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Journal of Chemical Information and Modeling
|
November 28, 2013
Binary classification of a large collection of environmental chemicals from estrogen receptor assays by quantitative structure-activity relationship and machine learning methods
Qingda Zang, Daniel M Rotroff, Richard S Judson
Journal of Chemical Information and Modeling
|
December 24, 2016
In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning
Qingda Zang, Kamel Mansouri, Antony J Williams, et al.
Journal of Applied Toxicology : JAT
|
August 3, 2016
Multivariate models for prediction of human skin sensitization hazard
Judy Strickland, Qingda Zang, Michael Paris, et al.
Journal of Applied Toxicology : JAT
|
January 12, 2017
Prediction of skin sensitization potency using machine learning approaches
Qingda Zang, Michael Paris, David M Lehmann, et al.
Journal of Applied Toxicology : JAT
|
February 7, 2016
Integrated decision strategies for skin sensitization hazard
Judy Strickland, Qingda Zang, Nicole Kleinstreuer, et al.
Journal of Pharmaceutical and Biomedical Analysis
|
January 11, 2011
Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical Chemistry
|
January 4, 2011
Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical and Bioanalytical Chemistry
|
October 19, 2010
Determination of galactosamine impurities in heparin samples by multivariate regression analysis of their (1)H NMR spectra
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical and Bioanalytical Chemistry
|
June 17, 2011
Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data
Qingda Zang, David A Keire, Lucinda F Buhse, et al.
Critical Reviews in Toxicology
|
February 24, 2018
Non-animal methods to predict skin sensitization (II): an assessment of defined approaches <sup>*</sup>
Nicole C Kleinstreuer, Sebastian Hoffmann, Nathalie Alépée, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Journal of Chemical Information and Modeling
|
November 28, 2013
Binary classification of a large collection of environmental chemicals from estrogen receptor assays by quantitative structure-activity relationship and machine learning methods
Qingda Zang, Daniel M Rotroff, Richard S Judson
Journal of Chemical Information and Modeling
|
December 24, 2016
In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning
Qingda Zang, Kamel Mansouri, Antony J Williams, et al.
Journal of Applied Toxicology : JAT
|
August 3, 2016
Multivariate models for prediction of human skin sensitization hazard
Judy Strickland, Qingda Zang, Michael Paris, et al.
Journal of Applied Toxicology : JAT
|
January 12, 2017
Prediction of skin sensitization potency using machine learning approaches
Qingda Zang, Michael Paris, David M Lehmann, et al.
Journal of Applied Toxicology : JAT
|
February 7, 2016
Integrated decision strategies for skin sensitization hazard
Judy Strickland, Qingda Zang, Nicole Kleinstreuer, et al.
Journal of Pharmaceutical and Biomedical Analysis
|
January 11, 2011
Combining (1)H NMR spectroscopy and chemometrics to identify heparin samples that may possess dermatan sulfate (DS) impurities or oversulfated chondroitin sulfate (OSCS) contaminants
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical Chemistry
|
January 4, 2011
Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical and Bioanalytical Chemistry
|
October 19, 2010
Determination of galactosamine impurities in heparin samples by multivariate regression analysis of their (1)H NMR spectra
Qingda Zang, David A Keire, Richard D Wood, et al.
Analytical and Bioanalytical Chemistry
|
June 17, 2011
Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data
Qingda Zang, David A Keire, Lucinda F Buhse, et al.
Critical Reviews in Toxicology
|
February 24, 2018
Non-animal methods to predict skin sensitization (II): an assessment of defined approaches <sup>*</sup>
Nicole C Kleinstreuer, Sebastian Hoffmann, Nathalie Alépée, et al.
Page
of 2