BOCAZ-BENEVENTI, Gaston, Rosa LATORRE, Marta FARKOVÁ and Josef HAVEL. Artificial neural networks for quantification in unresolved capillary electrophoresis peaks. Analytica Chimica Acta. Amsterdam: Elsevier Science Publishers, 2002, vol. 452, No 1, p. 47-63. ISSN 0003-2670.
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Basic information
Original name Artificial neural networks for quantification in unresolved capillary electrophoresis peaks
Authors BOCAZ-BENEVENTI, Gaston (152 Chile), Rosa LATORRE (724 Spain), Marta FARKOVÁ (203 Czech Republic) and Josef HAVEL (203 Czech Republic, guarantor).
Edition Analytica Chimica Acta, Amsterdam, Elsevier Science Publishers, 2002, 0003-2670.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10406 Analytical chemistry
Country of publisher Netherlands
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 2.114
RIV identification code RIV/00216224:14310/02:00005586
Organization unit Faculty of Science
UT WoS 000173613100006
Keywords in English capillary zone electrophoresis; unresolved peaks; experimental design; normalization; artificial neural networks; quantitation
Tags artificial neural networks, Capillary Zone Electrophoresis, experimental design, Normalization, quantitation, unresolved peaks
Tags International impact, Reviewed
Changed by Changed by: RNDr. Marta Farková, CSc., učo 546. Changed: 25/2/2013 12:31.
Abstract
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.
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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
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