Study of RNA Secondary Structure Prediction Algorithms

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Abstract:

RNA secondary structure study is one of the most important fields in computational molecular biology. According to different conditions, RNA secondary structure prediction derives two ways. In the paper, the method to predict RNA secondary structure is introduced in two ways. It includes the mathematic models and main algorithms. The paper also points out the existing problems. The main development directions of RNA secondary structure prediction algorithm is also be indicated.

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Advanced Materials Research (Volumes 393-395)

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955-960

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November 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Furtig B , Richter C , Wohnert J , Schwalbe H: NMR spectroscopy of RNA[J]. Chembiochem, 2003, 4 (10): 936 - 962.

DOI: 10.1002/cbic.200300700

Google Scholar

[2] MOUNT D W. Bioinformatics [M ]. Beijing: Science Press, 2003: 210- 228.

Google Scholar

[3] David H Mathews, Jeffret Sabina, Michael Zuker, Douglas H Turner. Expand sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure [J]. Journal of Molecular Biology, 1999, 288 (5): 911 - 940.

DOI: 10.1006/jmbi.1999.2700

Google Scholar

[4] J E Tabaska, RB Cary, HN Gabow, GD Stormo. An RNA folding method capable of identifying pseudoknots and base triples[J] . Bioinformatics, 1998, 14 (8): 691 - 699.

DOI: 10.1093/bioinformatics/14.8.691

Google Scholar

[5] Xiaolu Huang, Hesham Ali. High sensitivity RNA pseudoknot prediction[J]. Nucleic Acids Research, 2007, 35 (2) : 656 - 663.

DOI: 10.1093/nar/gkl943

Google Scholar

[6] Huang Chun Hsiang, Lu Chin Lung, Chiu Hsien Tai. A heuristic approach for detecting RNA H-type pseudoknots[J]. Bioinformatics, 2005, 21 (17): 3501-3508.

DOI: 10.1093/bioinformatics/bti568

Google Scholar

[7] Tinoco I, Uhlenbeck O C, Levine M D. Estimation of secondary structure in ribonucleic acids [J] . Nature, 1971 , 230 (5293) : 362- 367.

DOI: 10.1038/230362a0

Google Scholar

[8] Mathews David H. Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization [J].RNA, 2004, 10(8): 1178 -1190.

DOI: 10.1261/rna.7650904

Google Scholar

[9] CHEN Xiang, BU Dong-Bo, ZHANG Fa, GAO Wen. A Local-stem-search Algorithm to Predict The RNA Secondary Structure[J], Progress in Biochemistry and Biophysics,2009, 36(1): 115~121.

DOI: 10.3724/sp.j.1206.2008.00329

Google Scholar

[10] Turner Douglas H, Mathews David H. NNDB: the nearest neighbor parameter database for predicting seability of nucleic acid secondary structure[J]. Nucleic Acids Reaearch, 2010, 38: D280-282.

DOI: 10.1093/nar/gkp892

Google Scholar

[11] Woese C. Pace N : The RNA World, Chap. Probing RNA Structure, Function and History by Comparative Analysis[M]. Cold Spring Harbor Laboratory Press, Cold Spring Harbor , NY; 1993. 91 - 117.

DOI: 10.1126/science.264.5164.1479

Google Scholar

[12] Sakakibara Y, Brown M, Hughey R, et al. St ochast ic context - free grammars for tRNA modeling[J]. Nucleic Acids Research, 1994, 22: 5112- 5120.

DOI: 10.1093/nar/22.23.5112

Google Scholar

[13] Durbin R, Eddy S R, Krogh A, Mit chison G J. Biological Sequence Analysis: Probabilist ic Models of Proteins and Nucleic Acids [M] . UK: Cambridge University Press, (1998).

DOI: 10.1017/cbo9780511790492

Google Scholar

[14] Knudsen B, Hein J. RNA secondary structure predict ion using stochasti c cont ext- free grammars and evolut ionary history[J] . Bioinformatics, 1999, 15: 446- 454.

DOI: 10.1093/bioinformatics/15.6.446

Google Scholar

[15] Knudsen B, Hein J. Pfold: RNA secondary structure predict ion using stochast ic context - free grammars [J] . Nucleic Acids Research, 2003, 13: 3423- 3428.

DOI: 10.1093/nar/gkg614

Google Scholar

[16] Ruan J, Stormo G D, Zhang W. An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots. Bioinformatics, 2004, 20(1): 58~66.

DOI: 10.1093/bioinformatics/btg373

Google Scholar

[17] Nebel M.E. Combinatorial properties of RNA secondary structures, J Comput Biol., 2002; 9: 541-73.

Google Scholar

[18] Li W.J., Wu J.J. Prediction of RNA Secondary Structure Based on Helical Regions Distribution[J], Bioinformatics, 1998; 14: 700-706.

DOI: 10.1093/bioinformatics/14.8.700

Google Scholar

[19] Van Bantenburg F.H.D., Gultyaev A.P., et al. An APL-programmed Genetic Algorithm for the Prediction of RNA Secondary Structure,J. theor. Biol., 1995; 174: 269-280.

DOI: 10.1006/jtbi.1995.0098

Google Scholar

[20] CAO Su-bing et al. Application of Genetic Algorithm in the Prediction of RNA Secondary Structure[J]. Journal of Anhui Agriculture Science. 2010, 38( 24) : 12933- 12934.

Google Scholar

[21] Ruan, J., G. Stormo and W. Zhang. An iterated loop matching approach to the Prediction of RNA secondary structures with pseudoknots[J]. Bioinformatics,2004(20): 58-66.

DOI: 10.1093/bioinformatics/btg373

Google Scholar

[22] Knudsen, B. and J. Hein. Pfold: RNA secondary structure Prediction using stochastic context-free grammars[J]. Nucleic Acids Research,2003(31): 3423-3428.

DOI: 10.1093/nar/gkg614

Google Scholar

[23] Knudsen B , Hein J . Pfold : RNA secondary structure prediction using stochastic context2free grammars [J] . Nucleic Acids Research , 2003 , 31 (13) : 3423 - 3428.

DOI: 10.1093/nar/gkg614

Google Scholar

[24] J ulien Allali , Marie2France Sagot . A new distance for high level RNA secondary structure comparison [J] . IEEE/ ACM Transactions on Computational Biology and Bioinformatics , 2005 , 2 (1) : 3 - 14.

DOI: 10.1109/tcbb.2005.2

Google Scholar

[25] Hochsmann M. et al. Local similarity of RNA secondary structures. In Proc of the IEEE Bioinformatics Conferenee,(2003).

Google Scholar

[26] Siebert,S. and R. Backofen. MARNA: multiple alignment and consensus structure prediction of RNAs based on sequence structure comparisons [J]. Bioinformatics,2005(21): 3352-3359.

DOI: 10.1093/bioinformatics/bti550

Google Scholar

[27] Sankoff D. Simultaneous solution of the RNA folding , alignment and protosequence problems [J] . SIAM J ournal on Applied Mathematics , 1985 , 45 (5) : 810 - 825.

DOI: 10.1137/0145048

Google Scholar

[28] Hofacker IL , Bernhart S , Stadler P. Alignment of RNA base pairing probability matrices [J] . Bioinformatics , 2004 , 20 (14) : 2222 - 2227.

DOI: 10.1093/bioinformatics/bth229

Google Scholar

[29] Mandal M, Breaker R. Gene regulation by riboswitches [J]. Nature Reviews Molecular Cell Biology , 2004 , 5(6) : 451 - 463.

DOI: 10.1038/nrm1403

Google Scholar