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Machine learning in accelerating microsphere formulation development Journal article
Deng, Jiayin, Ye, Zhuyifan, Zheng, Wenwen, Chen, Jian, Gao, Haoshi, Wu, Zheng, Chan, Ging, Wang, Yongjun, Cao, Dongsheng, Wang, Yanqing, Lee, Simon Ming Yuen, Ouyang, Defang. Machine learning in accelerating microsphere formulation development[J]. Drug Delivery and Translational Research, 2023, 13(4), 966-982.
Authors:  Deng, Jiayin;  Ye, Zhuyifan;  Zheng, Wenwen;  Chen, Jian;  Gao, Haoshi; et al.
Favorite | TC[WOS]:6 TC[Scopus]:8  IF:5.7/5.5 | Submit date：2023/01/30
Drug Release  Machine Learning  Microspheres  Molecular Dynamics Simulation  
Vertical distributions of atmospheric black carbon in dry and wet seasons observed at a 356-m meteorological tower in Shenzhen, South China Journal article
Yue Liang, Cheng Wu, Dui Wu, Ben Liu, Yong Jie Li, Jiayin Sun, Honglong Yang, Xia Mao, Jian Tan, Rui Xia, Tao Deng, Mei Li, Zhen Zhou. Vertical distributions of atmospheric black carbon in dry and wet seasons observed at a 356-m meteorological tower in Shenzhen, South China[J]. Science of the Total Environment, 2022, 853, 158657.
Authors:  Yue Liang;  Cheng Wu;  Dui Wu;  Ben Liu;  Yong Jie Li; et al.
Favorite | TC[WOS]:8 TC[Scopus]:9  IF:8.2/8.6 | Submit date：2023/01/30
Black Carbon  Meteorological Tower  Micro Aethalometer  Shenzhen  Vertical Distribution  
Development of in silico methodology for siRNA lipid nanoparticle formulations Journal article
Gao, Haoshi, Kan, Stanislav, Ye, Zhuyifan, Feng, Yuchen, Jin, Lei, Zhang, Xudong, Deng, Jiayin, Chan, Ging, Hu, Yuanjia, Wang, Yongjun, Cao, Dongsheng, Ji, Yuanhui, Liang, Mingtao, Li, Haifeng, Ouyang, Defang. Development of in silico methodology for siRNA lipid nanoparticle formulations[J]. Chemical Engineering Journal, 2022, 442, 136310.
Authors:  Gao, Haoshi;  Kan, Stanislav;  Ye, Zhuyifan;  Feng, Yuchen;  Jin, Lei; et al.
Favorite | TC[WOS]:15 TC[Scopus]:16  IF:13.3/13.2 | Submit date：2022/05/13
Cationic Lipids  Knockdown Efficiency  Lipid Nanoparticle  Machine Learning  Molecular Dynamic Simulation  Sirna  
In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques Journal article
Li, Junjun, Gao, Hanlu, Ye, Zhuyifan, Deng, Jiayin, Ouyang, Defang. In silico formulation prediction of drug/cyclodextrin/polymer ternary complexes by machine learning and molecular modeling techniques[J]. Carbohydrate Polymers, 2022, 275(118712).
Authors:  Li, Junjun;  Gao, Hanlu;  Ye, Zhuyifan;  Deng, Jiayin;  Ouyang, Defang
Favorite | TC[WOS]:16 TC[Scopus]:16  IF:10.7/10.2 | Submit date：2022/02/21
Machine Learning  Molecular Modeling  Random Forest  Solubility Prediction  Ternary Cyclodextrin Complexes