ArticleScientific reports2016
Construction of feasible and accurate kinetic models of metabolism: A Bayesian approach.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Combining automated kinetic model selection with robust optimization and application to maximize cell-free production of UDP-GalNAc.Metabolic engineering communications · 2026Article
- Enzyme kinetics shapes the growth response of metabolic networks.PLoS computational biology · 2026Article
- Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.bioRxiv : the preprint server for biology · 2026Article
- Unique kinetic behavior of a secondary alcohol dehydrogenase: from a reaction engineering point of view.Bioprocess and biosystems engineering · 2026Article
- Kinetic sampling shows the effect of medium composition on metabolic control in Saccharomyces cerevisiae.Microbial cell factories · 2026Article
- Parameterization of cell-free systems with time-series data using KETCHUP.PLoS computational biology · 2025Article
- Complex Kinetic Models Predict β-Carotene Production and Reveal Flux Limitations in RecombinantACS synthetic biology · 2025Article
- The Dawn of High-Throughput and Genome-Scale Kinetic Modeling: Recent Advances and Future Directions.ACS synthetic biology · 2025Review
- BayesianSSA: a Bayesian statistical model based on structural sensitivity analysis for predicting responses to enzyme perturbations in metabolic networks.BMC bioinformatics · 2024Article
- Bottom-up parameterization of enzyme rate constants: Reconciling inconsistent data.Metabolic engineering communications · 2024Article
- Bayesian Regression Facilitates Quantitative Modeling of Cell Metabolism.ACS synthetic biology · 2024Review
- From observational to actionable: rethinking omics in biologics production.Trends in biotechnology · 2023Review
- From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry.FEMS microbiology reviews · 2023Review
- Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Symbolic kinetic models in python (SKiMpy): intuitive modeling of large-scale biological kinetic models.Bioinformatics (Oxford, England) · 2023Article
- Quantitative modeling of pentose phosphate pathway response to oxidative stress reveals a cooperative regulatory strategy.iScience · 2022Article
- The topology of genome-scale metabolic reconstructions unravels independent modules and high network flexibility.PLoS computational biology · 2022Article
- Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.Biomolecules · 2022Review
- Quantitative metabolic fluxes regulated by trans-omic networks.The Biochemical journal · 2022Review
- Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism.iScience · 2022Article
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Authors and funding
2 authors.
Funding
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Abstract
Kinetic models are essential to quantitatively understand and predict the behaviour of metabolic networks. Detailed and thermodynamically feasible kinetic models of metabolism are inherently difficult to formulate and fit. They have a large number of heterogeneous parameters, are non-linear and have complex interactions. Many powerful fitting strategies are ruled out by the intractability of the likelihood function. Here, we have developed a computational framework capable of fitting feasible and accurate kinetic models using Approximate Bayesian Computation. This framework readily supports advanced modelling features such as model selection and model-based experimental design. We illustrate this approach on the tightly-regulated mammalian methionine cycle. Sampling from the posterior distribution, the proposed framework generated thermodynamically feasible parameter samples that converged on the true values, and displayed remarkable prediction accuracy in several validation tests. Furthermore, a posteriori analysis of the parameter distributions enabled appraisal of the systems properties of the network (e.g., control structure) and key metabolic regulations. Finally, the framework was used to predict missing allosteric interactions.
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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.