Improving the Lower Bounds of DNA Encoding with Combinational Constraints

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Encoding and processing information in DNA computing have been proved to be an important problem for biological molecules calculation, especially information encoding which directly influences the accuracy and reliability of DNA computing. High quality DNA sequences can reduce the emergence of false hybrid reaction. So as to reduce the false hybridization, many researchers proposed various algorithms to search the DNA sequences and combine all kinds of constraint conditions. In this paper, we adopt the improved genetic algorithm (IGA) to design the DNA sequences satisfying H distance and hamming distance constraints. Compared with the existing results, we obviously enhance the lower bounds of DNA sequence sets which satisfy the H distance and Hamming distance (HD), so that we could use the least DNA sequences to denote the data and reduce the redundancy of DNA data stored.


Document Type: Research Article


Publication date: January 1, 2012

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  • Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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