Application of Machine Learning in Organic Chemistry

被引:13
|
作者
Liu, Yidi [1 ]
Yang, Qi [1 ]
Li, Yao [1 ]
Zhang, Long [1 ]
Luo, Sanzhong [1 ]
机构
[1] Tsinghua Univ, Ctr Basic Mol Sci, Dept Chem, Beijing 100084, Peoples R China
关键词
machine learning; molecular descriptor; algorithm; chemical property prediction; de novo design; chemical reaction prediction; retrosynthesis analysis; FINGERPRINT SIMILARITY SEARCH; DEVELOPMENT KIT CDK; SOURCE [!text type='JAVA']JAVA[!/text] LIBRARY; ARTIFICIAL-INTELLIGENCE; REACTIVITY PARAMETERS; MOLECULAR-PROPERTIES; REACTION PREDICTION; AQUEOUS SOLUBILITY; CHEMICAL-REACTIONS; NEURAL-NETWORKS;
D O I
10.6023/cjoc202006051
中图分类号
O62 [有机化学];
学科分类号
070303 ; 081704 ;
摘要
Driven by nowadays' computing power, big data technology as well as learning algorithm, artificial intelligence (AI) has gained trenmendous attentions and become a transformative approach in many research areas. One of the most extensively explored AI approaches in chemistry is (deep) machine learning, which provides new twists in the fields of organic chemistry. The workflow of machine learning (ML) study in organic chemistry is briefly introduced. Meanwhile, the application of ML in the accurate prediction of chemical properties, molecular de novo design, chemical reaction prediction, retrosynthetic analysis and artificial intelligence synthetic machine are also summarized. In the end, the current challenges in this field are analyzed and discussed.
引用
收藏
页码:3812 / 3827
页数:16
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