Robust QSAR Models Using Bayesian Regularized Neural Networks
- 24 July 1999
- journal article
- research article
- Published by American Chemical Society (ACS) in Journal of Medicinal Chemistry
- Vol. 42 (16) , 3183-3187
- https://doi.org/10.1021/jm980697n
Abstract
We describe the use of Bayesian regularized artificial neural networks (BRANNs) in the development of QSAR models. These networks have the potential to solve a number of problems which arise in QSAR modeling such as: choice of model; robustness of model; choice of validation set; size of validation effort; and optimization of network architecture. The application of the methods to QSAR of compounds active at the benzodiazepine and muscarinic receptors is illustrated.Keywords
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