Authors : Mohd Zakree Ahmad Nazri, M. Daman Huri, Azuraliza Abu Bakar, Salwani Abdullah, Masri Ayob Dan and Tri Basuki Kurniawan
Abstract: The fundamental principle in the fields of DNA computing and DNA nanotechnology is based on the complementary pairing of the Deoxyribonucleic Acid (DNA). In this field of research, it is essential to obtain good DNA sequences in order to obtain accurate DNA-based computational information. In this process, however there are four constraints involved, namely Hmeasure, similarity, continuity and hairpin. In addition, two other constraints also play a role to maintain the uniformity in the sequence of the GC-content and the melting temperature (Tm) that would arise. Therefore, a DNA sequence design tool is needed to facilitate the design process with the ability to monitor and completely satisfy the specified constraints. In this study, a biologically-inspired DNA sequence design algorithm is presented and it allows generated sets of DNA that satisfy the several thumb rules in the DNA sequence design. The algorithm is based on the Negative Selection Algorithm (NSA). NSA is a common technique inspired by the negative selection process that occurs during the maturation of the T cells in the thymus. The proposed algorithm is able to prevent risks of fraying strands of the DNA and to limit cross hybridizations. In addition, it is able to design unique sequences. Furthermore, the NSA based algorithm can prevent the formation of self-complimentary and hairpin structures of certain lengths and only allows minimum interaction with neighbouring sequences. In this study, the results are compared to an Ant Colony Optimization (ACO) based on the DNA sequence design tool. The analysis shows that the NSA based algorithm performs better than ACO in generating the DNA sequences that satisfy the given constraints.
Mohd Zakree Ahmad Nazri, M. Daman Huri, Azuraliza Abu Bakar, Salwani Abdullah, Masri Ayob Dan and Tri Basuki Kurniawan, 2013. DNA Sequence Design Using Artificial Immune Systems. Journal of Engineering and Applied Sciences, 8: 49-57.