Abstract
Although many RNA molecules contain pseudoknots, computational prediction of pseudoknotted RNA structure is still in its infancy due to high running time and space consumption implied by the dynamic programming formulations of the problem. In this paper, we introduce sparsification to significantly speedup the dynamic programming approaches for pseudoknotted RNA structure prediction, which also lower the space requirements. Although sparsification has been applied to a number of RNA-related structure prediction problems in the past few years, we provide the first application of sparsification to pseudoknotted RNA structure prediction specifically and to handling gapped fragments more generally - which has a much more complex recursive structure than other problems to which sparsification has been applied. We show that sparsification, when applied to the fastest, as well as the most general pseudoknotted structure prediction methods available, - respectively the Reeder-Giegerich algorithm and the Rivas-Eddy algorithm - reduces the number of ”candidate” substructures to be considered significantly. In fact, experimental results on the sparsified Reeder-Giegerich algorithm suggest a linear speedup over the unsparsified implementation.
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References
Sharp, P.A.: The centrality of RNA. Cell 136(4), 577–580 (2009)
Amaral, P.P., Dinger, M.E., Mercer, T.R., Mattick, J.S.: The eukaryotic genome as an RNA machine. Science 319(5871), 1787–1789 (2008)
Washietl, S., Pedersen, J.S., Korbel, J.O., Stocsits, C., Gruber, A.R., Hackermuller, J., Hertel, J., Lindemeyer, M., Reiche, K., Tanzer, A., Ucla, C., Wyss, C., Antonarakis, S.E., Denoeud, F., Lagarde, J., Drenkow, J., Kapranov, P., Gingeras, T.R., Guigo, R., Snyder, M., Gerstein, M.B., Reymond, A., Hofacker, I.L., Stadler, P.F.: Structured RNAs in the ENCODE selected regions of the human genome. Genome Res. 17(6), 852–864 (2007)
Mattick, J.S., Makunin, I.V.: Non-coding RNA. Hum. Mol. Genet. 15 Spec No. 1, R17–R29 (2006)
Staple, D.W., Butcher, S.E.: Pseudoknots: RNA structures with diverse functions. PLoS Biol. 3(6), e213 (2005)
Xayaphoummine, A., Bucher, T., Thalmann, F., Isambert, H.: Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations. Proc. Natl. Acad. Sci. USA 100(26), 15310–15315 (2003)
Lyngso, R.B., Pedersen, C.N.S.: Pseudoknots in RNA secondary structures. In: Proc. of the Fourth Annual International Conferences on Computational Molecular Biology (RECOMB 2000). ACM Press, New York (2000) (BRICS Report Series RS-00-1)
Rivas, E., Eddy, S.R.: A dynamic programming algorithm for RNA structure prediction including pseudoknots. Journal of Molecular Biology 285(5), 2053–2068 (1999)
Uemura, Y., Hasegawa, A., Kobayashi, S., Yokomori, T.: Tree adjoining grammars for RNA structure prediction. Theoretical Computer Science 210, 277–303 (1999) (Paper as Print Copy)
Akutsu, T.: Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots. Discrete Applied Mathematics 104, 45–62 (2000)
Deogun, J.S., Donis, R., Komina, O., Ma, F.: RNA secondary structure prediction with simple pseudoknots. In: APBC 2004: Proceedings of the second conference on Asia-Pacific bioinformatics, pp. 239–246. Australian Computer Society, Inc., Darlinghurst (2004)
Dirks, R.M., Pierce, N.A.: A partition function algorithm for nucleic acid secondary structure including pseudoknots. J. Comput. Chem. 24(13), 1664–1677 (2003)
Reeder, J., Giegerich, R.: Design, implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics. BMC Bioinformatics 5, 104 (2004)
Condon, A., Davy, B., Rastegari, B., Zhao, S., Tarrant, F.: Classifying RNA pseudoknotted structures. Theoretical Computer Science 320(1), 35–50 (2004)
Möhl, M., Will, S., Backofen, R.: Lifting prediction to alignment of RNA pseudoknots. Journal of Computational Biology (2010) (accepted)
Wexler, Y., Zilberstein, C.B.Z., Ziv-Ukelson, M.: A study of accessible motifs and rna folding complexity. In: Apostolico, A., Guerra, C., Istrail, S., Pevzner, P.A., Waterman, M.S. (eds.) RECOMB 2006. LNCS (LNBI), vol. 3909, pp. 473–487. Springer, Heidelberg (2006)
Backofen, R., Tsur, D., Zakov, S., Ziv-Ukelson, M.: Sparse RNA folding: Time and space efficient algorithms. In: Kucherov, G., Ukkonen, E. (eds.) CPM 2009. LNCS, vol. 5577, pp. 249–262. Springer, Heidelberg (2009)
Ziv-Ukelson, M., Gat-Viks, I., Wexler, Y., Shamir, R.: A faster algorithm for RNA co-folding. In: Crandall, K.A., Lagergren, J. (eds.) WABI 2008. LNCS (LNBI), vol. 5251, pp. 174–185. Springer, Heidelberg (2008)
Salari, R., Möhl, M., Will, S., Sahinalp, S.C., Backofen, R.: Time and space efficient RNA-RNA interaction prediction via sparse folding. In: Berger, B. (ed.) RECOMB 2010. LNCS, vol. 6044, pp. 473–490. Springer, Heidelberg (2010)
van Batenburg, F.H., Gultyaev, A.P., Pleij, C.W., Ng, J., Oliehoek, J.: Pseudobase: a database with RNA pseudoknots. Nucleic Acids Research 28(1), 201–204 (2000)
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Möhl, M., Salari, R., Will, S., Backofen, R., Sahinalp, S.C. (2010). Sparsification of RNA Structure Prediction Including Pseudoknots. In: Moulton, V., Singh, M. (eds) Algorithms in Bioinformatics. WABI 2010. Lecture Notes in Computer Science(), vol 6293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15294-8_4
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DOI: https://doi.org/10.1007/978-3-642-15294-8_4
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