Using artificial neural networks for elaboration of fluorescence biosensors on the basis of nanoparticles
Аннотация
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).
Ключевые слова
Об авторах
S. Burikov
Moscow M. V. Lomonosov State University
Россия
Россия
S. Dolenko
D. V. Skobeltsyn Institute of Nuclear Physics, Moscow State University
Россия
Россия
K. Laptinskiy
Moscow M. V. Lomonosov State University
Россия
Россия
I. Plastinin
Moscow M. V. Lomonosov State University
Россия
Россия
A. Vervald
Moscow M. V. Lomonosov State University
Россия
Россия
I. Vlasov
General Physics Institute RAS
Россия
Россия
T. Dolenko
Moscow M. V. Lomonosov State University
Россия
Россия
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Рецензия
Для цитирования:
, , , , , , . Наносистемы: физика, химия, математика. 2014;5(1):195-202.
For citation:
Burikov S.A., Dolenko S.A., Laptinskiy K.A., Plastinin I.V., Vervald A.M., Vlasov I.I., Dolenko T.A. Using artificial neural networks for elaboration of fluorescence biosensors on the basis of nanoparticles. Nanosystems: Physics, Chemistry, Mathematics. 2014;5(1):195-202.
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