公開日期 | 標題 | 作者 | 來源出版物 | WOS | 全文 |
2019 | Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research | David, L.; Arus-Pous, J.; Karlsson, J.; Engkvist, O.; Bjerrum, E. J.; Kogej, T.; Kriegl, J. M.; Beck, B.; Hong-Ming Chen | Frontiers in Pharmacology | | |
2018 | Cheminformatics in Drug Discovery, an Industrial Perspective | Hong-Ming Chen ; Kogej, T.; Engkvist, O. | Molecular Informatics | | |
2009 | Designing a Combinatorial Library by Using Reagent Pharmacophore Fingerprint | Hong-Ming Chen ; Borjesson, U.; Engkvist, O.; Kogej, T.; Svensson, M. A.; Blomberg, N.; Weigelt, D.; Burrows, J. N.; Lange, T. | Qsar & Combinatorial Science | | |
2018 | De novo molecular design using deep reinforcement learning methods | Hong-Ming Chen ; Olivercrona, M.; Blaschke, T.; Engkvist, O.; Kogej, T.; Tyrchan, C. | Abstracts of Papers of the American Chemical Society | | |
2009 | ProSAR: A New Methodology for Combinatorial Library Design | Hong-Ming Chen ; Borjesson, U.; Engkvist, O.; Kogej, T.; Svensson, M. A.; Blomherg, N.; Weigelt, D.; Burrows, J. N.; Lange, T. | Journal of Chemical Information and Modeling | | |