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Critical Reviews in Toxicology
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July 24, 2013
Hepatotoxicity: a scheme for generating chemical categories for read-across, structural alerts and insights into mechanism(s) of action
M Hewitt, S J Enoch, J C Madden, et al.
Reproductive Toxicology (Elmsford, N.Y.)
|
December 17, 2009
Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity
M Hewitt, C M Ellison, S J Enoch, et al.
General Physiology and Biophysics
|
July 31, 2007
Antioxidant properties of carotenoids: QSAR prediction of their redox potentials
M Kleinová, M Hewitt, V Brezová, et al.
Environmental Toxicology and Chemistry
|
September 16, 2011
Database of published retention factors for immobilized artificial membrane HPLC and an assessment of the effect of experimental variability
M R Ledbetter, S Gutsell, G Hodges, et al.
Journal of Chemical Information and Modeling
|
April 15, 2011
Assessment of methods to define the applicability domain of structural alert models
C M Ellison, R Sherhod, M T D Cronin, et al.
Journal of Chemical Information and Modeling
|
November 3, 2009
In silico prediction of aqueous solubility: the solubility challenge
M Hewitt, M T D Cronin, S J Enoch, et al.
SAR and QSAR in Environmental Research
|
June 4, 2013
Prediction of immobilised artificial membrane chromatography retention factors using theoretical molecular fragments and structural features
M R Ledbetter, S Gutsell, G Hodges, et al.
Expert Opinion on Drug Metabolism & Toxicology
|
April 5, 2017
Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties
K R Przybylak, J C Madden, E Covey-Crump, et al.
Archives of Toxicology
|
June 4, 2014
Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes
M D Nelms, G Ates, J C Madden, et al.
SAR and QSAR in Environmental Research
|
December 10, 2013
Evaluation criteria for the quality of published experimental data on nanomaterials and their usefulness for QSAR modelling
L Lubinski, P Urbaszek, A Gajewicz, et al.
Page
of 3
Search research articles
Search
Showing results (11-20 of 24) with videos related to
Sort By:
Page
of 3
Critical Reviews in Toxicology
|
July 24, 2013
Hepatotoxicity: a scheme for generating chemical categories for read-across, structural alerts and insights into mechanism(s) of action
M Hewitt, S J Enoch, J C Madden, et al.
Reproductive Toxicology (Elmsford, N.Y.)
|
December 17, 2009
Integrating (Q)SAR models, expert systems and read-across approaches for the prediction of developmental toxicity
M Hewitt, C M Ellison, S J Enoch, et al.
General Physiology and Biophysics
|
July 31, 2007
Antioxidant properties of carotenoids: QSAR prediction of their redox potentials
M Kleinová, M Hewitt, V Brezová, et al.
Environmental Toxicology and Chemistry
|
September 16, 2011
Database of published retention factors for immobilized artificial membrane HPLC and an assessment of the effect of experimental variability
M R Ledbetter, S Gutsell, G Hodges, et al.
Journal of Chemical Information and Modeling
|
April 15, 2011
Assessment of methods to define the applicability domain of structural alert models
C M Ellison, R Sherhod, M T D Cronin, et al.
Journal of Chemical Information and Modeling
|
November 3, 2009
In silico prediction of aqueous solubility: the solubility challenge
M Hewitt, M T D Cronin, S J Enoch, et al.
SAR and QSAR in Environmental Research
|
June 4, 2013
Prediction of immobilised artificial membrane chromatography retention factors using theoretical molecular fragments and structural features
M R Ledbetter, S Gutsell, G Hodges, et al.
Expert Opinion on Drug Metabolism & Toxicology
|
April 5, 2017
Characterisation of data resources for in silico modelling: benchmark datasets for ADME properties
K R Przybylak, J C Madden, E Covey-Crump, et al.
Archives of Toxicology
|
June 4, 2014
Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes
M D Nelms, G Ates, J C Madden, et al.
SAR and QSAR in Environmental Research
|
December 10, 2013
Evaluation criteria for the quality of published experimental data on nanomaterials and their usefulness for QSAR modelling
L Lubinski, P Urbaszek, A Gajewicz, et al.
Page
of 3