Application of artificial neural networks in the prediction of product distribution in electrophoretically mediated microanalysis

Electrophoresis

Volumn 30, Issue 13, 2009, Pages 2385-2389

  Riveros, Toni Ann ^a   Porcasi, Lyra ^b   Muliadi, Sarah ^b   Hanrahan, Grady ^b   Gomez, Frank A ^a  

^a CALIFORNIA STATE UNIVERSITY   (United States)

^b CALIFORNIA LUTHERAN UNIVERSITY   (United States)

Author keywords

Artificial neural networks; CE; Electrophoretically mediated microanalysis; Experimental design

Indexed keywords

AMIDES; DESIGN OF EXPERIMENTS; FORECASTING; GLUCOSE; NUCLEOTIDES; STATISTICS;

CE; ELECTROPHORETICALLY MEDIATED MICROANALYSIS; FACTORIAL EXPERIMENTAL DESIGN; FULL FACTORIAL; GLUCOSE 6 PHOSPHATES; GLUCOSE-6-PHOSPHATE DEHYDROGENASE; NICOTINAMIDE ADENINE DINUCLEOTIDES; OPTIMISATIONS; PRODUCT DISTRIBUTIONS; REACTION CONDITIONS;

NEURAL NETWORKS;

GLUCOSE 6 PHOSPHATE; GLUCOSE 6 PHOSPHATE DEHYDROGENASE; NICOTINAMIDE ADENINE DINUCLEOTIDE; PHOSPHOGLUCONATE DEHYDROGENASE;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CAPILLARY ELECTROPHORESIS; CHEMICAL REACTION; COMPUTER PREDICTION; ELECTRIC POTENTIAL; ELECTROPHORETICALLY MEDIATED MICROANALYSIS; ENZYME ANALYSIS; FACTORIAL ANALYSIS; INFORMATION PROCESSING; PROCESS OPTIMIZATION; SEPARATION TECHNIQUE;

ANALYSIS OF VARIANCE; BUFFERS; ELECTROPHORESIS, CAPILLARY; GLUCOSEPHOSPHATE DEHYDROGENASE; HEXANONES; HYDROGEN-ION CONCENTRATION; LINEAR MODELS; MICROCHEMISTRY; MODELS, CHEMICAL; NAD; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS;

EID: 70450216014     PISSN: 01730835     EISSN: 15222683     Source Type: Journal    
DOI: 10.1002/elps.200800703     Document Type: Article

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