Simultaneous RP-HPLC-DAD separation, and determination of flavonoids and phenolic acids in Plantago L. species.

A rapid reversed-phase (RP) high-performance liquid chromatography method was developed and applied for simultaneous separation, and determination of flavonoids and phenolic acids in eight Plantago L. taxa (P. altissima L.

Novel approach to evolutionary neural network based descriptor selection and QSAR model development.

Capability of evolutionary neural network (ENN) based QSAR approach to direct the descriptor selection process towards stable descriptor subset (DS) composition characterized by acceptable generalization, as well as the influence of description stability on QSAR model interpretation have been examined. In order to analyze the DS stability and QSAR model generalization properties multiple random dataset partitions into training and test set were made. Acceptability criteria proposed by Golbraikh et al.

Evaluation of novel sample identification approach based on chromatographic fingerprint set correlation homogeneity analysis.

Instead of usual rationale for chromatographic fingerprint based sample identification which relies upon visual inspection or principal component analysis of raw or aligned chromatograms novel nonparametric statistical measure of fingerprint set homogeneity is proposed. Randomization test is applied for significance analysis of fingerprint set homogeneity while average maximum crosscorrelation is used as a merit function. Chromatogram sets generated by random selection from standard and unknown sample chromatogram collections are compared with respect to merit function values with set of chromatograms that represents standard and/or unknown sample.

Optimization of artificial neural networks used for retention modelling in ion chromatography.

The aim of this work is the development of an artificial neural network model, which can be generalized and used in a variety of applications for retention modelling in ion chromatography. Influences of eluent flow-rate and concentration of eluent anion (OH-) on separation of seven inorganic anions (fluoride, chloride, nitrite, sulfate, bromide, nitrate, and phosphate) were investigated. Parallel prediction of retention times of seven inorganic anions by using one artificial neural network was applied.