Artificial neural network modeling of pH dependent structural descriptor-mobility relationship for capillary zone electrophoresis of tripeptides

Journal of Liquid Chromatography and Related Technologies

Volumn 31, Issue 15, 2008, Pages 2348-2362

  Olajos, M ^a,b   Chovan T ^a   Mittermayr, S ^a,b   Kenesei, T ^a   Hajos, P ^a   Molnar I ^c   Darvas, F ^a   Guttman, A ^b  

^a UNIVERSITY OF PANNONIA   (Hungary)

^b UNIVERSITY OF INNSBRUCK   (Austria)

^c Institute of Applied Chromatography   (Germany)

Author keywords

Back propagation artificial neural network; Capillary zone electrophoresis; Multivariable linear regression; Peptide mobility modeling

Indexed keywords

AROMATIC COMPOUNDS; CAPILLARY ELECTROPHORESIS; ELECTRIC FIELDS; ELECTROCHEMISTRY; ELECTROMAGNETIC FIELD THEORY; ELECTROMAGNETIC FIELDS; ELECTROPHORESIS; ELECTROPHORETIC MOBILITY; FOOD PROCESSING; FORECASTING; IMAGE CLASSIFICATION; ISOMERS; NEURAL NETWORKS; REGRESSION ANALYSIS; SEPARATION;

ANN MODELING; APPLIED ELECTRIC FIELD; APPLIED VOLTAGES; ARTIFICIAL NEURAL NETWORK MODELING; BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; CAPILLARY ZONE ELECTROPHORESIS; COMPREHENSIVE ANALYSIS; DESCRIPTOR; ELECTROPHORETIC MIGRATION; EXPERIMENTAL DATA; HIGHER PRECISION; IONIC CHARGES; MULTIVARIABLE LINEAR REGRESSION; NON-POLAR; PEPTIDE MOBILITY MODELING; PH-DEPENDENT; POSITIVELY CHARGED; PREDICTING MODELS; PRESENT STAGE; SEPARATION LENGTH; SEPARATION PARAMETERS; TRI-PEPTIDES;

BACKPROPAGATION;

TRIPEPTIDE;

ACIDITY; ALKALINITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CAPILLARY ZONE ELECTROPHORESIS; DRUG STRUCTURE; ELECTROPHORETIC MOBILITY; LINEAR REGRESSION ANALYSIS; PH MEASUREMENT; PHYSICAL CHEMISTRY; SEPARATION TECHNIQUE; STRUCTURE ANALYSIS;

EID: 49449099400     PISSN: 10826076     EISSN: 1520572X     Source Type: Journal    
DOI: 10.1080/10826070802281935     Document Type: Article

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