Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters
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Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolismQuantification and Classification of E. coli Proteome Utilization and Unused Protein Costs across Environments.Thermal adaptation of decomposer communities in warming soils.Maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms.Phenomenological model for predicting the catabolic potential of an arbitrary nutrientUse of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal mediumPredicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli.Predicting internal cell fluxes at sub-optimal growthPerception and regulatory principles of microbial growth controlTransition of an Anaerobic Escherichia coli Culture to Aerobiosis: Balancing mRNA and Protein Levels in a Demand-Directed Dynamic Flux Balance Analysis.Stoichiometric Representation of Gene-Protein-Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype PredictionGenome-scale models of metabolism and gene expression extend and refine growth phenotype prediction.Systematic applications of metabolomics in metabolic engineering.Constructing kinetic models of metabolism at genome-scales: A review.Thermodynamic Constraints Improve Metabolic Networks.Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints.Metabolic Trade-offs in Yeast are Caused by F1F0-ATP synthaseGenome-scale metabolic models applied to human health and disease.Experimental validation of in silico estimated biomass yields of Pseudomonas putida KT2440.Robust Analysis of Fluxes in Genome-Scale Metabolic PathwaysProteome reallocation in Escherichia coli with increasing specific growth rate.An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli.Macromolecular crowding explains overflow metabolism in cells.Near-zero growth kinetics of Pseudomonas putida deduced from proteomic analysis.Metabolic shift of Escherichia coli under salt stress in the presence of glycine betaine.Optimization-driven identification of genetic perturbations accelerates the convergence of model parameters in ensemble modeling of metabolic networks.Mathematical modelling of microbes: metabolism, gene expression and growth.Metabolic network architecture and carbon source determine metabolite production costs.A physical model of cell metabolism.
P2860
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P2860
Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters
description
2012 nî lūn-bûn
@nan
2012 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Prediction of microbial growth ...... etwork with kinetic parameters
@ast
Prediction of microbial growth ...... etwork with kinetic parameters
@en
Prediction of microbial growth ...... etwork with kinetic parameters
@nl
type
label
Prediction of microbial growth ...... etwork with kinetic parameters
@ast
Prediction of microbial growth ...... etwork with kinetic parameters
@en
Prediction of microbial growth ...... etwork with kinetic parameters
@nl
prefLabel
Prediction of microbial growth ...... etwork with kinetic parameters
@ast
Prediction of microbial growth ...... etwork with kinetic parameters
@en
Prediction of microbial growth ...... etwork with kinetic parameters
@nl
P2860
P50
P1476
Prediction of microbial growth ...... etwork with kinetic parameters
@en
P2093
Tomer Shlomi
P2860
P304
P356
10.1371/JOURNAL.PCBI.1002575
P577
2012-07-05T00:00:00Z