微生物学和微生物组研究的人工智能
Xu-Wen Wang1, Tong Wang2, Yang-Yu Liu1
1Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Cell systems
|February 19, 2026
概括
人工智能 (AI) 正在彻底改变微生物学和微生物组研究. 机器学习和深度学习方法正在推动了解微生物生命及其对健康和环境的影响的突破.
科学领域:
- 微生物学 微生物学
- 微生物组研究 微生物组研究
- 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:
- 人工智能 (AI) 正在越来越多地影响科学研究.
- 微生物学和微生物组研究正在从机器学习 (ML) 和深度学习 (DL) 应用中受益.
- 了解微生物群落对于各种生物和医学应用至关重要.
研究的目的:
- 在微生物学和微生物组研究中对人工智能驱动的方法进行全面审查.
- 引导研究人员为他们的具体目标选择合适的AI技术 (ML与DL).
- 突出通过人工智能应用获得的技术进步和生物见解.
主要方法:
- 对与生物数据相关的基础AI技术的审查.
- 人工智能应用在各种微生物学和微生物组研究领域的分类.
- 讨论挑战和该领域最近的突破.
主要成果:
- 人工智能为分类学分析,功能注释和微生物角色预测提供了强大的工具.
- 人工智能有助于研究微生物-X相互作用,微生物生态学和代谢建模.
- 人工智能应用扩展到精密营养,临床微生物学和治疗药物的开发.
结论:
- 人工智能是微生物学和微生物组研究的变革力量,使新的方法成为可能.
- 人工智能增强了我们对微生物生命对地球和人类健康的影响的理解.
- 人工智能的整合有望带来创新的解决方案和更深入的生物学见解.
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