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Constraint-based models predict metabolic and associated cellular functions

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NATURE REVIEWS GENETICS
卷 15, 期 2, 页码 107-120

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NATURE PUBLISHING GROUP
DOI: 10.1038/nrg3643

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  1. US National Institutes of Health [GM068837, GM057089]
  2. Novo Nordisk Foundation
  3. US National Science Foundation Graduate Research Fellowship [DGE-1144086]

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The prediction of cellular function from a genotype is a fundamental goal in biology. For metabolism, constraint-based modelling methods systematize biochemical, genetic and genomic knowledge into a mathematical framework that enables a mechanistic description of metabolic physiology. The use of constraint-based approaches has evolved over similar to 30 years, and an increasing number of studies have recently combined models with high-throughput data sets for prospective experimentation. These studies have led to validation of increasingly important and relevant biological predictions. As reviewed here, these recent successes have tangible implications in the fields of microbial evolution, interaction networks, genetic engineering and drug discovery.

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