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Bacterial Foraging Algorithm Based on Activity of Bacteria for DNA Computing Sequence Design

机译:基于细菌的DNA计算序列设计的细菌觅食算法

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摘要

Since the quantity and quality of DNA sequence directly affect the accuracy and efficiency of computation, the design of DNA sequence is essential for DNA computing. In order to improve the efficiency and reliability of DNA computing, there is a rich literature targeting at generating DNA sequences with lower similarity that can hybridize at a lower melting temperature. However, it is not trivial to improve both melting temperature and similarity for the DNA sequence, since DNA sequence design problem under the constraints of Hamming distance, secondary structure and molecular thermodynamic is known to be NP-hard. For the sake of achieving the lower melting temperature and similarity for the generated DNA sequence, we proposed an improved method for the bacterial foraging algorithm based on activity of bacteria (BFA-A). In particular, the effect of bacterial vitality on foraging ability is considered, and a competitive exclusion mechanism is introduced to improve the quality of the generated DNA sequences. In BFA-A, high-quality DNA strands are replicated to avoid the participation of inferior strands in the operation, and the active regulation mechanism and the competitive rejection mechanism are used to improve and accelerate the chemotaxis process. Experiments show that our proposed approach significantly outperforms existing methods in terms of melting temperature and similarity. In addition, the experimental results also show that our method can reduce the number of iterations, and has guiding significance to generate high-quality DNA sequences more efficiency.
机译:由于DNA序列的数量和质量直接影响计算的准确性和效率,因此DNA序列的设计对于DNA计算至关重要。为了提高DNA计算的效率和可靠性,存在富含性的文献靶向,该文献旨在产生具有较低相似性的DNA序列,其在较低的熔化温度下可以杂交。然而,改善DNA序列的熔化温度和相似性并不重要,因为DNA序列设计问题在汉明距离的约束下,已知二次结构和分子热力学是NP - 硬。为了实现所生成的DNA序列的较低熔化温度和相似性,我们提出了一种基于细菌活性(BFA-A)的细菌觅食算法的改进方法。特别地,考虑了细菌活力对觅食能力的影响,并引入了竞争的排阻机制以提高所生成的DNA序列的质量。在BFA-A中,复制高质量的DNA股线以避免在操作中的劣质股的参与,并且活性调节机制和竞争排斥机制用于改善和加速趋化性过程。实验表明,我们所提出的方法在熔化温度和相似性方面显着优于现有方法。此外,实验结果还表明,我们的方法可以减少迭代的数量,并且具有产生高质量DNA序列的引导意义更高的效率。

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