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Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization
Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moder...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808183/ https://www.ncbi.nlm.nih.gov/pubmed/20140072 |
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author | Spirollari, Junilda Wang, Jason T.L. Zhang, Kaizhong Bellofatto, Vivian Park, Yongkyu Shapiro, Bruce A. |
author_facet | Spirollari, Junilda Wang, Jason T.L. Zhang, Kaizhong Bellofatto, Vivian Park, Yongkyu Shapiro, Bruce A. |
author_sort | Spirollari, Junilda |
collection | PubMed |
description | Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http://datalab.njit.edu/biology/RSpredict. |
format | Text |
id | pubmed-2808183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-28081832010-02-04 Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization Spirollari, Junilda Wang, Jason T.L. Zhang, Kaizhong Bellofatto, Vivian Park, Yongkyu Shapiro, Bruce A. Bioinform Biol Insights Original Research Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http://datalab.njit.edu/biology/RSpredict. Libertas Academica 2009-06-03 /pmc/articles/PMC2808183/ /pubmed/20140072 Text en Copyright © 2009 The authors. https://creativecommons.org/licenses/by/2.0/This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ). |
spellingShingle | Original Research Spirollari, Junilda Wang, Jason T.L. Zhang, Kaizhong Bellofatto, Vivian Park, Yongkyu Shapiro, Bruce A. Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title | Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title_full | Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title_fullStr | Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title_full_unstemmed | Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title_short | Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization |
title_sort | predicting consensus structures for rna alignments via pseudo-energy minimization |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808183/ https://www.ncbi.nlm.nih.gov/pubmed/20140072 |
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