Department of Applied Data Science
Results 1-6 of 6
| Issue Date | Title | Author(s) | Type | |
|---|---|---|---|---|
| 1 | 2015 | The Impact of Docking Pose Generation Error on the Prediction of Binding Affinity | Li, Hongjian ; Prof. LEUNG Kwong Sak ; Wong, Man-Hon ; Ballester, Pedro J. | Conference Paper |
| 2 | 2015 | The importance of the regression model in the structure-based prediction of protein-ligand binding | Li, Hongjian ; Prof. LEUNG Kwong Sak ; Wong, Man-Hon ; Ballester, Pedro J. | Conference Paper |
| 3 | 2015 | Improving autodock vina using random forest: The growing accuracy of binding affinity prediction by the effective exploitation of larger data sets | Li, Hongjian ; Prof. LEUNG Kwong Sak ; Wong, Man-Hon ; Ballester, Pedro J. | Peer Reviewed Journal Article |
| 4 | 2015 | In silico identification and in vitro and in vivo validation of anti-psychotic drug fluspirilene as a potential CDK2 inhibitor and a candidate anti-cancer drug | Shi, Xi-Nan ; Li, Hongjian ; Yao, Hong ; Liu, Xu ; Li, Ling ; Prof. LEUNG Kwong Sak ; Kung, Hsiangfu ; Lu, Di ; Wong, Man-Hon ; Lin, Marie Chia-Mi | Peer Reviewed Journal Article |
| 5 | 2015 | Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest | Li, Hongjian ; Prof. LEUNG Kwong Sak ; Wong, Man-Hon ; Ballester, Pedro J. | Peer Reviewed Journal Article |
| 6 | 2015 | The use of random forest to predict binding affinity in docking | Li, Hongjian ; Prof. LEUNG Kwong Sak ; Wong, Man-Hon ; Ballester, Pedro J. | Conference Paper |