Inferring gene regulatory networks from temporal expression profiles under time-delay and noise

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Ordinary differential equations (ODE) have been widely used for modeling and analysis of dynamic gene networks in systems biology. In this paper, we propose an optimization method that can infer a gene regulatory network from time-series gene expression data. Specifically, the following four cases are considered: (1) reconstruction of a gene network from synthetic gene expression data with noise, (2) reconstruction of a Dene network from synthetic gene expression data with time-delay, (3) reconstruction of a gene network from synthetic gene expression data with noise and time-delay, and (4) reconstruction of a gene network from experimental time-series data in budding yeast cell cycle. (c) 2007 Elsevier Ltd. All rights reserved.
Publisher
ELSEVIER SCI LTD
Issue Date
2007-08
Language
English
Article Type
Article
Keywords

EXPONENTIAL STABILITY; NEURAL-NETWORKS; PERTURBATIONS; YEAST

Citation

COMPUTATIONAL BIOLOGY AND CHEMISTRY, v.31, pp.239 - 245

ISSN
1476-9271
DOI
10.1016/j.compbiolchem.2007.03.013
URI
http://hdl.handle.net/10203/88751
Appears in Collection
BiS-Journal Papers(저널논문)
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