Abstract
Pseudoknotted RNA structures are much more difficult to predict than non-pseudoknotted RNA structures both from the computational viewpoint and from the practical viewpoint. This is in part due to the unavailability of an exact energy model for pseudoknots, structural complexity of pseudoknots, and to the high time complexity of predicting algorithms. Therefore, existing approaches to predicting pseudoknotted RNA structures mostly focus on so-called H-type pseudoknots of small RNAs. We have developed a heuristic energy model and genetic algorithm for predicting RNA structures with various types of pseudoknots, including H-type pseudoknots. This paper analyzes the predictions by a genetic algorithm and compares the predictions to those by a dynamic programming algorithm.
This work has been supported by the Korea Science and Engineering Foundation (KOSEF) under grant R05-2001-000-01037-0.
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References
Lee, D., Han, K.: Prediction of RNA pseudoknots–comparative study of genetic algorithms. Genome Informatics 13, 414–415 (2002)
Lee, D., Han, K.: A Genetic Algorithm for Predicting RNA Pseudoknot Structures. In: Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Gorbachev, Y.E., Dongarra, J., Zomaya, A.Y. (eds.) ICCS 2003. LNCS, vol. 2659, pp. 130–139. Springer, Heidelberg (2003)
Gultyaev, A.P., van Batenburg, F.H.D., Pleij, C.W.A.: The computer simulation of RNA folding pathways using a genetic algorithm. Journal of Molecular Biology 250, 37–51 (1995)
Shapiro, B.A., Wu, J.C.: An annealing mutation operator in the genetic algorithms for RNA folding. Computer Applications in the Biosciences 12, 171–180 (1996)
Shapiro, B.A., Wu, J.C., Bengali, D., Potts, M.J.: The massively parallel genetic algorithm for RNA folding: MIMD implementation and population variation. Bioinformatics 17, 137–148 (2001)
Benedetti, G., Morosetti, S.: A genetic algorithm to search for optimal and suboptimal RNA secondary structures. Biophysical Chemistry 55, 253–259 (1995)
Shapiro, B.A., Navetta, J.: A massively parallel genetic algorithm for RNA secondary structure prediction. Journal of Supercomputing 8, 195–207 (1994)
Pleij, C.W.A.: Pseudoknots: a new motif in the RNA game. Trends in Biochemical Sciences 15, 143–147 (1990)
van Batenburg, F.H.D., Gultyaev, A.P., Pleij, C.W.A., Ng, J., Olihoek, J.: PseudoBase: a database with RNA pseudoknots. Nucliec Acids Res. 28, 201–204 (2000)
Han, K., Byun, Y.: PseudoViewer2: visualization of RNA pseudoknots of any type. Nucleic Acids Res. 31, 3432–3440 (2003)
Deiman, B.A., Pleij, C.W.A.: A vital fearue in viral RNA. Seminars in Virology 8, 166–175 (1997)
Einvik, C., Nielsen, H., Nour, R., Johansen, S.: Flanking sequences with an essential role in hydrolysis of a self-cleaving group l-like ribozyme. Nucleic Acids Res. 28, 2194–2200 (2000)
Abrahams, J.P., van den Berg, M., van Batenburg, E., Pleij, C.: Prediction of RNA secondary structure, including pseudoknotting, by computer simulation. Nucleic Acids Res. 18, 3035–3044 (1990)
Han, K., Lee, Y., Kim, W.: PseudoViewer: automatic visualization of RNA pseudoknots. Bioinformatics 18, S321–S328 (2002)
Rivas, E., Eddy, S.R.: A dynamic programming algorithm for RNA structure prediction including pseudoknots. Journal of Molecular Biology 285, 2053–2068 (1999)
Akutsu, T.: Dynamic programming algorithm for RNA secondary structure prediction with pseudoknots. Discrete Applied Mathematics 104, 45–62 (2000)
Reeder, J., Giegerich, R.: http://bibiserv.techfak.uni-bielefeld.de/pknotsrg/
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Lee, D., Han, K. (2003). A Genetic Algorithm for Inferring Pseudoknotted RNA Structures from Sequence Data. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_31
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DOI: https://doi.org/10.1007/978-3-540-39644-4_31
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