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DNA sequence design for DNA computation based on binary particle swarm optimizationud

机译:基于二进制粒子群算法的DNA计算DNA序列设计 ud

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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 com- putation in vitro, which consists of several chemical reactions. Other DNA-based tech- nologies 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 comple- mentary sequence, but not to any other sequences. Objective functions involved are simi- larity, Hmeasure, continuity, and hairpin. Binary particle swarm optimization (BinPSO) is employed to minimize those objectives subjected to two constraints: melting tempera- ture and GCcontent. 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计算利用这些特性在体外实现了由数个化学反应组成的计算。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,序列的设计使得每个序列都与其互补序列唯一杂交,而不与任何其他序列杂交。涉及的目标功能是相似性,Hmeasure,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目标:熔融温度和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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