Multiple linear regression and artificial neural network retention prediction models for ginsenosides on a polyamine-bonded stationary phase in hydrophilic interaction chromatography

Journal of Separation Science

Volumn 31, Issue 9, 2008, Pages 1550-1563

  Quiming, Noel S ^a,b   Denola, Nerissa L ^a,b   Saito, Yoshihiro ^a   Jinno, Kiyokatsu ^a  

^a TOYOHASHI UNIVERSITY OF TECHNOLOGY   (Japan)

^b UNIVERSITY OF THE PHILIPPINES MANILA   (Philippines)

Author keywords

Artificial neural network; Ginsenosides; Hydrophilic interaction chromatography; Multiple linear regression; Polyamine bonded phase

Indexed keywords

ALGEBRA; BACKPROPAGATION; CHEMICALS; CHROMATOGRAPHIC ANALYSIS; CHROMATOGRAPHY; EIGENVALUES AND EIGENFUNCTIONS; FLOW INTERACTIONS; FOOD PROCESSING; FORECASTING; IMAGE CLASSIFICATION; LINEAR REGRESSION; LIQUID CHROMATOGRAPHY; MATHEMATICAL MODELS; NEURAL NETWORKS; PHASE BEHAVIOR; REGRESSION ANALYSIS; RHENIUM; THEOREM PROVING; THERMAL LOGGING;

ANALYTES; ARTIFICIAL NEURAL NETWORK (ANNS); GINSENOSIDES (GS); HYDROPHILIC INTERACTION CHROMATOGRAPHY (HILIC); MOBILE PHASE; MOBILE-PHASE COMPOSITIONS; MULTIPLE LINEAR REGRESSION (MLR); MULTIPLE LINEAR REGRESSION (MLR) MODELS; POLY(OXYALKYLENE)-AMINE; PREDICTIVE ABILITIES; RETENTION BEHAVIORS; RETENTION FACTOR (RF); RETENTION PREDICTION; STATIONARY PHASE (SP); TEMPERATURE CONDITIONS;

HYDROPHILICITY;

GINSENOSIDE; GINSENOSIDE RB 1; GINSENOSIDE RB 2; GINSENOSIDE RC; GINSENOSIDE RD; GINSENOSIDE RE; GINSENOSIDE RF; POLYAMINE; SAPONIN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHROMATOGRAPHY; COLUMN CHROMATOGRAPHY; COMPUTER MODEL; CONTROLLED STUDY; DEPENDENT VARIABLE; DRUG DETERMINATION; DRUG STRUCTURE; HYDROPHILIC INTERACTION CHROMATOGRAPHY; INTERMETHOD COMPARISON; MULTIPLE LINEAR REGRESSION ANALYSIS; PHASE SEPARATION; PREDICTOR VARIABLE; PRIORITY JOURNAL; SEPARATION TECHNIQUE; SOLUTE; TEMPERATURE SENSITIVITY;

CHROMATOGRAPHY, HIGH PRESSURE LIQUID; CHROMATOGRAPHY, LIQUID; DATABASES, FACTUAL; GINSENOSIDES; INDICATORS AND REAGENTS; LINEAR MODELS; MODELS, THEORETICAL; MOLECULAR STRUCTURE; NEURAL NETWORKS (COMPUTER); PANAX; PHASE TRANSITION; POLYAMINES; SOLUTIONS; TEMPERATURE;

EID: 45949110373     PISSN: 16159306     EISSN: 16159314     Source Type: Journal    
DOI: 10.1002/jssc.200800077     Document Type: Article

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