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A Method for the Recognition of High Resolution Melting Curve Based on Machine Learning

机译:一种基于机器学习的高分辨率熔化曲线的方法

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High Resolution Melting (HRM)analysis technology has been widely used in the study of genotyping and has caused widespread attention. However, the recognition of melting curves requires manual interactions, resulting in a decrease in the accuracy and efficiency of genotyping. This paper presents a new method for the recognition of high melting curve based on machine learning. We validated this method on 57 known serotypes of Streptococcus pneumoniae data sets and achieved 100% accuracy on the test set with good robustness. Then, we used the Kras gene fragment and its 7 mutant to further verify the effectiveness of the algorithm and demonstrated 100% prediction accuracy. The method proposed in this paper achieves efficient, accurate, and automated genotyping, and has broad application prospects in the fields of medicine and biology.
机译:高分辨率熔融(HRM)分析技术已被广泛用于基因分型的研究,并引起了广泛的关注。然而,熔化曲线的识别需要手动相互作用,导致基因分型的准确性和效率降低。本文介绍了基于机器学习识别高熔点曲线的新方法。我们验证了57个已知的链球菌数据集的血清型血清型,并在具有良好稳健性的测试集上实现了100 %的精度。然后,我们使用KRAS基因片段及其7个突变体进一步验证算法的有效性并证明了100 %的预测精度。本文提出的方法实现了高效,准确和自动化的基因分型,并在医学和生物学领域具有广泛的应用前景。

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