article

SARNA-Predict: Accuracy Improvement of RNA Secondary Structure Prediction Using Permutation-Based Simulated Annealing

Authors:

Herbert H. Tsang,

Kay C. WieseAuthors Info & Claims

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 7, Issue 4

Pages 727 - 740

https://doi.org/10.1109/TCBB.2008.97

Published: 01 October 2010 Publication History

Abstract

Ribonucleic acid (RNA), a single-stranded linear molecule, is essential to all biological systems. Different regions of the same RNA strand will fold together via base pair interactions to make intricate secondary and tertiary structures that guide crucial homeostatic processes in living organisms. Since the structure of RNA molecules is the key to their function, algorithms for the prediction of RNA structure are of great value. In this article, we demonstrate the usefulness of SARNA{\hbox{-}}Predict, an RNA secondary structure prediction algorithm based on Simulated Annealing (SA). A performance evaluation of SARNA{\hbox{-}}Predict in terms of prediction accuracy is made via comparison with eight state-of-the-art RNA prediction algorithms: mfold, Pseudoknot (pknotsRE), NUPACK, pknotsRG{\hbox{-}}mfe, Sfold, HotKnots, ILM, and STAR. These algorithms are from three different classes: heuristic,dynamic programming, and statistical sampling techniques. An evaluation for the performance of SARNA{\hbox{-}}Predict in terms of prediction accuracy was verified with native structures. Experiments on 33 individual known structures from eleven RNA classes (tRNA, viral RNA, antigenomic HDV, telomerase RNA, tmRNA, rRNA, RNaseP, 5S rRNA, Group I intron 23S rRNA, Group I intron 16S rRNA, and 16S rRNA) were performed. The results presented in this paper demonstrate that SARNA{\hbox{-}}Predict can out-perform other state-of-the-art algorithms in terms of prediction accuracy. Furthermore, there is substantial improvement of prediction accuracy by incorporating a more sophisticated thermodynamic model (efn2).

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Cited By

Kai ZYulin L(2018)A Novel Efficient Simulated Annealing Algorithm for the RNA Secondary Structure Predicting with PseudoknotsIntelligent Computing Theories and Application10.1007/978-3-319-95933-7_44(365-370)Online publication date: 15-Aug-2018
https://dl.acm.org/doi/10.1007/978-3-319-95933-7_44
Tsang HWiese K(2015)A permutation based simulated annealing algorithm to predict pseudoknotted RNA secondary structuresInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2015.07193811:5(375-396)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1504/IJBRA.2015.071938
Ray SPal S(2013)RNA Secondary Structure Prediction Using Soft ComputingIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2012.15910:1(2-17)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1109/TCBB.2012.159
Show More Cited By

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SARNA-Predict: Accuracy Improvement of RNA Secondary Structure Prediction Using Permutation-Based Simulated Annealing
1. Applied computing
  1. Life and medical sciences

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cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics

IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume 7, Issue 4

October 2010

203 pages

ISSN:1545-5963

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 October 2010

Published in TCBB Volume 7, Issue 4

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Cited By

Kai ZYulin L(2018)A Novel Efficient Simulated Annealing Algorithm for the RNA Secondary Structure Predicting with PseudoknotsIntelligent Computing Theories and Application10.1007/978-3-319-95933-7_44(365-370)Online publication date: 15-Aug-2018
https://dl.acm.org/doi/10.1007/978-3-319-95933-7_44
Tsang HWiese K(2015)A permutation based simulated annealing algorithm to predict pseudoknotted RNA secondary structuresInternational Journal of Bioinformatics Research and Applications10.1504/IJBRA.2015.07193811:5(375-396)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1504/IJBRA.2015.071938
Ray SPal S(2013)RNA Secondary Structure Prediction Using Soft ComputingIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2012.15910:1(2-17)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1109/TCBB.2012.159
Tsang HDai DRanka SKahveci TSingh M(2012)RNA-DVProceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine10.1145/2382936.2383036(601-603)Online publication date: 7-Oct-2012
https://dl.acm.org/doi/10.1145/2382936.2383036

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