Discrete-time Neural Network Identification of Quorum Sensing Escherichia coli Regulators


Por: Torres-Cerna C.E., Morales J.A., Alanis A.Y., Hernandez-Vargas E.A.

Publicada: 1 ene 2018
Categoría: Control and systems engineering

Resumen:
Quorum Sensing (QS) is a complex process of cell to cell communication that allows bacteria to share information and regulate gene expression. This bacterial process is difficult to model because of their complexity, nonlinearity, and stochastic nature. While nonlinear systems can be derived using mathematical modeling, neural networks are an excellent tool to infer their dynamics. In this paper, we present a Recurrent High Order Neural Network (RHONN) to identify the communication system used by Escherichia coli (E. coli) to regulate its genetic expression. Simulation results show the applicability of the identifier. © 2018

Filiaciones:
Torres-Cerna C.E.:
 Universidad de Guadalajara, Apartado postal 51-71, Col. Las Aguilas, Zapopan, Jalisco 45080, Mexico

Morales J.A.:
 Universidad de Guadalajara, Apartado postal 51-71, Col. Las Aguilas, Zapopan, Jalisco 45080, Mexico

Alanis A.Y.:
 Universidad de Guadalajara, Apartado postal 51-71, Col. Las Aguilas, Zapopan, Jalisco 45080, Mexico

Hernandez-Vargas E.A.:
 Frankfurt Institute for Advanced Studies, Ruth-Moufang-Str. 1, Frankfurt am Main, 60438, Germany
ISSN: 24058963
Editorial
Elsevier, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS, Países Bajos
Tipo de documento: Conference Paper
Volumen: 51 Número: 13
Páginas: 120-124
WOS Id: 000443321500020
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