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生物研究中的人工智能代理:一项调查
Cong Qi1, Wenbo Wang2, Siqi Jiang1
1Department of Computer Science, New Jersey Institute of Technology, 323 Dr Martin Luther King Jr Blvd, Newark, NJ 07102, United States.
Briefings in bioinformatics
|February 26, 2026
概括
人工智能 (AI) 代理人正在推动生物研究超越预测到自主行动. 这项调查综合了100多项关于生物人工智能剂的研究,为未来的发展提供了一个框架.
科学领域:
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
- 生命科学中的人工智能
背景情况:
- 生物数据和实验复杂性正在迅速增加.
- 目前的人工智能模型主要作为研究中的被动工具.
- 人工智能系统越来越需要能够自主推理和行动的AI系统.
研究的目的:
- 系统地综合最近生物人工智能剂的进展.
- 为了解生物AI的景观提供统一的框架.
- 确定基于代理物的生物研究的关键挑战和未来方向.
主要方法:
- 进行了对100多项关于生物人工智能剂的代表性研究的系统审查.
- 开发了一个5D分类学来组织跨任务领域,架构,交互模式,评估和资源集成的现有研究.
- 分析了设计模式,新兴能力和公开挑战.
主要成果:
- 确定了关键的应用领域,包括临床分析,分子和药物设计,多omics分析和知识发现.
- 强调了代理性范式在适应性和交互性生物分析中的潜力.
- 编目了常见的设计模式和生物人工智能代理的新兴能力.
结论:
- 生物人工智能代理商在生命科学中提供了向自主推理和行动的范式转变.
- 关键的挑战仍然在于可靠性,隐私,可扩展性和标准化评估.
- 这项调查为开发更强大,透明和协作的生物研究基于代理的系统提供了路线图.
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