“有组织科研”背景下,科研团队建设已成为推动科技创新、实现国家科技战略目标的重要抓手。科研团队学作为一门国际上新兴的交叉学科,其核心是对科研团队从事研究探索活动的特点和有效性开展研究。阐释了科研团队学提出的时代背景以及...“有组织科研”背景下,科研团队建设已成为推动科技创新、实现国家科技战略目标的重要抓手。科研团队学作为一门国际上新兴的交叉学科,其核心是对科研团队从事研究探索活动的特点和有效性开展研究。阐释了科研团队学提出的时代背景以及当前科研团队发展的现实问题。运用隐含狄利克雷分布主题建模方法梳理了2006—2022年Web of Science上的692篇文献,凝练分析国际学术研究概况,从科研团队合作动机及协调发展、成员多样性与互动、跨学科协同环境、科研团队有效性等关键研究领域进行学术领域分析和价值阐释。从科研团队分层分类治理体系存在的“难点”、面向科技创新前沿的有组织科研探索存在的“卡点”以及支持系统推进创新突破的生态环境存在的“断点”等方面分析了中国发展科研团队学研究的迫切性。据此提出深入挖掘并分析科研团队资源禀赋特征、关注“有组织科研”的政策设计、营建科研团队成长的良好生态环境等研究展望。展开更多
Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providin...Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providing comprehensive insights into health and disease.The foundation of TCMF lies in its holistic approach,manifested through herbal compatibility theory,which has emerged from extensive clinical experience and evolved into a highly refined knowledge system.Within this framework,Chinese herbal medicines exhibit intricated characteristics,including multi-component interactions,diverse target sites,and varied biological pathways.These complexities pose significant challenges for understanding their molecular mechanisms.Contemporary advances in artificial intelligence(AI)are reshaping research in traditional Chinese medicine(TCM),offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs.This review explores the application of AI in uncovering these mechanisms,highlighting its role in compound absorption,distribution,metabolism,and excretion(ADME)prediction,molecular target identification,compound and target synergy recognition,pharmacological mechanisms exploration,and herbal formula optimization.Furthermore,the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms,promoting the modernization and globalization of TCM.展开更多
文摘“有组织科研”背景下,科研团队建设已成为推动科技创新、实现国家科技战略目标的重要抓手。科研团队学作为一门国际上新兴的交叉学科,其核心是对科研团队从事研究探索活动的特点和有效性开展研究。阐释了科研团队学提出的时代背景以及当前科研团队发展的现实问题。运用隐含狄利克雷分布主题建模方法梳理了2006—2022年Web of Science上的692篇文献,凝练分析国际学术研究概况,从科研团队合作动机及协调发展、成员多样性与互动、跨学科协同环境、科研团队有效性等关键研究领域进行学术领域分析和价值阐释。从科研团队分层分类治理体系存在的“难点”、面向科技创新前沿的有组织科研探索存在的“卡点”以及支持系统推进创新突破的生态环境存在的“断点”等方面分析了中国发展科研团队学研究的迫切性。据此提出深入挖掘并分析科研团队资源禀赋特征、关注“有组织科研”的政策设计、营建科研团队成长的良好生态环境等研究展望。
基金supported by the National Key R&D Program of China(No.2022YFC3502005)the three-year Action Plan for Shanghai TCM Development and Inheritance Program[No.ZY(2021-2023)-0401]the National Natural Science Foundation of China(No.82104521)。
文摘Traditional Chinese medicine formula(TCMF)represents a fundamental component of Chinese medical practice,incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities,while providing comprehensive insights into health and disease.The foundation of TCMF lies in its holistic approach,manifested through herbal compatibility theory,which has emerged from extensive clinical experience and evolved into a highly refined knowledge system.Within this framework,Chinese herbal medicines exhibit intricated characteristics,including multi-component interactions,diverse target sites,and varied biological pathways.These complexities pose significant challenges for understanding their molecular mechanisms.Contemporary advances in artificial intelligence(AI)are reshaping research in traditional Chinese medicine(TCM),offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs.This review explores the application of AI in uncovering these mechanisms,highlighting its role in compound absorption,distribution,metabolism,and excretion(ADME)prediction,molecular target identification,compound and target synergy recognition,pharmacological mechanisms exploration,and herbal formula optimization.Furthermore,the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms,promoting the modernization and globalization of TCM.
