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Primer design for multiplex PCR using a genetic algorithm

机译:使用遗传算法进行多重PCR的引物设计

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摘要

Multiplex Polymerase chain reaction (PCR) is the term used when more than one pair of primers is used in a polymerase chain reaction. The goal of multiplex PCR is to amplify several segments of target DNA simultaneously and thereby to conserve template DNA, save time, and minimize expense. The success of the experiment is dependent on primer design. However, this can be a dreary task as there are many constrains such as melting temperatures, primer length, GC content and complementarity that need to be optimized to obtain a good PCR product. In our investigations, we found few primer design tools for multiplex PCR and there was no suitable tool for our partners who want to use a multiplex PCR genotypic assay. The tool draws on a genetic algorithm where stochastic approaches based on the concept of biological evolution, biological genetics and genetic operations on chromosomes are used to find an optimal solution for multiplex PCR. The presented experimental results indicate that the proposed algorithm is able to find a set of primer pairs that not only obey the design properties but also work in the same tube.
机译:多重聚合酶链反应(PCR)是在聚合酶链反应中使用多于一对引物时使用的术语。多重PCR的目的是同时扩增靶DNA的多个片段,从而节省模板DNA,节省时间,并最大程度地减少费用。实验的成功取决于引物设计。但是,这可能是一项繁琐的任务,因为有许多约束条件需要优化,例如解链温度,引物长度,GC含量和互补性,以获得良好的PCR产物。在我们的研究中,我们发现用于多重PCR的引物设计工具很少,而对于想要使用多重PCR基因型分析的合作伙伴,没有合适的工具。该工具使用了一种遗传算法,其中基于生物进化,生物遗传学和对染色体的遗传操作的概念的随机方法被用于寻找多重PCR的最佳解决方案。给出的实验结果表明,所提出的算法能够找到一组引物对,这些引物对不仅服从设计特性,而且可以在同一管中工作。

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  • 来源
    《Soft Computing》 |2007年第9期|855-863|共9页
  • 作者单位

    Institute of System Biology and Bioinformatics National Central University 320 Taoyuan Taiwan;

    Institute of System Biology and Bioinformatics National Central University 320 Taoyuan Taiwan;

    Department of Biological Science and Technology Institute of Bioinformatics National Chiao Tung University 300 HsinChu Taiwan;

    Department of Computer Science and Information Engineering National Central University 320 Taoyuan Taiwan;

    Department of Biological Science and Technology Institute of Bioinformatics National Chiao Tung University 300 HsinChu Taiwan;

    Department of Computer Science and Information Engineering National Central University 320 Taoyuan Taiwan;

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