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AbstractIn this paper a pattern recognition approach to classifying quantitative structure-property relationships (QSPR) of the CYP2C19 isoform is presented. QSPR is a correlative computer modelling of the properties of chemical molecules and is widely used in cheminformatics and the pharmaceutical industry. Predicting whether or not a particular chemical will be metabolized by 2C19 is of primary importance to the pharmaceutical industry. This task poses certain challenges. First of alldoi:10.2478/s11536-011-0120-3 fatcat:axbhk2pconhg5fp56r4ax3t5ge