Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods-Reference-Cited by-同舟云学术

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Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods

Published:2016-10-26 Issue:11 Volume:16 Page:1483
ISSN:1424-8220
Container-title:Sensors
language:en
Short-container-title:Sensors

Author:

Gonzalez-Navarro Felix,Stilianova-Stoytcheva Margarita,Renteria-Gutierrez Livier,Belanche-Muñoz Lluís,Flores-Rios Brenda,Ibarra-Esquer Jorge

Funder

Consejo Nacional de Ciencia y Tecnología

Universidad Autónoma de Baja California

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Link

http://www.mdpi.com/1424-8220/16/11/1483/pdf

Reference25 articles.

1. Electrochemical biosensors: recommended definitions and classification1International Union of Pure and Applied Chemistry: Physical Chemistry Division, Commission I.7 (Biophysical Chemistry); Analytical Chemistry Division, Commission V.5 (Electroanalytical Chemistry).1

2. Amperometric Biosensors;Borgmann,2011

3. Kinetic behavior of enzymes immobilized in artificial membranes

4. Model for the amperometric enzyme electrode obtained through digital simulation and applied to the immobilized glucose oxidase system

5. Rotating ring-disk enzyme electrode for surface catalysis studies

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