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P Doucet

Showing results (51-60 of 66) with videos related to

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The EMBO Journal|January 1, 1990
Chromaffin cell scinderin, a novel calcium-dependent actin filament-severing proteinA Rodriguez Del Castillo, S Lemaire, L Tchakarov, et al.
SAR and QSAR in Environmental Research|February 5, 2004
Comparative study of non nucleoside inhibitors with HIV-1 reverse transcriptase based on 3D-QSAR and dockingH F Chen, X J Yao, Q Li, et al.
SAR and QSAR in Environmental Research|March 4, 2006
Quantitative structure-toxicity relationships (QSTRs): a comparative study of various non linear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- aromatics to Tetrahymena pyriformisA Panaye, B T Fan, J P Doucet, et al.
Pediatrics|December 20, 2015
Sign Language and Spoken Language for Children With Hearing Loss: A Systematic ReviewElizabeth M Fitzpatrick, Candyce Hamel, Adrienne Stevens, et al.
SAR and QSAR in Environmental Research|June 20, 2002
Theoretical study of fast repair of DNA damage by cistanoside C and analogs: mechanism and dockingO Sperandio, B T Fan, K Zakrzewska, et al.
SAR and QSAR in Environmental Research|September 26, 2003
Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and dockingH F Chen, X C Dong, B S Zen, et al.
Acta Psychiatrica Scandinavica|April 11, 2006
Cognitive behaviour therapy and medication in the treatment of obsessive-compulsive disorderK P O'Connor, F Aardema, S Robillard, et al.
SAR and QSAR in Environmental Research|February 7, 2003
Docking study of cistanoside C to telomeric DNA fragmentO Delalande, K Gao, B T Fan, et al.
Journal of Chemical Information and Computer Sciences|July 27, 2004
Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regressionX J Yao, A Panaye, J P Doucet, et al.
Journal of Chemical Information and Computer Sciences|June 28, 2002
Quantitative prediction of liquid chromatography retention of N-benzylideneanilines based on quantum chemical parameters and radial basis function neural networkY H Xiang, M C Liu, X Y Zhang, et al.
Pageof 7

Showing results (51-60 of 66) with videos related to

Sort By:
Pageof 7
The EMBO Journal|January 1, 1990
Chromaffin cell scinderin, a novel calcium-dependent actin filament-severing proteinA Rodriguez Del Castillo, S Lemaire, L Tchakarov, et al.
SAR and QSAR in Environmental Research|February 5, 2004
Comparative study of non nucleoside inhibitors with HIV-1 reverse transcriptase based on 3D-QSAR and dockingH F Chen, X J Yao, Q Li, et al.
SAR and QSAR in Environmental Research|March 4, 2006
Quantitative structure-toxicity relationships (QSTRs): a comparative study of various non linear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- aromatics to Tetrahymena pyriformisA Panaye, B T Fan, J P Doucet, et al.
Pediatrics|December 20, 2015
Sign Language and Spoken Language for Children With Hearing Loss: A Systematic ReviewElizabeth M Fitzpatrick, Candyce Hamel, Adrienne Stevens, et al.
SAR and QSAR in Environmental Research|June 20, 2002
Theoretical study of fast repair of DNA damage by cistanoside C and analogs: mechanism and dockingO Sperandio, B T Fan, K Zakrzewska, et al.
SAR and QSAR in Environmental Research|September 26, 2003
Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and dockingH F Chen, X C Dong, B S Zen, et al.
Acta Psychiatrica Scandinavica|April 11, 2006
Cognitive behaviour therapy and medication in the treatment of obsessive-compulsive disorderK P O'Connor, F Aardema, S Robillard, et al.
SAR and QSAR in Environmental Research|February 7, 2003
Docking study of cistanoside C to telomeric DNA fragmentO Delalande, K Gao, B T Fan, et al.
Journal of Chemical Information and Computer Sciences|July 27, 2004
Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regressionX J Yao, A Panaye, J P Doucet, et al.
Journal of Chemical Information and Computer Sciences|June 28, 2002
Quantitative prediction of liquid chromatography retention of N-benzylideneanilines based on quantum chemical parameters and radial basis function neural networkY H Xiang, M C Liu, X Y Zhang, et al.
Pageof 7