药物发现
计算机科学
数据科学
知识抽取
资源(消歧)
水准点(测量)
虚拟筛选
人工智能
生物信息学
大地测量学
计算机网络
生物
地理
作者
Jianyuan Deng,Zhibo Yang,Iwao Ojima,Dimitris Samaras,Fusheng Wang
摘要
Artificial intelligence (AI) has been transforming the practice of drug discovery in the past decade. Various AI techniques have been used in many drug discovery applications, such as virtual screening and drug design. In this survey, we first give an overview on drug discovery and discuss related applications, which can be reduced to two major tasks, i.e. molecular property prediction and molecule generation. We then present common data resources, molecule representations and benchmark platforms. As a major part of the survey, AI techniques are dissected into model architectures and learning paradigms. To reflect the technical development of AI in drug discovery over the years, the surveyed works are organized chronologically. We expect that this survey provides a comprehensive review on AI in drug discovery. We also provide a GitHub repository with a collection of papers (and codes, if applicable) as a learning resource, which is regularly updated.
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