通过最大缩核酸偏差模型解读病毒-宿主适应的代码
Andrea Di Gioacchino1, Ivan Lecce1, Benjamin D Greenbaum2,3
1CNRS UMR 8023, Laboratory of Physics of the Ecole Normale Supérieure and PSL Research, Sorbonne Université, Paris, France.
Molecular biology and evolution
|June 3, 2025
概括
最大缩核酸偏差 (MENB) 模型揭示了宿主特定的病毒进化模式. 这些模型准确地分类病毒家族和宿主,为病毒适应和序列设计提供了洞察力.
科学领域:
- 病毒学 病毒学
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 病毒进化受到宿主相互作用的显著影响.
- 了解宿主病毒的依赖性对于预测病毒传播和适应至关重要.
- 现有的病毒分类和宿主预测方法可能是计算密集的.
研究的目的:
- 引入和验证最大入核酸偏差 (MENB) 模型,以定量表征宿主病毒进化依赖.
- 开发一种快速,可解释和强大的方法来分类病毒家族和宿主.
- 探索MENB模型在跟踪病毒适应和设计新型病毒序列方面的潜力.
主要方法:
- MENB模型是从病毒基因组序列中使用单,二和三核酸开发的.
- 模型被训练分类病毒家族 (四个ssRNA家族) 和宿主 (三个宿主).
- 性能与深度神经网络方法进行了比较.
主要成果:
- 在核酸基因使用中,MENB模型成功地解码了宿主和病毒家族"指纹".
- 该方法从基因组序列准确预测病毒家族和宿主,在速度和可解释性方面超过深度学习方法.
- MENB向新的病毒家族和宿主种群表现出强烈的泛化,确定了流感A和人类冠状病毒的中间宿主,并检测到了基因组重组事件.
结论:
- MENB模型提供了一种强大而有效的工具,用于理解宿主病毒共同进化.
- 这些模型为推动病毒适应的选择性压力提供了洞察力,并可以指导病毒序列的设计.
- MENB代表了病毒基因组学分析的重大进步,提供了预测和解释能力.
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