ArticleBioinformatics (Oxford, England)2019
Parameter balancing: consistent parameter sets for kinetic metabolic models.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.bioRxiv : the preprint server for biology · 2026Article
- A multiscale, Bayesian inference approach to augment mechanistic models of cell signaling with machine-learning predictions of binding affinity.PLoS computational biology · 2026Article
- A compact model of Escherichia coli core and biosynthetic metabolism.PLoS computational biology · 2025Article
- Structural Thermokinetic Modelling.Metabolites · 2022Article
- Article
- eQuilibrator 3.0: a database solution for thermodynamic constant estimation.Nucleic acids research · 2022Article
- Model Balancing: A Search for In-Vivo Kinetic Constants and Consistent Metabolic States.Metabolites · 2021Article
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Authors and funding
2 authors.
Funding
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Abstract
summaryMeasured kinetic constants are key input data for metabolic models, but they are often uncertain, inconsistent and incomplete. Parameter balancing translates such data into complete and consistent parameter sets while accounting for predefined ranges and physical constraints. Based on Bayesian regression, it determines a most plausible parameter set as well as uncertainty ranges for all model parameters. Our tools for parameter balancing support standard model and data formats and enable an easy customization of prior distributions and constraints for biochemical constants. Modellers can balance kinetic constants, thermodynamic data and metabolomic data to obtain thermodynamically consistent metabolic states that comply with user-defined flux directions. AVAILABILITY AND IMPLEMENTATION: An online tool for parameter balancing, a stand-alone Python command line tool, a Python package and a Matlab toolbox (which uses the CPLEX solver) are freely available at www.parameterbalancing.net.
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