Qingda Zang

In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning

Antony J. Williams, Kamel Mansouri, Richard S. Judson, 2017, J. Chem. Inf. Model..

Binary Classification of a Large Collection of Environmental Chemicals from Estrogen Receptor Assays by Quantitative Structure-Activity Relationship and Machine Learning Methods

Richard S. Judson, Qingda Zang, Daniel M. Rotroff, 2013, J. Chem. Inf. Model..

ehp CERAPP : Collaborative Estrogen Receptor Activity Prediction Project

Ruili Huang, Igor V. Tetko, Eva Bay Wedebye, 2016 .

Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants.

Lucinda F Buhse, Moheb Nasr, Qingda Zang, 2011, Journal of pharmaceutical and biomedical analysis.

Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques.

Lucinda F Buhse, Moheb Nasr, Qingda Zang, 2011, Analytical chemistry.

Determination of galactosamine impurities in heparin samples by multivariate regression analysis of their 1H NMR spectra

William J. Welsh, Lucinda F. Buhse, Moheb Nasr, 2011, Analytical and bioanalytical chemistry.

Prediction of skin sensitization potency using machine learning approaches

David Allen, Nicole Kleinstreuer, Judy Strickland, 2017, Journal of applied toxicology : JAT.

CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

Ruili Huang, Igor V. Tetko, Eva Bay Wedebye, 2016, Environmental health perspectives.

Multivariate models for prediction of human skin sensitization hazard

David Allen, Nicole Kleinstreuer, Judy Strickland, 2017, Journal of applied toxicology : JAT.