2001
Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures
CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK a Josef HAVELZákladní údaje
Originální název
Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures
Autoři
CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK a Josef HAVEL
Vydání
JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Lausanne, ELSEVIER SCIENCE SA, LAUSANNE, 2001, 0022-0728
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10405 Electrochemistry
Stát vydavatele
Česká republika
Utajení
není předmětem státního či obchodního tajemství
Impakt faktor
Impact factor: 1.960
Kód RIV
RIV/00216224:14310/01:00004519
Organizační jednotka
Přírodovědecká fakulta
Klíčová slova anglicky
artificial neural networks; experimental design; differential pulse polarography; linear sweep voltammetry; adenine and
Štítky
Změněno: 28. 1. 2002 08:52, prof. RNDr. Libuše Trnková, CSc.
Anotace
V originále
A new method for the simultaneous determination of adenine and cytosine is described. Multivariate calibration based on a suitable experimental design (ED) and soft modeling with artificial neural networks (ANNs) is used for quantitative analysis of overlapped linear scan voltammetric (LSV) and differential pulse polarographic (DPP) peaks of adenine and cytosine that occur in the region of hydrogen evolution. It is demonstrated that analysis of mixtures, even if some of the constituents undergo an irreversible reduction, can be quantified with reasonable accuracy. The average absolute error was estimated as 3.7% in LSV, 4.6%, in DPP for adenine and 5.2% in LSV, 5.9% in DPP for cytosine. For the whole testing set the comparison of the added and found values of adenine and cytosine concentrations was characterized by an agreement factor (about 0.06). The method is quite general and can be used for analysis of other biologically important substances without their separation.
Návaznosti
GV204/97/K084, projekt VaV |
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MSM 143100011, záměr |
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