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B T Fan

Showing results (21-30 of 38) with videos related to

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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.
Journal of Chemical Information and Computer Sciences|May 28, 2003
Diagnosing breast cancer based on support vector machinesH X Liu, R S Zhang, F Luan, et al.
Journal of Chemical Information and Computer Sciences|November 24, 2004
Quantitative prediction of logk of peptides in high-performance liquid chromatography based on molecular descriptors by using the heuristic method and support vector machineH X Liu, C X Xue, R S Zhang, et al.
Journal of Computer-Aided Molecular Design|August 2, 2005
The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machineH X Liu, R J Hu, R S Zhang, 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.
Journal of Chemical Information and Computer Sciences|September 28, 2004
QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machineC X Xue, R S Zhang, H X Liu, et al.
SAR and QSAR in Environmental Research|July 6, 2000
Prediction of programmed-temperature retention values of naphthas by artificial neural networksJ H Qi, X Y Zhang, R S Zhang, et al.
Journal of Chemical Information and Computer Sciences|March 23, 2004
An accurate QSPR study of O-H bond dissociation energy in substituted phenols based on support vector machinesC X Xue, R S Zhang, H X Liu, et al.
Talanta|October 31, 2008
Application of artificial neural networks in multifactor optimization of an on-line microwave FIA system for catalytic kinetic determination of ruthenium (III)Y B Zeng, H P Xu, H T Liu, et al.
Pageof 4

Showing results (21-30 of 38) with videos related to

Sort By:
Pageof 4
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.
Journal of Chemical Information and Computer Sciences|May 28, 2003
Diagnosing breast cancer based on support vector machinesH X Liu, R S Zhang, F Luan, et al.
Journal of Chemical Information and Computer Sciences|November 24, 2004
Quantitative prediction of logk of peptides in high-performance liquid chromatography based on molecular descriptors by using the heuristic method and support vector machineH X Liu, C X Xue, R S Zhang, et al.
Journal of Computer-Aided Molecular Design|August 2, 2005
The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machineH X Liu, R J Hu, R S Zhang, 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.
Journal of Chemical Information and Computer Sciences|September 28, 2004
QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machineC X Xue, R S Zhang, H X Liu, et al.
SAR and QSAR in Environmental Research|July 6, 2000
Prediction of programmed-temperature retention values of naphthas by artificial neural networksJ H Qi, X Y Zhang, R S Zhang, et al.
Journal of Chemical Information and Computer Sciences|March 23, 2004
An accurate QSPR study of O-H bond dissociation energy in substituted phenols based on support vector machinesC X Xue, R S Zhang, H X Liu, et al.
Talanta|October 31, 2008
Application of artificial neural networks in multifactor optimization of an on-line microwave FIA system for catalytic kinetic determination of ruthenium (III)Y B Zeng, H P Xu, H T Liu, et al.
Pageof 4