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John B O Mitchell

Showing results (11-20 of 80) with videos related to

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Bioinformatics (Oxford, England)|March 19, 2010
A machine learning approach to predicting protein-ligand binding affinity with applications to molecular dockingPedro J Ballester, John B O Mitchell
BMC Bioinformatics|June 3, 2014
From sequence to enzyme mechanism using multi-label machine learningLuna De Ferrari, John B O Mitchell
Molecular Pharmaceutics|June 12, 2014
Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules?David S Palmer, John B O Mitchell
Journal of Chemical Information and Modeling|May 20, 2011
Comments on "leave-cluster-out cross-validation is appropriate for scoring functions derived from diverse protein data sets": significance for the validation of scoring functionsPedro J Ballester, John B O Mitchell
Organic & Biomolecular Chemistry|November 10, 2004
A structure-odour relationship study using EVA descriptors and hierarchical clusteringShin-ya Takane, John B O Mitchell
ACS Omega|August 19, 2024
Revisiting the Application of Machine Learning Approaches in Predicting Aqueous SolubilityTianyuan Zheng, John B O Mitchell, Simon Dobson
Journal of Cheminformatics|December 15, 2017
Can human experts predict solubility better than computers?Samuel Boobier, Anne Osbourn, John B O Mitchell
Current Medicinal Chemistry|July 15, 2017
Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening ApproachesJelica Vucicevic, Katarina Nikolic, John B O Mitchell
BMC Bioinformatics|July 4, 2013
PFClust: a novel parameter free clustering algorithmLazaros Mavridis, Neetika Nath, John B O Mitchell
Journal of Molecular Evolution|September 5, 2014
One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic treesRosanna G Alderson, Daniel Barker, John B O Mitchell
Pageof 8

Showing results (11-20 of 80) with videos related to

Sort By:
Pageof 8
Bioinformatics (Oxford, England)|March 19, 2010
A machine learning approach to predicting protein-ligand binding affinity with applications to molecular dockingPedro J Ballester, John B O Mitchell
BMC Bioinformatics|June 3, 2014
From sequence to enzyme mechanism using multi-label machine learningLuna De Ferrari, John B O Mitchell
Molecular Pharmaceutics|June 12, 2014
Is experimental data quality the limiting factor in predicting the aqueous solubility of druglike molecules?David S Palmer, John B O Mitchell
Journal of Chemical Information and Modeling|May 20, 2011
Comments on "leave-cluster-out cross-validation is appropriate for scoring functions derived from diverse protein data sets": significance for the validation of scoring functionsPedro J Ballester, John B O Mitchell
Organic & Biomolecular Chemistry|November 10, 2004
A structure-odour relationship study using EVA descriptors and hierarchical clusteringShin-ya Takane, John B O Mitchell
ACS Omega|August 19, 2024
Revisiting the Application of Machine Learning Approaches in Predicting Aqueous SolubilityTianyuan Zheng, John B O Mitchell, Simon Dobson
Journal of Cheminformatics|December 15, 2017
Can human experts predict solubility better than computers?Samuel Boobier, Anne Osbourn, John B O Mitchell
Current Medicinal Chemistry|July 15, 2017
Rational Drug Design of Antineoplastic Agents Using 3D-QSAR, Cheminformatic, and Virtual Screening ApproachesJelica Vucicevic, Katarina Nikolic, John B O Mitchell
BMC Bioinformatics|July 4, 2013
PFClust: a novel parameter free clustering algorithmLazaros Mavridis, Neetika Nath, John B O Mitchell
Journal of Molecular Evolution|September 5, 2014
One origin for metallo-β-lactamase activity, or two? An investigation assessing a diverse set of reconstructed ancestral sequences based on a sample of phylogenetic treesRosanna G Alderson, Daniel Barker, John B O Mitchell
Pageof 8