Abstract
In DNA based computation and DNA nanotechnology, the design of good DNA sequences has turned out to be an essential problem and one of the most practical and important research topics. Basically, the DNA sequence design problem is a multi-objective problem, and it can be evaluated using four objective functions, namely, H measure , similarity, continuity, andhairpin. There are several ways to solve a multi-objective problem, such as value function method, weighted sum method, and using evolutionary algorithms. However, in this paper, common method has been used, namely weighted sum method to convert DNA sequence design problem into single objective problem. Binary particle swarm optimization (BinPSO) is proposed to minimize the objective in the problem, subjected to two constraints: melting temperature and GC content . Based on experiments and researches done, 20 particles are used in the implementation of the optimization process, where the average values and the standard deviation for 100 runs are shown along with comparison to other existing methods. The results obtained verified that BinPSO can suitably solve DNA sequence design problem using the proposed method and model, comparatively better than other approaches.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arita, M., Nishikawa, A., Hagiya, M., Komiya, K., Gouzu, H., Sakamoto, K.: Improving sequence design for DNA computing. In: Proc. Genetic Evol. Comput. Conf. (GECCO), pp. 875–882 (2000)
Reece, R. J.: Analysis of Genes and Genomes. Wiley, Chichester (2004)
Adleman, L.: Molecular computation of solutions to combinatorial problems. Science 266, 1021–1024 (1998)
Kashiwamura, S., Kameda, A., Yamamoto, M., Ohuchi, A.: Two-step Search for DNA Se-quence Design. In: Proceedings of the 2003 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2003), pp. 1815–1818 (2003)
Arita, M., Kobayashi, S.: DNA sequence design using templates. New Generation Comput. 20, 263–277 (2002)
Kobayashi, S., Kondo, T.: On Template Method for DNA Sequence Design. In: Preliminary Proceeding of 8th International Meeting on DNA Based Computers, pp. 115–124 (2002)
Kennedy, J., Eberhart, R.C.: A discrete binary version of the particle swarm algorithm. In: Proc. Conf. Systems, Piscataway, NJ, pp. 4104–4108 (1997)
Kalyanmoy, D.: Multi-objective Evolutionary Optimization, p. 50. John Wiley & Sons, Chichester (2001)
Seeman, N.C., Kallenbach, N.R.: Design of immobile Nucleic Acid Junctions. Biophysical Journal 44, 201–209 (1983)
Seeman, N.C.: De Novo Design of Sequences for Nucleic Acid Structural Engineering. Journal of Biomolecular Structure & Dynamics 8(3), 573–581 (1990)
Baum, E.B.: DNA Sequences Useful for Computation (unpublished) (1996), http://www.neci.nj.nec.com/homepages/eric/seq.ps
Hartemink, A.J., Gifford, D.K., Khodor, J.: Automated Constraint Based Nucleotide Sequence Selection for DNA Computation. In: Proc. 4th DIMACS Workshop DNA Based Computer, pp. 227–235 (1998)
Penchovsky, R., Ackermann, J.: DNA library design for molecular computation. J. Comput. Bio. 10(2), 215–229 (2003)
Tanaka, F., Naktsugawa, M., Yamamoto, M., Shiba, T., Ohuchi, A.: Toward a general-purpose sequence design system in DNA computing. In: Proc. Congr. Evil. Comput (CEC), pp. 73–78 (2002)
Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220, 671–680 (1983)
Marathe, A., Condon, A.E., Corn, R.M.: On Combinatorial DNA Word Design. In: Proceedings of the 5th International Meeting on DNA Based Computers (1999)
Feldkamp, U., Saghafi, S., Banzhaf, W., Rauhe, H.: DNA sequence generator–A program for the construction of DNA sequences. In: Proc. 7th Int. Workshop DNA Based Computer, pp. 179–188 (2001)
Frutos, A.G., Thiel, A.J., Condon, A.E., Smith, L.M., Corn, R.M.: DNA computing at surfaces: Four base mismatch word designs. In: Proc. 3rd DIMACS Workshop DNA Based Computer, p. 238 (1997)
Deaton, R., Murphy, R.C., Garzon, M., Franceschetti, D.T., Stevens Jr., S.E.: Good Encod-ings for DNA−based Solutions to Combinatorial Problems. In: Proceedings of the Second Annual Meeting on DNA Based Computers, held at Princeton University, pp. 159–171. Princeton University Press, Princeton (1996)
Deaton, R., Murphy, R.C., Rose, J.A., Garzon, M., Franceschetti, D.T., Stevens Jr., S.E.: Genetic Search for Reliable Encodings for DNA−based Computation. In: First Conference on Genetic Programming (1996)
Shin, S.Y., Lee, I.H., Kim, D., Zhang, B.T.: Multi-objective evolutionary optimization of DNA sequences for reliable DNA computing. IEEE Transaction on Evolutionary Computation 9(2), 143–158 (2005)
Guangzhao, C., Yunyun, N., Yangfeng, W., Xuncai, Z., Linqiang, P.: A New approach Based on PSO algorithm to Find Good Computational Encoding Sequences. Progress in Natural Science 17(6), 712–716 (2007)
Zhou, S., Zhang, Q., Zhao, J., Li, J.: DNA Encoding Based on Multi-objective Particle Swarm. Journal of Computational and Theoretical Nanoscience 4, 1249–1252 (2007)
Kurniawan, T.B., Khalid, N.K., Ibrahim, Z., Khalid, M., Middendorf, M.: An Ant Colony System for DNA Sequence Design Based On Thermodynamics. In: Proceedings of the Fourth IASTED International Conference Advances in Computer Science and Technology (ACST 2008), Langkawi, Malaysia, pp. 144–149 (2008)
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proceeding of IEEE Interna-tional Conference on Neural Networks, Perth, Australia, pp. 1942–1948 (1995)
Santa Lucia Jr., J.: A unified view of polymer, dumbbell, and oligonucleotide DNA nearest-neighbour thermodynamics. Proc. Nat. Acad. Sci. USA 95, 1460–1465 (1998)
Eberhart, R.C., Shi, Y.: Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization. In: Proceedings of IEEE congress evolutionary computation, San Diego, CA, pp. 84–88 (2000)
van der Bergh, F., Engelbrecht, A.P.: An analysis of particle swarm optimizers, PhD thesis, Department of Computer Science, University of Pretoria, South Africa (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Khalid, N.K., Ibrahim, Z., Kurniawan, T.B., Khalid, M., Engelbrecht, A.P. (2009). Implementation of Binary Particle Swarm Optimization for DNA Sequence Design. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_64
Download citation
DOI: https://doi.org/10.1007/978-3-642-02481-8_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02480-1
Online ISBN: 978-3-642-02481-8
eBook Packages: Computer ScienceComputer Science (R0)