αExtractor: a system for automatic extraction of chemical information from biomedical literature

作     者：Jiacheng Xiong Xiaohong Liu Zhaojun Li Hongzhong Xiao Guangchao Wang Zhenjiang Niu Chaoyuan Fei Feisheng Zhong Gang Wang Wei Zhang Zunyun Fu Zhiguo Liu Kaixian Chen Hualiang Jiang Mingyue Zheng 

作者机构：Drug Discovery and Design CenterState Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of SciencesBeijing 100049China AI DepartmentSuzhou Alphama Biotechnology Co.Ltd.Suzhou 215125China College of Computer and Information EngineeringDezhou UniversityDezhou 253023China 

出 版 物：《Science China(Life Sciences)》 (中国科学（生命科学英文版）)

年 卷 期：2024年第67卷第3期

页      面：618-621页

核心收录：

学科分类：0710[理学-生物学] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 10[医学] 

基　　金：supported by the National Natural Science Foundation of China(T2225002,82273855) Lingang Laboratory(LG202102-01-02) the National Key Research and Development Program of China(2022YFC3400504) 

主　　题：has such knowledge 

摘      要：Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structure prediction and protein design(Madani et al., 2023). However, there is massive biomedical knowledge not curated in the form of structured data but hidden in primary scientific literature.