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Sean Ekins

Showing results (171-180 of 374) with videos related to

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Drug Discovery Today|February 24, 2009
Novel web-based tools combining chemistry informatics, biology and social networks for drug discoveryMoses Hohman, Kellan Gregory, Kelly Chibale, et al.
Journal of Computer-Aided Molecular Design|June 20, 2014
Bigger data, collaborative tools and the future of predictive drug discoverySean Ekins, Alex M Clark, S Joshua Swamidass, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|November 12, 2010
Identification and validation of novel human pregnane X receptor activators among prescribed drugs via ligand-based virtual screeningYongmei Pan, Linhao Li, Gregory Kim, et al.
European Journal of Medicinal Chemistry|November 21, 2020
Dispirotripiperazine-core compounds, their biological activity with a focus on broad antiviral property, and perspectives in drug design (mini-review)Anna Egorova, Elke Bogner, Elena Novoselova, et al.
Molecular Pharmaceutics|August 18, 2018
Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding PredictionDaniel P Russo, Kimberley M Zorn, Alex M Clark, et al.
ACS Chemical Neuroscience|May 14, 2025
Adverse Outcome Pathway and Machine Learning to Predict Drug Induced Seizure LiabilityThomas R Lane, Scott H Snyder, Joshua S Harris, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|September 26, 2006
Rapid identification of P-glycoprotein substrates and inhibitorsCheng Chang, Praveen M Bahadduri, James E Polli, et al.
ACS Omega|October 28, 2020
Machine Learning for Discovery of GSK3β InhibitorsPatricia A Vignaux, Eni Minerali, Daniel H Foil, et al.
ACS Omega|July 21, 2020
Pruned Machine Learning Models to Predict Aqueous SolubilityAlexander L Perryman, Daigo Inoyama, Jimmy S Patel, et al.
Toxicological Sciences : an Official Journal of the Society of Toxicology|September 3, 2025
The case for Equilibrative Nucleoside Transporters in current regulatory guidanceLucy Martinez-Guerrero, Xinyi Tang, Sean Ekins, et al.
Pageof 38

Showing results (171-180 of 374) with videos related to

Sort By:
Pageof 38
Drug Discovery Today|February 24, 2009
Novel web-based tools combining chemistry informatics, biology and social networks for drug discoveryMoses Hohman, Kellan Gregory, Kelly Chibale, et al.
Journal of Computer-Aided Molecular Design|June 20, 2014
Bigger data, collaborative tools and the future of predictive drug discoverySean Ekins, Alex M Clark, S Joshua Swamidass, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|November 12, 2010
Identification and validation of novel human pregnane X receptor activators among prescribed drugs via ligand-based virtual screeningYongmei Pan, Linhao Li, Gregory Kim, et al.
European Journal of Medicinal Chemistry|November 21, 2020
Dispirotripiperazine-core compounds, their biological activity with a focus on broad antiviral property, and perspectives in drug design (mini-review)Anna Egorova, Elke Bogner, Elena Novoselova, et al.
Molecular Pharmaceutics|August 18, 2018
Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding PredictionDaniel P Russo, Kimberley M Zorn, Alex M Clark, et al.
ACS Chemical Neuroscience|May 14, 2025
Adverse Outcome Pathway and Machine Learning to Predict Drug Induced Seizure LiabilityThomas R Lane, Scott H Snyder, Joshua S Harris, et al.
Drug Metabolism and Disposition: the Biological Fate of Chemicals|September 26, 2006
Rapid identification of P-glycoprotein substrates and inhibitorsCheng Chang, Praveen M Bahadduri, James E Polli, et al.
ACS Omega|October 28, 2020
Machine Learning for Discovery of GSK3β InhibitorsPatricia A Vignaux, Eni Minerali, Daniel H Foil, et al.
ACS Omega|July 21, 2020
Pruned Machine Learning Models to Predict Aqueous SolubilityAlexander L Perryman, Daigo Inoyama, Jimmy S Patel, et al.
Toxicological Sciences : an Official Journal of the Society of Toxicology|September 3, 2025
The case for Equilibrative Nucleoside Transporters in current regulatory guidanceLucy Martinez-Guerrero, Xinyi Tang, Sean Ekins, et al.
Pageof 38