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SNP位点选择是国境口岸食源性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,为此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,能够准确地寻找食源性微生物的SNP位点组合,为大规模的检测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 the key link in the design of detection probes for foodborne microbial microarray at border crossing. Currently, the SNP locus mainly relies on manual processing, which seriously affects the detection speed and quality of detection. Therefore, a genetic algorithm based SNP locus Automatic selection method. The method uses the rough set theory to evaluate the classification ability of SNP loci combinations, synthesizes the design indexes which are closely related to the testing experiments, and uses the genetic algorithm to optimize the search. The experimental results show that this method has good robustness and fast convergence speed, and can accurately find SNP loci combinations of foodborne microorganisms, which provides a fast and reliable way for large-scale automatic detection of chip probes. Shorten the detection time limit of pathogenic microorganisms at border crossings and improve the accuracy of test results.