Function approximation approach to the inference of reduced NGnet models of genetic networks |
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Authors: | Shuhei Kimura Katsuki Sonoda Soichiro Yamane Hideki Maeda Koki Matsumura Mariko Hatakeyama |
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Institution: | (1) Faculty of Engineering, Tottori University, 4-101 Koyama-Minami, Tottori, Japan;(2) JFE R&D Corporation, 1-1 Minami-Watarida, Kawasaki, Japan;(3) JFE Engineering Corporation, 2-1 Suehiro, Tsurumi, Yokohama, Japan;(4) RIKEN Genomic Sciences Center, 1-7-22 Suehiro, Tsurumi, Yokohama, Japan |
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Abstract: | Background The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of
gene expression patterns. While a number of models have been proposed to describe genetic regulatory networks, this study
focuses on a set of differential equations since it has the ability to model dynamic behavior of gene expression. When we
use a set of differential equations to describe genetic networks, the inference problem can be defined as a function approximation
problem. On the basis of this problem definition, we propose in this study a new method to infer reduced NGnet models of genetic
networks. |
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Keywords: | |
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