> My colleague, Frank Burden (Monash University)
and I have used Bayesian
> regularized neural nets for QSAR. We find that they overcome virtually all of
> the problems with PLS QSAR models as they give the single statistically best
> model possible for the data set. In addition there are good theoretical
> why they do not require cross validation or test sets. We are investigating
> for QSAR and preliminary results suggest that this is the case.
> We have published some of this work recently:
>  New QSAR Methods Applied to Structure-Activity Mapping and
> Combinatorial Chemistry, Burden, F.R. and Winkler, D.A. J. Chem. Inf.
> Comput. Sci. 39, 236 (1999).
>  The Computer Simulation of High Throughput Screening of Bioactive
> Molecules, F.R. Burden, D.A. Winkler, in Molecular Modelling and Prediction
> of Bioactivity (K. Gundertofte and F.S. Jorgensen eds), Plenum Press 1998.
>  Robust QSAR Models Using Bayesian Regularised Artificial Neural
> Networks, Burden, F.R. and Winkler, D.A. J. Med. Chem., 1999; 42(16);
> 3187 (1999).
>  A QSAR Model for the Acute Toxicity of Substituted Benzenes towards
> Tetrahymena Pyriformis using Bayesian Regularized Neural Networks. F R.
> Burden* David A. Winkler, Chem. Res. Toxicol., in press.
>  Robust QSAR Models from Novel Descriptors and Bayesian Regularized
> Neural Networks, Winkler, D.A, Burden, F.R. Mol. Simul. 1999 in press.
>  Do QSAR Models using Bayesian Regularized Artificial Neural Networks
> Really Need Validation? Winkler, D.A. and Burden, F.R. J.Chem. Inf.
> Comput. Sci in preparation.
> Dr. David A. Winkler Email: dave.winkler -AatT-
> Senior Principal Research Scientist Voice: 61-3-9545-2477
> CSIRO Molecular Science Fax: 61-3-9545-2446
> Private Bag 10,Clayton South MDC 3169 http://www.csiro.au
> Australia http://www.molsci.csiro.au
Dr David Turner
Dept of Information Studies, Sheffield University
Sheffield, S10 2TN, UK Tel. 0114 2 222 650
E-mail: D.Turner -AatT- sheffield.ac.uk
Fax: 0114 2 780 300