我着迷于将最新的人工智能和机器学习技术应用于药物发现. It has the potential, 以及自动化的进一步发展, 改变药物发现过程.
Key Achievements
2021
2021
2018
Featured publications
通过课程学习提高从头分子设计
Nature Machine Intelligence. 2022; 4, Guo, J., Fialková, V., Arango, J.D. et al. 出版链接:http://www.nature.com/articles/s42256 - 022 - 00494 - 4 # citeas
化学反应的计算预测:现状与展望.
Drug Discovery Today. 2018; 23(6): 1203-1218. Engkvist O, Norrby P-O, Selmi N等. Publication link: http://www.sciencedirect.com/science/article/pii/S1359644617305068
深度学习在药物发现中的兴起.
Drug Discovery Today. 2018; 23(6): 1241-1250. 陈海,吴英杰,王勇,等. Publication link: http://www.sciencedirect.com/science/article/pii/S1359644617303598
通过深度强化学习的分子从头设计.
Journal of Cheminformatics. 2017; 9(48). Olivecrona M, Blaschke T, Engkvist O,陈海. Publication link: http://jcheminf.biomedcentral.com/articles/10.1186/s13321-017-0235-x
生成式自编码器在从头分子设计中的应用.
Molecular Informatics. 2018; 37(1-2): 1700123. Blaschke T, Olivecrona M, Engkvist O等. Publication link: http://onlinelibrary.wiley.com/doi/full/10.1002/minf.201700123
大化学:化学大数据分析的挑战与机遇.
Molecular Informatics. 2016; 35(11-12): 615-621, Tetko I.V., Engkvist O, Koch U et al. Publication link: http://onlinelibrary.wiley.com/doi/full/10.1002/minf.201600073
Veeva ID: Z4-57592
筹备日期:2023年8月