Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures

Varování

Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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CUKROWSKA Ewa TRNKOVÁ Libuše KIZEK René HAVEL Josef

Rok publikování 2001
Druh Článek v odborném periodiku
Časopis / Zdroj JOURNAL OF ELECTROANALYTICAL CHEMISTRY
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
Obor Elektrochemie
Klíčová slova artificial neural networks; experimental design; differential pulse polarography; linear sweep voltammetry; adenine and
Popis 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.
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