A Pseudo Data Generation Method and a Two-Stage Quantitation Method for Simultaneous Determination Sensor of Nucleotide Derivatives
Akito Fukuda*, Sayaka Kondo**, Kenichi Maruyama**,
Koji Suzuki**, and Masafumi Hagiwara*
*Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
**Department of Applied Chemistry, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan
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.
Koji Suzuki, and Masafumi Hagiwara, “A Pseudo Data Generation Method and a Two-Stage Quantitation Method for Simultaneous Determination Sensor of Nucleotide Derivatives,” J. Adv. Comput. Intell. Intell. Inform., Vol.11, No.7, pp. 751-758, 2007.
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