回顾性分析
计算机科学
背景(考古学)
过程(计算)
人工智能
数据科学
地理
考古
全合成
操作系统
有机化学
化学
作者
Jingxin Dong,Mingyi Zhao,Yuansheng Liu,Yansen Su,Xiangxiang Zeng
摘要
In recent years, synthesizing drugs powered by artificial intelligence has brought great convenience to society. Since retrosynthetic analysis occupies an essential position in synthetic chemistry, it has received broad attention from researchers. In this review, we comprehensively summarize the development process of retrosynthesis in the context of deep learning. This review covers all aspects of retrosynthesis, including datasets, models and tools. Specifically, we report representative models from academia, in addition to a detailed description of the available and stable platforms in the industry. We also discuss the disadvantages of the existing models and provide potential future trends, so that more abecedarians will quickly understand and participate in the family of retrosynthesis planning.
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