Department of Chemistry, Ilam Branch, Islamic Azad University, Ilam, Iran.
Drug Test Anal. 2013 May;5(5):315-9. doi: 10.1002/dta.325. Epub 2011 Oct 19.
Genetic algorithm and partial least square (GA-PLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention time and descriptors for drug metabolites which obtained by two-dimensional liquid chromatography. The applied internal (leave-group-out cross validation (LGO-CV)) and external (test set) validation methods were used for the predictive power of four models. Both methods resulted in accurate prediction whereas more accurate results were obtained by L-M ANN model. The best model obtained from L-M ANN showed a good R(2) value (determination coefficient between observed and predicted values) for all compounds, which was superior to GA-PLS models.
遗传算法和偏最小二乘（GA-PLS）以及勒让德-马夸尔特人工神经网络（L-M ANN）技术被用于研究二维液相色谱获得的药物代谢物保留时间与描述符之间的相关性。应用内部（分组外留一交叉验证（LGO-CV））和外部（测试集）验证方法来评估四个模型的预测能力。两种方法都得到了准确的预测，而 L-M ANN 模型的结果更准确。从 L-M ANN 得到的最佳模型对所有化合物都表现出了良好的 R（2）值（观察值与预测值之间的决定系数），优于 GA-PLS 模型。
