Y Z Chen

发表

MODEL—molecular descriptor lab: A web‐based server for computing structural and physicochemical features of compounds

Z R Li, L Y Han, Y Xue, 2007, Biotechnology and bioengineering.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

Z. R. Li, Y Z Chen, P Zhang, 2017, Journal of molecular biology.

Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach

Y Z Chen, X H Liu, H Y Song, 2010, Molecular informatics.

Prediction of genotoxicity of chemical compounds by statistical learning methods.

Z R Li, Z. R. Li, Y Xue, 2005, Chemical research in toxicology.

Prediction of factor Xa inhibitors by machine learning methods.

H H Lin, L Y Han, Y Xue, 2007, Journal of molecular graphics & modelling.

Virtual screening methods as tools for drug lead discovery from large chemical libraries.

Y Z Chen, X H Ma, F Zhu, 2012, Current medicinal chemistry.

Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools.

Y Z Chen, P Zhang, C Qin, 2015, Advanced drug delivery reviews.

Prediction of torsade-causing potential of drugs by support vector machine approach.

Y Xue, C W Yap, Y Z Chen, 2004, Toxicological sciences : an official journal of the Society of Toxicology.

Theme 7. Sharing International Experiences in Disasters: Summary and Action Plan

Y Z Chen, R Brown, R A Andrews, 2001, Prehospital and Disaster Medicine.

Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods.

Z R Li, Z. R. Li, C W Yap, 2006, Journal of molecular graphics & modelling.

Usefulness of traditionally defined herbal properties for distinguishing prescriptions of traditional Chinese medicine from non-prescription recipes.

Y Z Chen, C Y Ung, Y. Z. Chen, 2007, Journal of ethnopharmacology.

Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties.

C W Yap, H Li, Y Z Chen, 2007, Mini reviews in medicinal chemistry.

Synergistic therapeutic actions of herbal ingredients and their mechanisms from molecular interaction and network perspectives.

B Xie, Y Z Chen, Y. Z. Chen, 2009, Drug discovery today.

Predicting targeted polypharmacology for drug repositioning and multi- target drug discovery.

Y Z Chen, S Y Yang, F. Zhu, 2013, Current medicinal chemistry.

Application of support vector machines to in silico prediction of cytochrome p450 enzyme substrates and inhibitors.

Z R Li, Z. R. Li, C W Yap, 2006, Current topics in medicinal chemistry.

Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins.

Z R Li, Z. R. Li, C W Yap, 2007, Journal of pharmaceutical sciences.

Virtual screening of selective multitarget kinase inhibitors by combinatorial support vector machines.

Y Z Chen, B. C. Low, X. H. Ma, 2010, Molecular pharmaceutics.

Prediction of compounds with specific pharmacodynamic, pharmacokinetic or toxicological property by statistical learning methods.

Z R Li, Z. R. Li, C W Yap, 2006, Mini reviews in medicinal chemistry.

Traditional Chinese medicine information database.

Y Z Chen, Y. Z. Chen, Z. Cao, 2005, Clinical pharmacology and therapeutics.

Classification of a diverse set of Tetrahymena pyriformis toxicity chemical compounds from molecular descriptors by statistical learning methods.

C W Yap, H Li, Y Z Chen, 2006, Chemical research in toxicology.

Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries.

Y Z Chen, J. Jia, C. Qin, 2012, Journal of molecular graphics & modelling.