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Computers in Biology and Medicine|May 16, 2025
A novel in silico approach for predicting unbound brain-to-plasma ratio using machine learning-based support vector regressionGiang H Ta, Max K LeongChemico-Biological Interactions|August 25, 2025
Modeling skin sensitization: hierarchical support vector regression-based prediction of lysine depletion in DPRAGiang H Ta, Max K LeongFrontiers in Pharmacology|December 11, 2024
Mitigating Paxlovid™-induced drug‒drug interaction toxicity: an in silico insightGiang H Ta, Max K LeongToxicology|February 2, 2024
Development of a hierarchical support vector regression-based in silico model for the prediction of the cysteine depletion in DPRAGiang H Ta, Ching-Feng Weng, Max K LeongChemical Research in Toxicology|January 31, 2007
A novel approach using pharmacophore ensemble/support vector machine (PhE/SVM) for prediction of hERG liabilityMax K LeongMedicinal Chemistry (Shariqah (United Arab Emirates))|August 5, 2008
Prediction of cytochrome P450 2B6-substrate interactions using pharmacophore ensemble/support vector machine (PhE/SVM) approachMax K Leong, Tzu-Hsien ChenChemical Research in Toxicology|July 19, 2018
Insight Analysis of Promiscuous Estrogen Receptor α-Ligand Binding by a Novel Machine Learning SchemeTien-Yi Hou, Ching-Feng Weng, Max K LeongFrontiers in Pharmacology|May 21, 2021
In silico Prediction of Skin Sensitization: Quo vadis?Giang Huong Ta, Ching-Feng Weng, Max K LeongToxicology in Vitro : an International Journal Published in Association with BIBRA|December 29, 2016
In silico prediction of the mutagenicity of nitroaromatic compounds using a novel two-QSAR approachYi-Lung Ding, You-Chen Lyu, Max K LeongPlos One|March 23, 2012
Prediction of promiscuous p-glycoprotein inhibition using a novel machine learning schemeMax K Leong, Hong-Bin Chen, Yu-Hsuan ShihPageof 4