Genome-scale microbial in silico models: the constraints-based approach.

@article{Price2003GenomescaleMI,
  title={Genome-scale microbial in silico models: the constraints-based approach.},
  author={Nathan D. Price and Jason A. Papin and Christopher H. Schilling and Bernhard O. Palsson},
  journal={Trends in biotechnology},
  year={2003},
  volume={21 4},
  pages={
          162-9
        }
}

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References

SHOWING 1-10 OF 68 REFERENCES
Metabolic modeling of microbial strains in silico.
Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth
TLDR
When placed under growth selection pressure, the growth rate of E. coli on glycerol reproducibly evolved from a sub-optimal value to the optimal growth rate predicted from a whole-cell in silico model, opening the possibility of using adaptive evolution of entire metabolic networks to realize metabolic states that have been determined a priori based on insilico analysis.
Transcriptional Regulation in Constraints-based Metabolic Models of Escherichia coli * 210
TLDR
The combined metabolic/regulatory model can predict the ability of mutant E. coli strains to grow on defined media as well as time courses of cell growth, substrate uptake, metabolic by-product secretion, and qualitative gene expression under various conditions, as indicated by comparison with experimental data under a variety of environmental conditions.
In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data
TLDR
This study demonstrates how the combination of in silico and experimental biology can be used to obtain a quantitative genotype–phenotype relationship for metabolism in bacterial cells.
Genome-Scale Metabolic Model of Helicobacter pylori 26695
TLDR
The results presented herein suggest an effective strategy of combining in silico modeling with experimental technologies to enhance biological discovery for less characterized organisms and their genomes.
Toward Metabolic Phenomics: Analysis of Genomic Data Using Flux Balances
TLDR
How the metabolic characteristics of annotated small genomes can be analyzed using flux balance analysis (FBA) is illustrated to show how FBA can be used to study the capabilities of this strain.
Regulation of gene expression in flux balance models of metabolism.
TLDR
Genome-scale metabolic networks can now be reconstructed based on annotated genomic data augmented with biochemical and physiological information about the organism, and transcriptional regulatory events are incorporated within FBA to further constrain the space of possible network functions.
Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network.
TLDR
The reconstructed metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information and may be used as the basis for in silico analysis of phenotypic functions.
The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.
  • J. EdwardsB. Palsson
  • Biology, Engineering
    Proceedings of the National Academy of Sciences of the United States of America
  • 2000
TLDR
It was shown that based on stoichiometric and capacity constraints the in silico analysis was able to qualitatively predict the growth potential of mutant strains in 86% of the cases examined.
Sequence-based analysis of metabolic demands for protein synthesis in prokaryotes.
TLDR
The framework provided herein can subsequently be integrated with genome-scale metabolic models, providing a sequence-based accounting of the metabolic demands resulting from RNA and protein polymerization.
...
...