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

J 2001

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

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

Basic information

Original name

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

Authors

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

Edition

JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Lausanne, ELSEVIER SCIENCE SA, LAUSANNE, 2001, 0022-0728

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10405 Electrochemistry

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Impact factor

Impact factor: 1.960

RIV identification code

RIV/00216224:14310/01:00004519

Organization unit

Faculty of Science

Keywords in English

artificial neural networks; experimental design; differential pulse polarography; linear sweep voltammetry; adenine and

Abstract

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.

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

MSM 143100011, plan (intention)

Name: Struktura a vazebné poměry, vlastnosti a analýza syntetických a přírodních molekulových ansamblů

Investor: Ministry of Education, Youth and Sports of the CR, Structure and character of bonding, properties and analysis of synthetic and natural molecular ensembles

Citovat

CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK and Josef HAVEL. Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures. JOURNAL OF ELECTROANALYTICAL CHEMISTRY. Lausanne: ELSEVIER SCIENCE SA, LAUSANNE, 2001, vol. 2001, No 503, p. 117-124. ISSN 0022-0728.

@article{371372,
   author = {Cukrowska, Ewa and Trnková, Libuše and Kizek, René and Havel, Josef},
   article_location = {Lausanne},
   article_number = {503},
   keywords = {artificial neural networks; experimental design; differential pulse polarography; linear sweep voltammetry; adenine and},
   language = {eng},
   issn = {0022-0728},
   journal = {JOURNAL OF ELECTROANALYTICAL CHEMISTRY},
   title = {Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures},
   volume = {2001},
   year = {2001}
}

TY  - JOUR
ID  - 371372
AU  - Cukrowska, Ewa - Trnková, Libuše - Kizek, René - Havel, Josef
PY  - 2001
TI  - Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures
JF  - JOURNAL OF ELECTROANALYTICAL CHEMISTRY
VL  - 2001
IS  - 503
SP  - 117
EP  - 117
PB  - ELSEVIER SCIENCE SA, LAUSANNE
SN  - 00220728
KW  - artificial neural networks
KW  - experimental design
KW  - differential pulse polarography
KW  - linear sweep voltammetry
KW  - adenine and
N2  - 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.
ER  -

CUKROWSKA, Ewa, Libuše TRNKOVÁ, René KIZEK and Josef HAVEL. Use of artificial neural networks for the evaluation of electrochemical signals of adenine and cytosine in mixtures. \textit{JOURNAL OF ELECTROANALYTICAL CHEMISTRY}. Lausanne: ELSEVIER SCIENCE SA, LAUSANNE, 2001, vol.~2001, No~503, p.~117-124. ISSN~0022-0728.

Detailed Information on Publication Record