人工智能与生物科学之间的桥梁:生物信息学中大型语言模型的全面审查
Anqi Lin1, Junpu Ye1, Chang Qi2
1Donghai County People's Hospital (Affiliated Kangda College of Nanjing Medical University); Department of Oncology, Zhujiang Hospital, Southern Medical University, Lianyungang 222000, China.
Briefings in bioinformatics
|July 25, 2025
概括
大型语言模型 (LLM) 正通过增强复杂的生物数据分析来彻底改变生物信息学. 本综述探讨了它们在结构预测和药物发现等领域的应用,挑战和未来潜力.
科学领域:
- 生物信息学是一种生物信息学.
- 人工智能的人工智能
- 计算生物学 计算生物学
背景情况:
- 大型语言模型 (LLM) 代表了人工智能的重大进步.
- 在生物信息学研究中,LLM显示了实质性的应用价值和潜力.
- 他们擅长处理和分析复杂的生物数据.
研究的目的:
- 系统地审查生物信息学LLM的发展和应用.
- 突出LLM在蛋白质/核酸结构预测,奥米克分析,药物设计和文献挖掘方面的进展.
- 讨论生物医学领域LLM的挑战和未来潜力.
主要方法:
- 关于生物信息学LLM应用的综合文献综述.
- 分析LLM在端到端学习和知识转移方面的能力.
- 讨论包括模型解释性和数据偏差在内的挑战.
主要成果:
- 在蛋白质和核酸结构预测方面,LLM表现出了显著的进展.
- 应用范围包括OMIC分析,药物设计和查以及生物医学文献挖掘.
- 法学士课程在端到端学习和知识转移方面提供了独特的能力.
结论:
- 在生物信息学研究中,LLM正在成为必不可少的工具.
- 应对可解释性和偏见等挑战对于未来的发展至关重要.
- 在跨模式学习和跨学科生物医学创新方面,LLM具有巨大的潜力.
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