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Cizmarik, J.
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article
Thermal parameters of phenylcarbamic acid derivatives using calculated molecular descriptors with MLR and ANN: Quantitative structure-property relationship studies
Abstract
<p>The aim of this work was to build MLR and ANN models for predicting certain thermal parameters of phenylcarbamic acid derivatives. For 66 compounds belonging to this group DSC analysis was performed. Based on the DSC curves, nine thermal parameters were calculated. The chemical structure of newly synthesized local anaesthetic drugs was encoded in calculated theoretical descriptors. To build the QSPR models Multiple Linear Regression and Artificial Neural Networks were applied. The variable reduction in the case of MLR was performed by means of visual inspection of the significant loading plots obtained by Principal Component Analysis, but using forward selection. Two models of ANN were built: linear and non-linear, but for the reduction of the variables the genetic algorithm was applied. As a result, MLR and ANN models for predicting some thermal parameters of phenylcarbamic acid derivatives were obtained. © 2007 Springer Science+Business Media LLC.</p>