Cargando…

RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming

Motivation: Considerable attention has been focused on predicting RNA–RNA interaction since it is a key to identifying possible targets of non-coding small RNAs that regulate gene expression post-transcriptionally. A number of computational studies have so far been devoted to predicting joint second...

Descripción completa

Detalles Bibliográficos
Autores principales: Kato, Yuki, Sato, Kengo, Hamada, Michiaki, Watanabe, Yoshihide, Asai, Kiyoshi, Akutsu, Tatsuya
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935440/
https://www.ncbi.nlm.nih.gov/pubmed/20823308
http://dx.doi.org/10.1093/bioinformatics/btq372
_version_ 1782186403590832128
author Kato, Yuki
Sato, Kengo
Hamada, Michiaki
Watanabe, Yoshihide
Asai, Kiyoshi
Akutsu, Tatsuya
author_facet Kato, Yuki
Sato, Kengo
Hamada, Michiaki
Watanabe, Yoshihide
Asai, Kiyoshi
Akutsu, Tatsuya
author_sort Kato, Yuki
collection PubMed
description Motivation: Considerable attention has been focused on predicting RNA–RNA interaction since it is a key to identifying possible targets of non-coding small RNAs that regulate gene expression post-transcriptionally. A number of computational studies have so far been devoted to predicting joint secondary structures or binding sites under a specific class of interactions. In general, there is a trade-off between range of interaction type and efficiency of a prediction algorithm, and thus efficient computational methods for predicting comprehensive type of interaction are still awaited. Results: We present RactIP, a fast and accurate prediction method for RNA–RNA interaction of general type using integer programming. RactIP can integrate approximate information on an ensemble of equilibrium joint structures into the objective function of integer programming using posterior internal and external base-paring probabilities. Experimental results on real interaction data show that prediction accuracy of RactIP is at least comparable to that of several state-of-the-art methods for RNA–RNA interaction prediction. Moreover, we demonstrate that RactIP can run incomparably faster than competitive methods for predicting joint secondary structures. Availability: RactIP is implemented in C++, and the source code is available at http://www.ncrna.org/software/ractip/ Contact: ykato@kuicr.kyoto-u.ac.jp; satoken@k.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.
format Text
id pubmed-2935440
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-29354402010-09-08 RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming Kato, Yuki Sato, Kengo Hamada, Michiaki Watanabe, Yoshihide Asai, Kiyoshi Akutsu, Tatsuya Bioinformatics Eccb 2010 Conference Proceedings September 26 to September 29, 2010, Ghent, Belgium Motivation: Considerable attention has been focused on predicting RNA–RNA interaction since it is a key to identifying possible targets of non-coding small RNAs that regulate gene expression post-transcriptionally. A number of computational studies have so far been devoted to predicting joint secondary structures or binding sites under a specific class of interactions. In general, there is a trade-off between range of interaction type and efficiency of a prediction algorithm, and thus efficient computational methods for predicting comprehensive type of interaction are still awaited. Results: We present RactIP, a fast and accurate prediction method for RNA–RNA interaction of general type using integer programming. RactIP can integrate approximate information on an ensemble of equilibrium joint structures into the objective function of integer programming using posterior internal and external base-paring probabilities. Experimental results on real interaction data show that prediction accuracy of RactIP is at least comparable to that of several state-of-the-art methods for RNA–RNA interaction prediction. Moreover, we demonstrate that RactIP can run incomparably faster than competitive methods for predicting joint secondary structures. Availability: RactIP is implemented in C++, and the source code is available at http://www.ncrna.org/software/ractip/ Contact: ykato@kuicr.kyoto-u.ac.jp; satoken@k.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2010-09-15 2010-09-04 /pmc/articles/PMC2935440/ /pubmed/20823308 http://dx.doi.org/10.1093/bioinformatics/btq372 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Eccb 2010 Conference Proceedings September 26 to September 29, 2010, Ghent, Belgium
Kato, Yuki
Sato, Kengo
Hamada, Michiaki
Watanabe, Yoshihide
Asai, Kiyoshi
Akutsu, Tatsuya
RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title_full RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title_fullStr RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title_full_unstemmed RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title_short RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
title_sort ractip: fast and accurate prediction of rna-rna interaction using integer programming
topic Eccb 2010 Conference Proceedings September 26 to September 29, 2010, Ghent, Belgium
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935440/
https://www.ncbi.nlm.nih.gov/pubmed/20823308
http://dx.doi.org/10.1093/bioinformatics/btq372
work_keys_str_mv AT katoyuki ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming
AT satokengo ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming
AT hamadamichiaki ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming
AT watanabeyoshihide ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming
AT asaikiyoshi ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming
AT akutsutatsuya ractipfastandaccuratepredictionofrnarnainteractionusingintegerprogramming