Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Michael Fernández

Showing results (1-10 of 41) with videos related to

Pageof 5
Sort By:
Journal of Molecular Graphics & Modelling|April 1, 2006
Bayesian-regularized genetic neural networks applied to the modeling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptorMichael Fernández, Julio Caballero
Current Topics in Medicinal Chemistry|December 17, 2008
Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1)Julio Caballero, Michael Fernández
Journal of Molecular Modeling|January 12, 2007
QSAR models for predicting the activity of non-peptide luteinizing hormone-releasing hormone (LHRH) antagonists derived from erythromycin A using quantum chemical propertiesMichael Fernández, Julio Caballero
Bioorganic & Medicinal Chemistry|June 26, 2007
QSAR modeling of matrix metalloproteinase inhibition by N-hydroxy-alpha-phenylsulfonylacetamide derivativesMichael Fernández, Julio Caballero
Chemical Biology & Drug Design|November 16, 2006
Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprinesMichael Fernández, Julio Caballero
Journal of Molecular Modeling|October 6, 2005
Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networksJulio Caballero, Michael Fernández
Bioorganic & Medicinal Chemistry|October 6, 2005
Modeling of activity of cyclic urea HIV-1 protease inhibitors using regularized-artificial neural networksMichael Fernández, Julio Caballero
Nucleic Acids Research|February 14, 2012
Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machinesMichael Fernández, Diego Miranda-Saavedra
Journal of Computer-Aided Molecular Design|December 24, 2005
Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+ -activated K+ channel by some triarylmethanes using topological charge indexes descriptorsJulio Caballero, Miguel Garriga, Michael Fernández
Bioorganic & Medicinal Chemistry|January 31, 2006
2D Autocorrelation modeling of the negative inotropic activity of calcium entry blockers using Bayesian-regularized genetic neural networksJulio Caballero, Miguel Garriga, Michael Fernández
Pageof 5

Showing results (1-10 of 41) with videos related to

Sort By:
Pageof 5
Journal of Molecular Graphics & Modelling|April 1, 2006
Bayesian-regularized genetic neural networks applied to the modeling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptorMichael Fernández, Julio Caballero
Current Topics in Medicinal Chemistry|December 17, 2008
Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1)Julio Caballero, Michael Fernández
Journal of Molecular Modeling|January 12, 2007
QSAR models for predicting the activity of non-peptide luteinizing hormone-releasing hormone (LHRH) antagonists derived from erythromycin A using quantum chemical propertiesMichael Fernández, Julio Caballero
Bioorganic & Medicinal Chemistry|June 26, 2007
QSAR modeling of matrix metalloproteinase inhibition by N-hydroxy-alpha-phenylsulfonylacetamide derivativesMichael Fernández, Julio Caballero
Chemical Biology & Drug Design|November 16, 2006
Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprinesMichael Fernández, Julio Caballero
Journal of Molecular Modeling|October 6, 2005
Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networksJulio Caballero, Michael Fernández
Bioorganic & Medicinal Chemistry|October 6, 2005
Modeling of activity of cyclic urea HIV-1 protease inhibitors using regularized-artificial neural networksMichael Fernández, Julio Caballero
Nucleic Acids Research|February 14, 2012
Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machinesMichael Fernández, Diego Miranda-Saavedra
Journal of Computer-Aided Molecular Design|December 24, 2005
Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+ -activated K+ channel by some triarylmethanes using topological charge indexes descriptorsJulio Caballero, Miguel Garriga, Michael Fernández
Bioorganic & Medicinal Chemistry|January 31, 2006
2D Autocorrelation modeling of the negative inotropic activity of calcium entry blockers using Bayesian-regularized genetic neural networksJulio Caballero, Miguel Garriga, Michael Fernández
Pageof 5