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Journal of Chemical Information and Computer Sciences|July 1, 1996
Neural network studies. 2. Variable selectionI V Tetko, A E Villa, D J LivingstoneJournal of Chemical Information and Modeling|April 3, 2012
PLS-optimal: a stepwise D-optimal design based on latent variablesStefan Brandmaier, Ullrika Sahlin, Igor V Tetko, et al.Journal of Computer-Aided Molecular Design|November 3, 2019
Focused Library Generator: case of Mdmx inhibitorsZhonghua Xia, Pavel Karpov, Grzegorz Popowicz, et al.Journal of Pharmaceutical Sciences|February 9, 1999
Prediction of partition coefficient based on atom-type electrotopological state indicesJ J Huuskonen, A E Villa, I V TetkoJournal of Medicinal Chemistry|July 13, 2001
Volume learning algorithm artificial neural networks for 3D QSAR studiesI V Tetko, V V Kovalishyn, D J LivingstoneJournal of Medicinal Chemistry|April 2, 1993
Applications of neural networks in structure-activity relationships of a small number of moleculesI V Tetko, A I Luik, G I PodaJournal of Chemical Information and Computer Sciences|October 18, 2001
Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indicesI V Tetko, V Y Tanchuk, A E VillaCurrent Medicinal Chemistry|February 14, 2006
In silico approaches to prediction of aqueous and DMSO solubility of drug-like compounds: trends, problems and solutionsKonstantin V Balakin, Nikolay P Savchuk, Igor V TetkoNucleic Acids Research|January 13, 2006
A systematic approach to infer biological relevance and biases of gene network structuresAlexey V Antonov, Igor V Tetko, Hans W MewesJournal of Cheminformatics|January 26, 2016
The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTSIgor V Tetko, Daniel M Lowe, Antony J WilliamsPageof 15