A Pseudo Data Generation Method and a Two-Stage Quantitation Method for Simultaneous Determination Sensor of Nucleotide Derivatives
Author(s) -
Akito Fukuda,
Sayaka Kondo,
Kenichi Maruyama,
Koji Suzuki,
Masafumi Hagiwara
Publication year - 2007
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2007.p0751
Subject(s) - computer science , nucleotide , biological system , stage (stratigraphy) , chemistry , gene , biology , biochemistry , paleontology
In this paper, we propose a pseudo data generation method and a two-stage quantitation method for simultaneous determination of nucleotide derivatives sensor that determines concentration of nucleotide derivatives based on sensor response. Conventional sensors are difficult to determine concentration of nucleotide derivatives simultaneously because they have similar structures and they influence each other, so the precision is low. In order to archive high precision and simultaneous determination sensor, this paper proposes a pseudo data generation method and a two-stage quantitation method. To analyze sensor response, we use GRNN (General Regression Neural Network). With this sensor, concentration of nucleotide derivatives is determined simultaneously, easily and fast. It was confirmed by the experiments that proposed methods are effective for determining concentration of nucleotide derivatives.
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