum length of sequences that can be treated, but comparison with state-of-the-art algorithms shows that TT2NE significantly improves the quality of predictions. Analysis of TT2NE's incorrect predictions sheds light on the need to study how sterical constraints limit the range of pseudoknotted structures that can be formed from a given sequence. An implementation of TT2NE on a public server can be found at http://ipht.cea.fr/rna/tt2ne.php.
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spelling pubmed-31523632011-08-08 TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots Bon, Michaël Orland, Henri Nucleic Acids Res Methods Online We present TT2NE, a new algorithm to predict RNA secondary structures with pseudoknots. The method is based on a classification of RNA structures according to their topological genus. TT2NE is guaranteed to find the minimum free energy structure regardless of pseudoknot topology. This unique proficiency is obtained at the expense of the maximum length of sequences that can be treated, but comparison with state-of-the-art algorithms shows that TT2NE significantly improves the quality of predictions. Analysis of TT2NE's incorrect predictions sheds light on the need to study how sterical constraints limit the range of pseudoknotted structures that can be formed from a given sequence. An implementation of TT2NE on a public server can be found at http://ipht.cea.fr/rna/tt2ne.php. Oxford University Press 2011-08 2011-05-18 /pmc/articles/PMC3152363/ /pubmed/21593129 http://dx.doi.org/10.1093/nar/gkr240 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Bon, Michaël
Orland, Henri
TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title_full TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title_fullStr TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title_full_unstemmed TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title_short TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots
title_sort tt2ne: a novel algorithm to predict rna secondary structures with pseudoknots
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3152363/
https://www.ncbi.nlm.nih.gov/pubmed/21593129
http://dx.doi.org/10.1093/nar/gkr240
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