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- W2890123531 endingPage "144" @default.
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- W2890123531 abstract "Plant metabolism is characterized by a wide diversity of metabolites, with systems far more complicated than those of microorganisms. Mathematical modeling is useful for understanding dynamic behaviors of plant metabolic systems for metabolic engineering. Time-series metabolome data has great potential for estimating kinetic model parameters to construct a genome-wide metabolic network model. However, data obtained by current metabolomics techniques does not meet the requirement for constructing accurate models. In this article, we highlight novel strategies and algorithms to handle the underlying difficulties and construct dynamic in vivo models for large-scale plant metabolic systems. The coarse but efficient modeling enables the prediction of unknown mechanisms regulating plant metabolism." @default.
- W2890123531 created "2018-09-27" @default.
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- W2890123531 date "2018-12-01" @default.
- W2890123531 modified "2023-09-27" @default.
- W2890123531 title "Using metabolome data for mathematical modeling of plant metabolic systems" @default.
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- W2890123531 doi "https://doi.org/10.1016/j.copbio.2018.08.005" @default.
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