Research Article Open Access

DNA Sequence Optimization Based on Continuous Particle Swarm Optimization for Reliable DNA Computing and DNA Nanotechnology

N. K. Khalid, Z. Ibrahim, T. B. Kurniawan, M. S.Z. Abidin, M. Khalid and Andries P. Engelbrecht

Abstract

Problem statement: 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, Hmeasure, similarity, continuity and hairpin. Approach: There are several ways to solve multi-objective problem, however, in order to evaluate the correctness of PSO algorithm in DNA sequence design, this problem is converted into single objective problem. Particle Swarm Optimization (PSO) is proposed to minimize the objective in the problem, subjected to two constraints: melting temperature and GCcontent. A model is developed to present the DNA sequence design based on PSO computation. Results: 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. Conclusion: The results achieve verified that PSO can suitably solves the DNA sequence design problem using the proposed method and model, comparatively better than other approaches.

Journal of Computer Science
Volume 4 No. 11, 2008, 942-950

DOI: https://doi.org/10.3844/jcssp.2008.942.950

Submitted On: 29 November 2008 Published On: 30 November 2008

How to Cite: Khalid, N. K., Ibrahim, Z., Kurniawan, T. B., Abidin, M. S., Khalid, M. & Engelbrecht, A. P. (2008). DNA Sequence Optimization Based on Continuous Particle Swarm Optimization for Reliable DNA Computing and DNA Nanotechnology. Journal of Computer Science, 4(11), 942-950. https://doi.org/10.3844/jcssp.2008.942.950

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Keywords

  • Particle swarm optimization
  • DNA sequence design
  • optimization
  • user-defined weights