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Updated: May 15, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

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通过基于树的学习预测病毒宿主密码体适应性和路径转移,以密码体使用偏差和基因组特征为基础

Shuquan Su1,2,3, Zhongran Ni4,5, Tian Lan2

  • 1Faculty of Computer Science and Control Engineering, Shenzhen University of Advanced Technology, Shenzhen, China.

Scientific reports
|April 10, 2025
PubMed
概括

本研究引入了一种定量方法来测量病毒密码体适应性 (VCF) 和其转移,这对于了解病原体传播至关重要. 机器学习模型使用病毒基因组属性预测VCF,揭示了摇摆位置.

关键词:
科登使用偏见机器学习是机器学习.病毒的演化 病毒的演化病毒宿主科顿健身的健康状况

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