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Methods in Molecular Biology (Clifton, N.J.)|October 29, 2010
Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library designJerry O Ebalunode, Weifan Zheng, Alexander TropshaMolecular Informatics|August 5, 2016
Drug Side Effect Profiles as Molecular Descriptors for Predictive Modeling of Target BioactivityNancy C Baker, Denis Fourches, Alexander TropshaMolecular Informatics|August 6, 2016
Comparative Analysis of QSAR-based vs. Chemical Similarity Based Predictors of GPCRs Binding AffinityMan Luo, Xiang S Wang, Alexander TropshaJournal of Medicinal Chemistry|November 11, 2005
Application of validated QSAR models of D1 dopaminergic antagonists for database miningScott Oloff, Richard B Mailman, Alexander TropshaJournal of Chemical Information and Modeling|January 4, 2021
OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug DesignMaria Korshunova, Boris Ginsburg, Alexander Tropsha, et al.Journal of Controlled Release : Official Journal of the Controlled Release Society|November 5, 2013
Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loadingAhuva Cern, Yechezkel Barenholz, Alexander Tropsha, et al.Environmental Health Perspectives|April 17, 2008
Use of cell viability assay data improves the prediction accuracy of conventional quantitative structure-activity relationship models of animal carcinogenicityHao Zhu, Ivan Rusyn, Ann Richard, et al.Journal of Chemical Information and Modeling|November 21, 2013
Data set modelability by QSARAlexander Golbraikh, Eugene Muratov, Denis Fourches, et al.Journal of Chemical Information and Modeling|February 7, 2017
Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundSStephen J Capuzzi, Eugene N Muratov, Alexander TropshaBioinformatics (Oxford, England)|October 5, 2010
Chembench: a cheminformatics workbenchTheo Walker, Christopher M Grulke, Diane Pozefsky, et al.Pageof 26