Spectrophotometric resolution of ternary mixtures of tryptophan, tyrosine, and histidine with the aid of principal component-artificial neural network models

Analytical Biochemistry

Volumn 370, Issue 1, 2007, Pages 68-76

  Hasani, Masoumeh ^a   Moloudi, Mahsa ^a   Emami, Fereshteh ^a  

^a BU ALI SINA UNIVERSITY   (Iran)

Author keywords

Artificial neural network; Histidine; Multivariate calibration; Principal component analysis; Simultaneous determination; Ternary mixtures; Tryptophan; Tyrosine

Indexed keywords

AMINO ACIDS; BACKPROPAGATION; DATA FLOW ANALYSIS; IRON COMPOUNDS; MIXTURES; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; REACTION RATES; SPECTROPHOTOMETERS; SPECTROPHOTOMETRY;

HISTIDINE; MULTIVARIATE CALIBRATION; SIMULTANEOUS DETERMINATIONS; TERNARY MIXTURES; TRYPTOPHAN; TYROSINE;

MULTILAYER NEURAL NETWORKS;

HISTIDINE; POTASSIUM FERRICYANIDE; TRYPTOPHAN; TYROSINE; WATER;

ALKALINITY; AMINO ACID ANALYSIS; ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALIBRATION; DATA ANALYSIS; KINETICS; LEARNING; OXIDATION; PERFORMANCE; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PRINCIPAL COMPONENT ARTIFICIAL NEURAL NETWORK; PRIORITY JOURNAL; REACTION ANALYSIS; SPECTROPHOTOMETER; SPECTROPHOTOMETRY;

EID: 34548652560     PISSN: 00032697     EISSN: 10960309     Source Type: Journal    
DOI: 10.1016/j.ab.2007.06.025     Document Type: Article

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