ArticleBiophysical journal2004
Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies.
Article in Biophysical journal, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.
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Who cites it
73 citing papers in PubMed.
- Article
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana.The New phytologist · 2025Article
- Genome scale metabolic network modelling for metabolic profile predictions.PLoS computational biology · 2024Article
- LooplessFluxSampler: an efficient toolbox for sampling the loopless flux solution space of metabolic models.BMC bioinformatics · 2024Article
- Trade-offs predicted by metabolic network structure give rise to evolutionary specialization and phenotypic diversification.Molecular biology and evolution · 2022Article
- Structural Thermokinetic Modelling.Metabolites · 2022Article
- Inspecting the Solution Space of Genome-Scale Metabolic Models.Metabolites · 2022Article
- Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.Cancers · 2021Review
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- Integrated genetic and metabolic landscapes predict vulnerabilities of temozolomide resistant glioblastoma cells.NPJ systems biology and applications · 2021Article
- Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021Review
- Kinetic modeling of H2O2 dynamics in the mitochondria of HeLa cells.PLoS computational biology · 2020Article
- Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens.Frontiers in cell and developmental biology · 2020Review
- Acetate Metabolism and the Inhibition of Bacterial Growth by Acetate.Journal of bacteriology · 2019Article
- Flux sampling is a powerful tool to study metabolism under changing environmental conditions.NPJ systems biology and applications · 2019Article
- Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotrophPeerJ · 2019Article
- Human Systems Biology and Metabolic Modelling: A Review-From Disease Metabolism to Precision Medicine.BioMed research international · 2019Review
- Mathematical modelling of microbes: metabolism, gene expression and growth.Journal of the Royal Society, Interface · 2017Review
- SteadyCom: Predicting microbial abundances while ensuring community stability.PLoS computational biology · 2017Article
13 more citing papers are in PubMed but not listed here.
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Reconstruction of genome-scale metabolic networks is now possible using multiple different data types. Constraint-based modeling is an approach to interrogate capabilities of reconstructed networks by constraining possible cellular behavior through the imposition of physicochemical laws. As a result, a steady-state flux space is defined that contains all possible functional states of the network. Uniform random sampling of the steady-state flux space allows for the unbiased appraisal of its contents. Monte Carlo sampling of the steady-state flux space of the reconstructed human red blood cell metabolic network under simulated physiologic conditions yielded the following key results: 1), probability distributions for the values of individual metabolic fluxes showed a wide variety of shapes that could not have been inferred without computation; 2), pairwise correlation coefficients were calculated between all fluxes, determining the level of independence between the measurement of any two fluxes, and identifying highly correlated reaction sets; and 3), the network-wide effects of the change in one (or a few) variables (i.e., a simulated enzymopathy or fixing a flux range based on measurements) were computed. Mathematical models provide the most compact and informative representation of a hypothesis of how a cell works. Thus, understanding model predictions clearly is vital to driving forward the iterative model-building procedure that is at the heart of systems biology. Taken together, the Monte Carlo sampling procedure provides a broadening of the constraint-based approach by allowing for the unbiased and detailed assessment of the impact of the applied physicochemical constraints on a reconstructed network.
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