在传染病研究中的生物序列分析的大型语言模型
Junyu Luo1, Xiyang Cai1, Yixue Li1,2,3,4,5,6
1Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou 510005, China.
Biosafety and health
|November 20, 2025
概括
大型语言模型 (LLM) 通过分析生物序列来彻底改变传染病研究. 本综述涵盖了LLM类型,应用和在病原体识别和药物开发中有效使用的挑战.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 基因组学就是基因组学.
背景情况:
- 大型语言模型 (LLM) 在分析复杂的生物数据方面显示出显著的前景.
- 它们在传染病研究中的应用正在迅速扩大,提供了新的分析能力.
研究的目的:
- 审查生物LLM的主要类型:蛋白质,基因组和多式模式.
- 突出这些模型在传染病研究中的架构和多样化的应用.
- 讨论目前的挑战和LLM实施的未来方向.
主要方法:
- 对生物LLMs现有文献的审查.
- 将LLM分类为蛋白质,基因组和多模式类型.
- 在病原体识别,进化监测,宿主病原体预测和治疗开发中对LLM应用的分析.
主要成果:
- 通过LLM,可以对基因组和蛋白质组数据进行大规模的解释.
- 关键应用包括增强病原体识别和加速治疗开发.
- 确定的挑战包括数据质量,模型可解释性和生物安全性.
结论:
- 生物LLM是传染病研究的变革性工具.
- 解决数据质量,可解释性和安全方面的挑战对于负责任的部署至关重要.
- 了解LLM的潜力和局限性是推动传染病科学发展的关键.
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