Study on the quantitative relationship between the structures and electrophoretic mobilities of flavonoids in micellar electrokinetic capillary chromatography.
Quantitative structure-mobility relationship (QSMR) models were developed between the structures of flavonoids and their eletrophoretic mobilities in micellar electrokinetic capillary chromatography. Molecular descriptors calculated from structure alone are used to represent molecular structures, moreover, Nt was defined by ourselves. Multiple linear regression and radial basis function neural networks (RBFNNs) are utilized to construct the linear and nonlinear prediction model, respectively. The optimal QSMR model developed was based on a 3-10-1 RBFNNs architecture. The root mean square errors in mobilities predictions for the data set was 0.1083 mobility unit (10(-4) cm2 V(-1) s(-1)). The prediction results were in good agreement with the experimental values.
Wang
Shufang
S
Department of Chemistry Lanzhou University, Lanzhou 730000, Gansu Province, PR China.
Xue
Chunxia
C
Chen
Xingguo
X
Liu
Mancang
M
Hu
Zhide
Z
D020374:Chromatography, Micellar Electrokinetic Capillary / Q000379:methods*; D005419:Flavonoids / Q000032:analysis* / Q000737:chemistry; D015394:Molecular Structure; D016571:Neural Networks, Computer; D012044:Regression Analysis
D005419:Flavonoids