ArticlePloS one2013
Systematic construction of kinetic models from genome-scale metabolic networks.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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Who cites it
48 citing papers in PubMed, 115 citations in OpenAlex.
- Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.bioRxiv : the preprint server for biology · 2026Article
- Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations.Nature communications · 2023Article
- Multi-scale models of whole cells: progress and challenges.Frontiers in cell and developmental biology · 2023Review
- A kinetic framework for modeling oleochemical biosynthesis in Escherichia coli.Biotechnology and bioengineering · 2022Article
- Structural Thermokinetic Modelling.Metabolites · 2022Article
- Diverse classes of constraints enable broader applicability of a linear programming-based dynamic metabolic modeling framework.Scientific reports · 2022Article
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- Can Systems Biology Advance Clinical Precision Oncology?Cancers · 2021Review
- Model Balancing: A Search for In-Vivo Kinetic Constants and Consistent Metabolic States.Metabolites · 2021Article
- Modular assembly of dynamic models in systems biology.PLoS computational biology · 2021Article
- Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment.Cancers · 2021Review
- A structural property for reduction of biochemical networks.Scientific reports · 2021Article
- Modular dynamic biomolecular modelling with bond graphs: the unification of stoichiometry, thermodynamics, kinetics and data.Journal of the Royal Society, Interface · 2021Article
- The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.Nucleic acids research · 2021Article
- MASSpy: Building, simulating, and visualizing dynamic biological models in Python using mass action kinetics.PLoS computational biology · 2021Article
- Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN.Nature communications · 2020Article
- Parameter balancing: consistent parameter sets for kinetic metabolic models.Bioinformatics (Oxford, England) · 2019Article
- Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties.PLoS computational biology · 2019Article
- MCS2: minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks.Bioinformatics (Oxford, England) · 2019Article
- Scalable nonlinear programming framework for parameter estimation in dynamic biological system models.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.