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Toxicology|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 LeongBiochemical and Biophysical Research Communications|August 4, 2007
Selection and characterization of lipase abzyme from phage displayed antibody librariesMax K Leong, Chinpiao Chen, Ker-Chang Shar, et al.Journal of Biomolecular Structure & Dynamics|November 30, 2017
Potential natural mTOR inhibitors screened by in silico approach and suppress hepatic stellate cells activationVaradharajan Thiyagarajan, Kuan-Wei Lee, Max K Leong, et al.Molecules (Basel, Switzerland)|July 25, 2018
Theoretical Prediction of the Complex P-Glycoprotein Substrate Efflux Based on the Novel Hierarchical Support Vector Regression SchemeChun Chen, Ming-Han Lee, Ching-Feng Weng, et al.Biomolecules|December 24, 2021
In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II DiabetesJirawat Riyaphan, Dinh-Chuong Pham, Max K Leong, et al.Pharmaceutics|February 2, 2021
Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 PermeabilityGiang Huong Ta, Cin-Syong Jhang, Ching-Feng Weng, et al.Toxicological Sciences : an Official Journal of the Society of Toxicology|May 29, 2010
Predicting mutagenicity of aromatic amines by various machine learning approachesMax K Leong, Sheng-Wen Lin, Hong-Bin Chen, et al.Pharmaceutical Research|December 24, 2008
Development of a new predictive model for interactions with human cytochrome P450 2A6 using pharmacophore ensemble/support vector machine (PhE/SVM) approachMax K Leong, Yen-Ming Chen, Hong-Bin Chen, et al.Chemical Research in Toxicology|September 17, 2011
Predicting activation of the promiscuous human pregnane X receptor by pharmacophore ensemble/support vector machine approachCi-Nong Chen, Yu-Hsuan Shih, Yi-Lung Ding, et al.International Journal of Molecular Sciences|July 3, 2019
In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR ApproachCheng-Ting Chi, Ming-Han Lee, Ching-Feng Weng, et al.Pageof 4