Rfold: an exact algorithm for computing local base pairing probabilities

Motivation: Base pairing probability matrices have been frequently used for the analyses of structural RNA sequences. Recently, there has been a growing need for computing these probabilities for long DNA sequences by constraining the maximal span of base pairs to a limited value. However, none of t...

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Vydáno v:Bioinformatics Ročník 24; číslo 3; s. 367 - 373
Hlavní autoři: Kiryu, Hisanori, Kin, Taishin, Asai, Kiyoshi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Oxford University Press 01.02.2008
Oxford Publishing Limited (England)
Témata:
Algorithms
Base Pairing - genetics
Base Sequence
Bioinformatics
Biological and medical sciences
Computer Simulation
Fundamental and applied biological sciences. Psychology
General aspects
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Chemical
Models, Genetic
Models, Statistical
Molecular Sequence Data
RNA, Untranslated - chemistry
RNA, Untranslated - genetics
Sequence Analysis, RNA - methods
Software
Probability
Algorithm
Pairing
Bioinformatics
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Shrnutí:Motivation: Base pairing probability matrices have been frequently used for the analyses of structural RNA sequences. Recently, there has been a growing need for computing these probabilities for long DNA sequences by constraining the maximal span of base pairs to a limited value. However, none of the existing programs can exactly compute the base pairing probabilities associated with the energy model of secondary structures under such a constraint. Results: We present an algorithm that exactly computes the base pairing probabilities associated with the energy model under the constraint on the maximal span W of base pairs. The complexity of our algorithm is given by in time and in memory, where N is the sequence length. We show that our algorithm has a higher sensitivity to the true base pairs as compared to that of RNAplfold. We also present an algorithm that predicts a mutually consistent set of local secondary structures by maximizing the expected accuracy function. The comparison of the local secondary structure predictions with those of RNALfold indicates that our algorithm is more accurate. Our algorithms are implemented in the software named ‘Rfold.’ Availability: The C++ source code of the Rfold software and the test dataset used in this study are available at http://www.ncrna.org/software/Rfold/ Contact: kiryu-h@aist.go.jp Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliografie:Associate Editor: Dmitrij Frishman
To whom correspondence should be addressed.
ArticleID:btm591
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btm591