基于二值向量评价的粒子群优化方法求解DNA序列设计问题

Z. Ibrahim, Noor Khafifah Khalid, Kian Sheng Lim, S. Buyamin, Jameel Mukred
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引用次数: 8

摘要

脱氧核糖核酸(DNA)具有一些独特的性质,如自组装和杂交中的自互补,这在许多基于DNA的技术中都很重要。DNA杂交可以通过合理设计DNA序列来控制。在这项研究中,序列被设计成每个序列与它的互补序列唯一杂交,而不是与任何其他序列杂交。采用向量评估粒子群优化(Vector - evaluation particle swarm optimization, VEPSO)算法,在熔化温度和gc含量两个约束条件下,通过最小化相似性、Hmeasure、连续性和发夹四个目标函数来解决DNA序列设计问题。可以得到非支配解,这比其他只生成一组序列的研究工作要好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A binary vector evaluated particle swarm optimization based method for DNA sequence design problem
Deoxyribonucleic Acid (DNA) has certain unique properties such as self-assembly and self-complementary in hybridization, which are important in many DNA-based technologies. Hybridization of DNA can be controlled by properly designing DNA sequences. In this study, sequences are designed such that each sequence uniquely hybridizes to its complementary sequence, but not to any other sequences. Vector evaluated particle swarm optimization (VEPSO) is employed to solve the DNA sequence design problem by minimizing four objective functions, namely similarity, Hmeasure, continuity, and hairpin, subjected to two constraints: melting temperature and GCcontent. Non-dominated solutions can be produced, which are better than other research works where only a set of sequences is generated.
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