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首页> 外文期刊>International Journal of Innovative Computing Information and Control >DNA SEQUENCE DESIGN FOR DNA COMPUTATION BASED ON BINARY PARTICLE SWARM OPTIMIZATION
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DNA SEQUENCE DESIGN FOR DNA COMPUTATION BASED ON BINARY PARTICLE SWARM OPTIMIZATION

机译：基于二元粒子群优化的DNA计算DNA序列设计

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摘要

Deoxyribonucleic Acid (DNA) has certain unique properties such as self-assembly and self-complementary in hybridization, which are important in many DNA-based technologies. DNA computing, for example, uses these properties to realize a computation in vitro, which consists of several chemical reactions. Other DNA-based technologies such as DNA-based nanotechnology and polymerase chain reaction also depend on hybridization to assemble nanostructure and to amplify DNA templates, respectively. Hybridization of DNA can be controlled by properly designing DNA sequences. In this paper, sequences are designed such that each sequence uniquely hybridizes to its complementary sequence, but not to any other sequences. Objective functions involved are similarity, H_(measure), continuity, and hairpin. Binary particle swarm optimization (BinPSO) is employed to minimize those objectives subjected to two constraints: melting temperature and GC_(content). It is found that BinPSO can provide a set of good DNA sequences, better than basic PSO algorithm in terms of aggregated fitness value.
机译：脱氧核糖核酸（DNA）具有某些独特的特性，例如杂交中的自组装和自互补，这在许多基于DNA的技术中都很重要。例如，DNA计算使用这些属性来实现体外计算，该计算由多个化学反应组成。其他基于DNA的技术（例如基于DNA的纳米技术和聚合酶链反应）也分别依赖于杂交来组装纳米结构和扩增DNA模板。 DNA的杂交可以通过适当设计DNA序列来控制。在本文中，设计序列时要使每个序列都与其互补序列唯一杂交，而不与其他任何序列杂交。涉及的目标函数是相似性，H_（度量），连续性和发夹。采用二进制粒子群优化（BinPSO）可以最大程度地减少受两个约束的那些目标：熔化温度和GC_（含量）。发现在聚合适应度值方面，BinPSO可以提供一组良好的DNA序列，优于基本PSO算法。

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