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SNP位点选择是是国境口岸致病微生物基因芯片检测探针设计的关键环节,目前主要依靠手工完成,严重影响着检测速度和检测质量。我们提出了一种基于遗传算法的SNP位点的自动选择方法,该方法运用粗糙集理论评估SNP位点组合的分类能力,综合与检测实验密切相关的设计指标,采用遗传算法进行优化搜索。实验结果表明,该方法具有很好的稳健性和较快的收敛速度,能够准确地寻找致病微生物的SNP位点组合,为大规模的检测基因芯片探针自动设计提供了快速可靠的途径,缩短了国境口岸致病微生物的检测时限,提高了检测结果的准确性。
SNP locus selection is a key link in the design of pathogenic microbe microarray detection probes at the border crossing. Currently, the SNP locus mainly depends on manual processing, which seriously affects the detection speed and quality of detection. We propose a method of automatic selection of SNP loci based on genetic algorithm. This method uses rough set theory to evaluate the classification ability of SNP loci. Based on the design indexes which are closely related to the testing experiments, genetic algorithm is used to optimize the search. The experimental results show that the method has good robustness and fast convergence speed, can accurately find SNP locus combinations of pathogenic microorganisms, and provides a fast and reliable way for large-scale automatic detection of gene chip probes. Shorten the detection time limit of pathogenic microorganisms at border crossings and improve the accuracy of test results.