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I V Tetko

Showing results (1-10 of 30) with videos related to

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Journal of Neuroscience Methods|February 13, 2001
A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 1. Detection of repeated patternsI V Tetko, A E Villa
Journal of Neuroscience Methods|February 13, 2001
A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 2. Application to simultaneous single unit recordingsI V Tetko, A E Villa
Journal of Computer-Aided Molecular Design|March 1, 1997
Data modelling with neural networks: advantages and limitationsD J Livingstone, D T Manallack, I V Tetko
Journal of Chemical Information and Computer Sciences|July 1, 1996
Neural network studies. 2. Variable selectionI V Tetko, A E Villa, D J Livingstone
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 Tetko
Journal 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 Villa
Journal of Medicinal Chemistry|July 13, 2001
Volume learning algorithm artificial neural networks for 3D QSAR studiesI V Tetko, V V Kovalishyn, D J Livingstone
Journal 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 Poda
Bio Systems|February 13, 2001
Non-linear cortico-cortical interactions modulated by cholinergic afferences from the rat basal forebrainA E Villa, I V Tetko, P Dutoit, et al.
Bio Systems|January 14, 1999
Dynamical cell assemblies in the rat auditory cortex in a reaction-time taskA E Villa, B Hyland, I V Tetko, et al.
Pageof 3

Showing results (1-10 of 30) with videos related to

Sort By:
Pageof 3
Journal of Neuroscience Methods|February 13, 2001
A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 1. Detection of repeated patternsI V Tetko, A E Villa
Journal of Neuroscience Methods|February 13, 2001
A pattern grouping algorithm for analysis of spatiotemporal patterns in neuronal spike trains. 2. Application to simultaneous single unit recordingsI V Tetko, A E Villa
Journal of Computer-Aided Molecular Design|March 1, 1997
Data modelling with neural networks: advantages and limitationsD J Livingstone, D T Manallack, I V Tetko
Journal of Chemical Information and Computer Sciences|July 1, 1996
Neural network studies. 2. Variable selectionI V Tetko, A E Villa, D J Livingstone
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 Tetko
Journal 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 Villa
Journal of Medicinal Chemistry|July 13, 2001
Volume learning algorithm artificial neural networks for 3D QSAR studiesI V Tetko, V V Kovalishyn, D J Livingstone
Journal 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 Poda
Bio Systems|February 13, 2001
Non-linear cortico-cortical interactions modulated by cholinergic afferences from the rat basal forebrainA E Villa, I V Tetko, P Dutoit, et al.
Bio Systems|January 14, 1999
Dynamical cell assemblies in the rat auditory cortex in a reaction-time taskA E Villa, B Hyland, I V Tetko, et al.
Pageof 3