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RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming
- Source :
- Bioinformatics
- Publication Year :
- 2010
- Publisher :
- Oxford University Press, 2010.
-
Abstract
- 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.
- Subjects :
- Statistics and Probability
Source code
Theoretical computer science
Computer science
media_common.quotation_subject
Protein and Nucleotide Structure
Biochemistry
Eccb 2010 Conference Proceedings September 26 to September 29, 2010, Ghent, Belgium
Software
Gene expression
Binding site
Molecular Biology
Integer programming
Base Pairing
Mathematical Computing
media_common
Class (computer programming)
Binding Sites
Base Sequence
business.industry
RNA
Original Papers
Computer Science Applications
Computational Mathematics
Range (mathematics)
Computational Theory and Mathematics
Key (cryptography)
Nucleic Acid Conformation
business
Algorithms
Subjects
Details
- Language :
- English
- ISSN :
- 13674811 and 13674803
- Volume :
- 26
- Issue :
- 18
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....4810e41db3c78d2759b25ab354c5705c