کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1216749 | 1494120 | 2012 | 11 صفحه PDF | دانلود رایگان |
A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (log kw). The overall best model was the SVM one built using descriptors selected by ACO.
► Ant Colony Optimization, Relief, Stepwise regression and Genetic Algorithm as descriptor selection methods.
► SVM and MLR methods to model retention factors of the 83 diverse drugs.
► A slight preference may go to the ACO/SVMR model.
Journal: Journal of Chromatography B - Volume 910, 1 December 2012, Pages 84–94