Artificial Neural Networks for Quantitative Analysis of Ade-Cyt Mixtures by UV-Vis Spectrophotometry

CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK and Josef HAVEL. Artificial Neural Networks for Quantitative Analysis of Ade-Cyt Mixtures by UV-Vis Spectrophotometry. In Chemometrics V. I. Brno, Czech Republic: Masaryk University, Brno, 1999, p. 6. Brno Section of the Chemical Society.

Basic information

Original name

Artificial Neural Networks for Quantitative Analysis of Ade-Cyt Mixtures by UV-Vis Spectrophotometry

Authors

CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK and Josef HAVEL

Edition

I. Brno, Czech Republic, Chemometrics V, p. 6-6, Brno Section of the Chemical Society, 1999

Publisher

Masaryk University, Brno

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10406 Analytical chemistry

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

RIV identification code

RIV/00216224:14310/99:00003220

Organization unit

Faculty of Science

Keywords in English

Absorption Spectra of Purine and Pyrimidine Derivatives; Adenine; Cytosine; Artificial Neural Networks; Experimental Design

Tags

adenine, artificial neural networks, cytosine, experimental design

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Abstract

V originále

This work presents the application of experimental desing and artificial neural networks for quantifying purine and pyrimidine in mixtures studied by UV-Vis spectrophotometry. Multivariate calibration based on a suitable experimental design (ED) and soft modelling with artificial neural networks (ANNs) is used for quantitative analysis of highly overlapped absorbance spectra of adenine and cytosine.

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Links

GV204/97/K084, research and development project

Name: Elektrody modifikované nukleovými kyselinami a bílkovinami. Nové nástroje v biochemickém a biomedicínském výzkumu Investor: Czech Science Foundation, Electrodes modified with nucleic acids and proteins. New tools in biochemical and biomedical research