对生物学和化学的大型语言模型的调查
Islambek Ashyrmamatov1, Su Ji Gwak2, Su-Young Jin2
1Research Institute of Pharmaceutical Science, College of Pharmacy, Seoul National University, Seoul, Republic of Korea.
Experimental & molecular medicine
|November 19, 2025
概括
人工智能 (AI) 正通过生物/化学语言模型彻底改变生物医学研究. 这些模型将分子数据转化为语言,使药物发现和生物理解的先进计算分析成为可能.
科学领域:
- 生物医学研究的研究.
- 计算生物学是一种计算生物学.
- 化学信息学 化学信息学
背景情况:
- 人工智能 (AI) 为复杂的生物系统提供可扩展的计算框架.
- 生物/化学语言模型,包括大型语言模型 (LLM),是人工智能对生物医学影响的核心.
- 这些模型将分子结构视为高级计算分析的语言.
研究的目的:
- 批判性地检查AI语言模型在生物学和化学中的作用.
- 追踪这些模型的演变,从分子表示到生成和优化.
- 探索关键的生物医学应用和人工智能在科学发现中的未来方向.
主要方法:
- 对分子表示策略 (序列,字符串,图形,点云) 的审查.
- 探索核心的人工智能模型架构 (例如,变压器) 和预训练策略 (例如,自主监督学习).
- 对各种生物医学应用中的代表性研究进行分析.
主要成果:
- 突出了关键的分子表示策略及其在AI中的局限性.
- 讨论了各种AI模型架构和预训练方法.
- 探索了许多生物医学应用,从蛋白质设计到反应预测.
结论:
- 人工智能语言模型正在改变分子表示,生成和优化.
- 新兴的代理人工智能系统有望加速科学发现.
- 技术,伦理和监管方面的考虑对人工智能在生物医学中的未来至关重要.
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