Abstract
The lattice approach to biological structural analysis was made popular by the HP model for protein folding, but had not been used previously for RNA secondary structure prediction. We introduce the Delta toolset for the structural analysis of biological sequences on a 3D triangular lattice. The Delta toolset includes a proof-of-concept RNA folding program that is both fast and accurate in predicting the secondary structures with pseudoknots of short RNA sequences.
Supported by Utah State University research funds A13501 and A14766.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Abrahams, J.P., et al.: Prediction of RNA secondary structure, including pseudoknotting, by computer simulation. Nucleic Acids Research 18(10), 3035–3044 (1990)
Agarwala, R., et al.: Local rules for protein folding on a triangular lattice and generalized hydrophobicity in the HP model. In: Proceedings of the 8th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’97), pp. 390–399 (1997)
Akutsu, T.: Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots. Discrete Applied Mathematics 104(1-3), 45–62 (2000)
van Batenburg, F.H.D., Gultyaev, A.P., Pleij, C.W.A.: An APL-programmed genetic algorithm for the prediction of RNA secondary structure. Journal of Theoretical Biology 174(3), 269–280 (1995)
van Batenburg, F.H.D., et al.: Pseudobase: a database with RNA pseudoknots. Nucleic Acids Research 28(1), 201–204 (2000)
Berger, B., Leighton, T.: Protein folding in the hydrophobic-hydrophilic (HP) model is NP-complete. In: Proceedings of the 2nd Conference on Computational Molecular Biology (RECOMB’98), pp. 30–39 (1998)
Crescenzi, P., et al.: On the complexity of protein folding. In: Proceedings of the 2nd Conference on Computational Molecular Biology (RECOMB’98), pp. 61–62 (1998) and in: Proceedings of the 30th Annual ACM Symposium on Theory of Computing (STOC’98), pp. 597–603 (1998)
Crochemore, M., et al.: Approximating the 2-interval pattern problem. In: Brodal, G.S., Leonardi, S. (eds.) ESA 2005. LNCS, vol. 3669, pp. 426–437. Springer, Heidelberg (2005)
Deogun, J.S., et al.: RNA secondary structure prediction with simple pseudoknots. In: Proceedings of the 2nd Asia-Pacific Bioinformatics Conference (APBC’04), pp. 239–246 (2004)
Dill, K.A.: Theory for the folding and stability of globular proteins. Biochemistry 24(6), 1501–1509 (1985)
Dill, K.A.: Dominant forces in protein folding. Biochemistry 29, 7133–7155 (1990)
Eddy, S.R.: How do RNA folding algorithms work? Nature Biotechnology 22(11), 1457–1458 (2004)
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(1), 37–51 (1995)
Hart, W.E., Istrail, S.: Fast protein folding in the hydrophobic-hydrophilic model within three-eights of optimal. In: Proc. 27th Annual ACM Symposium on Theory of Computing (STOC’95), pp. 157–168 (1995)
Hofacker, I.L., et al.: Fast folding and comparison of RNA secondary structures. Monatshefte für Chemie 125(2), 167–188 (1994)
Ieong, S., et al.: Predicting RNA secondary structure with arbitrary pseudoknots by maximizing the number of stacking pairs. Journal of Computational Biology 10(6), 981–995 (2003)
Jiang, M.: A 2-approximation for the preceding-and-crossing structured 2-interval pattern problem. Journal of Combinatorial Optimization, Special Issue on Bioinformatics, to appear
Jiang, M.: Improved approximation algorithms for predicting RNA secondary structures with arbitrary pseudoknots. In: Kao, M.-Y., Li, X.-Y. (eds.) AAIM 2007. LNCS, vol. 4508, pp. 399–410. Springer, Heidelberg (2007)
Jiang, M., Zhu, B.: Protein folding on the hexagonal lattice in the HP model. Journal of Bioinformatics and Computational Biology 3(1), 19–34 (2005)
Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983)
Lesh, N., Mitzenmacher, M., Whiteslides, S.: A complete and effective move set for simplified protein folding. In: Proceedings of the 7th Annual International Conference on Computational Molecular Biology (RECOMB’03), pp. 188–195 (2003)
Lyngsø, R.B.: Complexity of pseudoknot prediction in simple models. In: Díaz, J., et al. (eds.) ICALP 2004. LNCS, vol. 3142, pp. 919–931. Springer, Heidelberg (2004)
Lyngsø, R.B., Pedersen, C.N.S.: RNA pseudoknot prediction in energy-based models. Journal of Computational Biology 7(3-4), 409–427 (2000)
Lyngsø, R.B., Zuker, M., Pedersen, C.N.S.: Fast evaluation of interval loops in RNA secondary structure prediction. Bioinformatics 15(6), 440–445 (1999)
Mauri, G., Pavesi, G., Piccolboni, A.: Approximation algorithms for protein folding prediction. In: Proceedings of the 10th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’99), pp. 945–946 (1999)
Newman, A.: A new algorithm for protein folding in the HP model. In: Proceedings of the 13th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’02), pp. 876–884 (2002)
Nussinov, R., et al.: Algorithms for loop matching. SIAM Journal on Applied Mathematics 35(1), 68–82 (1978)
Rivas, E., Eddy, S.R.: A dynamic programming algorithm for RNA structure prediction including pseudoknots. Journal of Molecular Biology 285, 2053–2068 (1999)
Ruan, J., Stormo, G.D., Zhang, W.: An iterated loop matching approach to the prediction of RNA secondary structure with pseudoknots. Bioinformatics 20(1), 58–66 (2004)
Shapiro, B.A., Wu, J.C.: Predicting RNA H-type pseudoknots with the massively parallel genetic algorithm. Computer Applications in the Biosciences 13(4), 459–471 (1997)
Tabaska, J.E., et al.: An RNA folding method capable of identifying pseudoknots and base triples. Bioinformatics 14(8), 691–699 (1998)
Tinoco, I., et al.: Improved estimation of secondary structure in ribonucleic acids. Nature New Biology 246, 40–42 (1973)
Uemura, Y., et al.: Tree adjoining grammars for RNA structure prediction. Theoretical Computer Science 210(2), 277–303 (1999)
Vialette, S.: On the computational complexity of 2-interval pattern matching problems. Theoretical Computer Science 312, 223–249 (2004)
Waterman, M.S.: Introduction to Computational Biology: Maps, Sequences and Genomes. Chapman and Hall, Boca Raton (1995)
Zuker, M., Stiegler, P.: Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Research 9(1), 133–148 (1981)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiang, M., Mayne, M., Gillespie, J. (2007). Delta: A Toolset for the Structural Analysis of Biological Sequences on a 3D Triangular Lattice. In: Măndoiu, I., Zelikovsky, A. (eds) Bioinformatics Research and Applications. ISBRA 2007. Lecture Notes in Computer Science(), vol 4463. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72031-7_47
Download citation
DOI: https://doi.org/10.1007/978-3-540-72031-7_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72030-0
Online ISBN: 978-3-540-72031-7
eBook Packages: Computer ScienceComputer Science (R0)