药物发现
自然(考古学)
药品
计算机科学
医学
地理
药理学
生物
生物信息学
考古
作者
Feng-Lei Duan,Chun‐Bao Duan,Huilin Xu,Xin-Ying Zhao,Otgonpurev Sukhbaatar,Jie Gao,Ming‐Zhi Zhang,Weihua Zhang,Yu‐Cheng Gu
出处
期刊:
[Elsevier BV]
日期:2024-06-25
卷期号:3 (3): 185-187
被引量:28
标识
DOI:10.1016/j.aac.2024.06.003
摘要
The latest review published in Nature Reviews Drug Discovery by Michael W. Mullowney and co-authors focuses on the use of artificial intelligence techniques, specifically machine learning, in natural product drug discovery. The authors discussed various applications of AI in this field, such as genome and metabolome mining, structural characterization of natural products, and predicting targets and biological activities of these compounds. They also highlighted the challenges associated with creating and managing large datasets for training algorithms, as well as strategies to address these obstacles. Additionally, the authors examine common pitfalls in algorithm training and offer suggestions for avoiding them.
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