Artificial neural networks for quantification in unresolved
capillary electrophoresis peaks

J 2002

Artificial neural networks for quantification in unresolved capillary electrophoresis peaks

BOCAZ-BENEVENTI, Gaston, Rosa LATORRE, Marta FARKOVÁ a Josef HAVEL

Základní údaje

Originální název

Artificial neural networks for quantification in unresolved capillary electrophoresis peaks

Autoři

BOCAZ-BENEVENTI, Gaston (152 Chile), Rosa LATORRE (724 Španělsko), Marta FARKOVÁ (203 Česká republika) a Josef HAVEL (203 Česká republika, garant)

Vydání

Analytica Chimica Acta, Amsterdam, Elsevier Science Publishers, 2002, 0003-2670

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10406 Analytical chemistry

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 2.114

Kód RIV

RIV/00216224:14310/02:00005586

Organizační jednotka

Přírodovědecká fakulta

UT WoS

000173613100006

Klíčová slova anglicky

capillary zone electrophoresis; unresolved peaks; experimental design; normalization; artificial neural networks; quantitation

Štítky

artificial neural networks, Capillary Zone Electrophoresis, experimental design, Normalization, quantitation, unresolved peaks

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 25. 2. 2013 12:31, RNDr. Marta Farková, CSc.

Anotace

V originále

The application of the combination of experimental design (ED) and artificial neural networks (ANNs) for the quantification of overlapped peaks in capillary zone electrophoresis is described. When the total separation cannot be achieved by separation techniques, the use of ED-ANN can be a suitable approach. The unstability of EOF causes peak shift that has to be corrected in order to apply ED-ANN methods. In this work, normalization procedure of electropherograms with consequent application of ANNs for quantification purpose was developed. Both, spectra and electropherograms can be used as multivariate data. In general, both kinds of data were found to be suitable for unresolved peaks quantification by ED-ANN approach.

Návaznosti

MSM 143100011, záměr

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

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Struktura a vazebné poměry, vlastnosti a analýza syntetických a přírodních molekulových ansamblů

Citovat

BOCAZ-BENEVENTI, Gaston, Rosa LATORRE, Marta FARKOVÁ a Josef HAVEL. Artificial neural networks for quantification in unresolved capillary electrophoresis peaks. Analytica Chimica Acta. Amsterdam: Elsevier Science Publishers, 2002, roč. 452, č. 1, s. 47-63. ISSN 0003-2670.

@article{400391,
   author = {BocazandBeneventi, Gaston and Latorre, Rosa and Farková, Marta and Havel, Josef},
   article_location = {Amsterdam},
   article_number = {1},
   keywords = {capillary zone electrophoresis; unresolved peaks; experimental design; normalization; artificial neural networks; quantitation},
   language = {eng},
   issn = {0003-2670},
   journal = {Analytica Chimica Acta},
   title = {Artificial neural networks for quantification in unresolved capillary electrophoresis peaks},
   volume = {452},
   year = {2002}
}

TY  - JOUR
ID  - 400391
AU  - Bocaz-Beneventi, Gaston - Latorre, Rosa - Farková, Marta - Havel, Josef
PY  - 2002
TI  - Artificial neural networks for quantification in unresolved capillary electrophoresis peaks
JF  - Analytica Chimica Acta
VL  - 452
IS  - 1
SP  - 47
EP  - 47
PB  - Elsevier Science Publishers
SN  - 00032670
KW  - capillary zone electrophoresis
KW  - unresolved peaks
KW  - experimental design
KW  - normalization
KW  - artificial neural networks
KW  - quantitation
N2  - The application of the combination of experimental design (ED) and artificial neural networks (ANNs) for the quantification of overlapped peaks in capillary zone electrophoresis is described. When the total separation cannot be achieved by separation techniques, the use of ED-ANN can be a suitable approach. The unstability of EOF causes peak shift that has to be corrected in order to apply ED-ANN methods. In this work, normalization procedure of electropherograms with consequent application of ANNs for quantification purpose was developed. Both, spectra and electropherograms can be used as multivariate data. In general, both kinds of data were found to be suitable for unresolved peaks quantification by ED-ANN approach.
ER  -

BOCAZ-BENEVENTI, Gaston, Rosa LATORRE, Marta FARKOVÁ a Josef HAVEL. Artificial neural networks for quantification in unresolved capillary electrophoresis peaks. \textit{Analytica Chimica Acta}. Amsterdam: Elsevier Science Publishers, 2002, roč.~452, č.~1, s.~47-63. ISSN~0003-2670.

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