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首页> 外文期刊>Computational and mathematical methods in medicine >Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes
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Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes

机译:使用还原氨基酸模式预测高风险类型的人乳头瘤病毒

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A human papillomavirus type plays an important role in the early diagnosis of cervical cancer. Most of the prediction methods use protein sequence and structure information, but the reduced amino acid modes have not been used until now. In this paper, we introduced the modes of reduced amino acids to predict high-risk HPV. We first reduced 20 amino acids into several nonoverlapping groups and calculated their structure and physicochemical modes for high-risk HPV prediction, which was tested and compared with the existing methods on 68 samples of known HPV types. The experiment result indicates that the proposed method achieved better performance with an accuracy of 96.49%, indicating that the reduced amino acid modes might be used to improve the prediction of high-risk HPV types.
机译:人乳头瘤病毒型在宫颈癌的早期诊断中起着重要作用。大多数预测方法使用蛋白质序列和结构信息,但直到现在尚未使用还原的氨基酸模式。在本文中,我们介绍了降低氨基酸的模式,以预测高风险的HPV。我们首先将20个氨基酸缩减为几个非原始基团,并计算其用于高风险HPV预测的结构和物理化学模式,并与现有的已知HPV类型样品上的现有方法进行测试。实验结果表明,该方法的精度达到了96.49%的准确性,表明还可用于改善高风险HPV类型的预测来改善氨基酸模式。

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