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首页> 外文期刊>Arabian Journal for Science and Engineering >Data Clustering for the DNA Computing Readout Method Implemented on LightCycler and Based on Particle Swarm Optimization
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Data Clustering for the DNA Computing Readout Method Implemented on LightCycler and Based on Particle Swarm Optimization

机译：基于粒子群优化的LightCycler DNA读出方法的数据聚类

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摘要

In this work, particle swarm optimization (PSO) is applied to automate the DNA computing readout method based on a real-time polymerase chain reaction (PCR). Moreover, real-time amplification was performed and the TaqMan detection approach was used for the plan and the readout approach development. The most important part of the readout method is identifying two different reactions in the real-time PCR, which involve in vitro and in silico processes in order to inspect the placement of pairs of nodes in the Hamiltonian path problem. In addition, the real-time PCR experiment is implemented on the LightCycler System. Previously, manual method was exploited to classify two different output reactions of real-time PCR that was a time consuming process. In this study, by exploiting MATLAB the PSO has been implemented for clustering output reactions of real-time PCR and experimental results depict that the amplification response for "YES" and "NO" reactions can be clustered correctly.
机译：在这项工作中，基于实时聚合酶链反应（PCR）的粒子群优化（PSO）技术可用于自动化DNA计算读出方法。此外，进行了实时扩增，并将TaqMan检测方法用于计划和读出方法的开发。读出方法最重要的部分是在实时PCR中识别两个不同的反应，涉及体外和计算机过程，以检查汉密尔顿路径问题中节点对的放置。此外，实时PCR实验是在LightCycler系统上进行的。以前，利用手动方法对实时PCR的两个不同输出反应进行分类，这是一个耗时的过程。在这项研究中，通过利用MATLAB，PSO已实现了对实时PCR输出反应的聚类，并且实验结果表明，“是”和“否”反应的扩增反应可以正确地聚类。

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