ArticleScience advances2026
COBRA-k: A powerful framework bridging constraint-based and kinetic metabolic modeling.
Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- WILDkCAT: extract, retrieve, and predict enzyme turnover numbers of constraint-based metabolic models.Bioinformatics (Oxford, England) · 2026Article
- Article
- Enzyme kinetics shapes the growth response of metabolic networks.PLoS computational biology · 2026Article
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2 authors.
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Abstract
Mathematical modeling is key to understanding cellular metabolism. Two common approaches are kinetic modeling and constraint-based reconstruction and analysis (COBRA). COBRA models analyze steady-state fluxes using linear constraints but lack kinetic detail. Kinetic models offer mechanistic descriptions via differential equations but require (often unknown) kinetic parameters and enzyme concentrations. To bridge this gap, we introduce COBRA-k, a framework integrating nonlinear kinetic rate laws into COBRA models to consistently constrain metabolic fluxes, enzyme abundances, and metabolite concentrations. COBRA-k enables flexible exploration of metabolic steady states with optimization techniques, even with incomplete parametrization. COBRA-k models require solving computationally demanding mixed-integer nonlinear programs. We therefore developed a dedicated iterative algorithm, implemented in an open-source Python package. We applied COBRA-k to a large-scale
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