相关实验视频

Updated: Jan 29, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

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DyVarMap:整合合规动力学和可解释的机器学习,用于FGFR2中的癌症相关误解变异分类

Yiyang Lian1, Amarda Shehu1,2

  • 1School of Systems Biology, George Mason University, Manassas, VA 20110, USA.

Bioengineering (Basel, Switzerland)
|January 28, 2026
PubMed
概括

在癌症中解释基因变异是具有挑战性的. 一个新的框架DyVarMap使用结构动态来预测变异效应,为精确瘤学提供机械洞察力.

关键词:
在AlphaFold2中,我们将使用AlphaFold2.在FGFR2中.构造动力学 构造动力学机器学习是机器学习.错误的意义的变体精确瘤学 精确瘤学受体氨酸激酶的受体.变体效应预测变体效应预测

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