The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.
By Jeremy S. Edwards, Bernhard O. Palsson. Proceedings of the National Academy of Sciences of the United States of America, 2000
971 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/3e8d08919bc0dbed07ad38683f56d71b9d5f749f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Bernhard O. Palsson
- Costas D. Maranas
- Jennie L. Reed
- Prit Pharkya
- Jason A. Papin
- Nathan D. Price
- V. Schachter
- Pierre-Yves Bourguignon
In Genetics
- Bernhard O. Palsson
- C. Schilling
- Jennie L. Reed
- Hidde de Jong
- Thomas F. Hansen
- Adam M. Feist
- James M. Cheverud
- Costas D. Maranas
In Molecular Biology
- Bernhard O. Palsson
- V. Schachter
- Pierre-Yves Bourguignon
- Maxime Durot
- Jennie L. Reed
- Costas D. Maranas
- Adam M. Feist
- Nathan D. Price
Citations in the corpus
- Graph theory and networks in Biology. (2006, background): “The results of this paper indicate that, for all 43 networks studied, the distributions of in-degree, Pin(k), and out-degree, Pout(k), have tails of the form (3), with 2 γ 3.”
- A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 (2011, background): “coli was iJE660 (Edwards and Palsson, 2000).”
- Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli (2013, methodology): “The cumulative and new number of studies published per year separated according to ( A ) the metabolic reconstruction used (Edwards and Palsson, 2000; Reed et al , 2003; Feist et al , 2007; Orth et al , 2011 Engineering strategies found using model-driven analysis can often be nonintuitive and…”
- Cleaning up with genomics: applying molecular biology to bioremediation (2003, background): “This systems approach to microbial physiology has the ability to predict the metabolic response of organisms to various environmental conditions without the need for information on kinetic parameters for each of the individual reactions that are involved in the pathwa”
- Use of network analysis of metabolic systems in bioengineering (2002, methodology): “In this case, the remaining fluxes may be calculated by invoking an optimality principle such as maximization of ATP production [8, 10, 38, 40].”
- Genome-scale models of bacterial metabolism: reconstruction and applications (2008, positive): “…the unknown proton translocation stoichiometry of such a reaction in Methano-sarcina barkeri by determining for each media the model maintenance parameters that provided the best growth yield This model is an update of two earlier models for E. coli (Edwards & Palsson, 2000; Reed et al ., 2003).”
- Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth (2002, background): “In particular, constraints-based in silico model”
- Regulation of gene expression in flux balance models of metabolism. (2001, methodology): “An in silico model of E. coli, for example, accounts for 660 metabolic genes thought to be in the genome (Edwards & Palsson , 2000).”
- Modeling and Simulation of Genetic Regulatory Systems: A Literature Review (2002, positive): “…2001), the simulation of the development of the Drosophila embryo in the framework of the Virtual Drosophila project (Kitano et al ., 1997), and the analysis of metabolic networks in E. coli and H. in(cid:143)uenzae (Edwards and Palsson, 2000; Schilling et al ., 2000; Schilling and Palsson, 2000).”
- Metabolomics – the link between genotypes and phenotypes (2004, background): “In two excellent break-through papers by Edwards and co-workers (Edwards and Palsson, 2000; Edwards et al., 2001) it was shown that predictions based purely on stoichiometry metabolic matrices could be demonstrated by growth rate data from Escherichia coli mutants.”
- Thirteen Years of Building Constraint-Based In Silico Models of Escherichia coli (2003, methodology): “In this analysis, 68 of 79 (86%) of the in silico predictions were consistent with the experimental observations ( 16 ).”