Using artificial neural networks for elaboration of fluorescence biosensors on the basis of nanoparticles
Nanosistemy: fizika, himiâ, matematika, Tome 5 (2014) no. 1, pp. 195-202.

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In this study, the results for the solution of the pattern recognition problem are presented – extraction of fluorescence contribution for carbon dots used as biomarkers from the background signals of natural fluorophores and the determination of relative nanoparticle concentration. To solve this problem, artificial neural networks were used. The principal opportunity for solution of the given problem was demonstrated. The used architectures for neural networks allow the detection of carbon dot-based fluorescence within the background of native fluorescent egg protein with sufficiently high accuracy (not lower than 0.002 mg/ml).
Keywords: carbon dots, biomarkers, egg protein, autofluorescence, artificial neural networks.
Mots-clés : fluorescence
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     author = {S. A. Burikov and S. A. Dolenko and K. A. Laptinskiy and I. V. Plastinin and A. M. Vervald and I. I. Vlasov and T. A. Dolenko},
     title = {Using artificial neural networks for elaboration of fluorescence biosensors on the basis of nanoparticles},
     journal = {Nanosistemy: fizika, himi\^a, matematika},
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     url = {http://geodesic.mathdoc.fr/item/NANO_2014_5_1_a28/}
}
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S. A. Burikov; S. A. Dolenko; K. A. Laptinskiy; I. V. Plastinin; A. M. Vervald; I. I. Vlasov; T. A. Dolenko. Using artificial neural networks for elaboration of fluorescence biosensors on the basis of nanoparticles. Nanosistemy: fizika, himiâ, matematika, Tome 5 (2014) no. 1, pp. 195-202. http://geodesic.mathdoc.fr/item/NANO_2014_5_1_a28/