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Methods in Molecular Biology (Clifton, N.J.)
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June 18, 2016
In Silico Study of In Vitro GPCR Assays by QSAR Modeling
Kamel Mansouri, Richard S Judson
Environmental Science & Technology
|
September 28, 2019
Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Lethal Concentrations and Points of Departure
Thomas Y Sheffield, Richard S Judson
Plos One
|
July 26, 2018
Uncertainty quantification in ToxCast high throughput screening
Eric D Watt, Richard S Judson
Journal of Cheminformatics
|
September 20, 2018
Exploring non-linear distance metrics in the structure-activity space: QSAR models for human estrogen receptor
Ilya A Balabin, Richard S Judson
Toxicology Mechanisms and Methods
|
December 22, 2009
Toxicity data informatics: supporting a new paradigm for toxicity prediction
Ann M Richard, Chihae Yang, Richard S Judson
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
Toxicology and Applied Pharmacology
|
July 21, 2019
Identification of potential endocrine disrupting chemicals using gene expression biomarkers
J Christopher Corton, Nicole C Kleinstreuer, Richard S Judson
Toxicological Sciences : an Official Journal of the Society of Toxicology
|
August 13, 2010
A novel framework for predicting in vivo toxicities from in vitro data using optimal methods for dense and sparse matrix reordering and logistic regression
Peter A DiMaggio, Ashwin Subramani, Richard S Judson, et al.
Regulatory Toxicology and Pharmacology : RTP
|
March 1, 2017
Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study
Richard S Judson, Matthew T Martin, Grace Patlewicz, et al.
Journal of Cheminformatics
|
March 10, 2018
OPERA models for predicting physicochemical properties and environmental fate endpoints
Kamel Mansouri, Chris M Grulke, Richard S Judson, et al.
Page
of 11
Search research articles
Search
Showing results (1-10 of 103) with videos related to
Sort By:
Page
of 11
Methods in Molecular Biology (Clifton, N.J.)
|
June 18, 2016
In Silico Study of In Vitro GPCR Assays by QSAR Modeling
Kamel Mansouri, Richard S Judson
Environmental Science & Technology
|
September 28, 2019
Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Lethal Concentrations and Points of Departure
Thomas Y Sheffield, Richard S Judson
Plos One
|
July 26, 2018
Uncertainty quantification in ToxCast high throughput screening
Eric D Watt, Richard S Judson
Journal of Cheminformatics
|
September 20, 2018
Exploring non-linear distance metrics in the structure-activity space: QSAR models for human estrogen receptor
Ilya A Balabin, Richard S Judson
Toxicology Mechanisms and Methods
|
December 22, 2009
Toxicity data informatics: supporting a new paradigm for toxicity prediction
Ann M Richard, Chihae Yang, Richard S Judson
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
Toxicology and Applied Pharmacology
|
July 21, 2019
Identification of potential endocrine disrupting chemicals using gene expression biomarkers
J Christopher Corton, Nicole C Kleinstreuer, Richard S Judson
Toxicological Sciences : an Official Journal of the Society of Toxicology
|
August 13, 2010
A novel framework for predicting in vivo toxicities from in vitro data using optimal methods for dense and sparse matrix reordering and logistic regression
Peter A DiMaggio, Ashwin Subramani, Richard S Judson, et al.
Regulatory Toxicology and Pharmacology : RTP
|
March 1, 2017
Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study
Richard S Judson, Matthew T Martin, Grace Patlewicz, et al.
Journal of Cheminformatics
|
March 10, 2018
OPERA models for predicting physicochemical properties and environmental fate endpoints
Kamel Mansouri, Chris M Grulke, Richard S Judson, et al.
Page
of 11