ArticleFEBS letters2013
A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes.
Article in FEBS letters, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed.
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- Robust Rapid Cellular Metabolite Sensing Using Benchtop NMR and SABRE-Hyperpolarized [1-Analytical chemistry · 2026Article
- Virtual Cell and Metabolic Control Analysis: Control Coefficients for Glycolytic Flux Are Highly Dependent on the Subsystem Selected for Analysis.Life (Basel, Switzerland) · 2026Article
- Parameterization of cell-free systems with time-series data using KETCHUP.PLoS computational biology · 2025Article
- Cell-Free Systems Biology: Characterizing Central Metabolism ofACS synthetic biology · 2024Article
- GraphKM: machine and deep learning for KBMC bioinformatics · 2024Article
- Data integration strategies for whole-cell modeling.FEMS yeast research · 2024Review
- Enzyme catalytic efficiency prediction: employing convolutional neural networks and XGBoost.Frontiers in artificial intelligence · 2024Article
- Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning.Nature communications · 2023Article
- Using Kinetic Modelling to Infer Adaptations inMetabolites · 2023Article
- Identification and biochemical characterization of a novel N-acetylglucosamine kinase in Saccharomyces cerevisiae.Scientific reports · 2022Article
- pH dependencies of glycolytic enzymes of yeast under in vivo-like assay conditions.The FEBS journal · 2022Article
- Limited Mechanistic Link Between the Monod Equation and Methanogen Growth: a Perspective from Metabolic Modeling.Microbiology spectrum · 2022Article
- Systems-based approaches to study immunometabolism.Cellular & molecular immunology · 2022Review
- From Petri Plates to Petri Nets, a revolution in yeast biology.FEMS yeast research · 2022Article
- Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism.iScience · 2022Article
- Agent-based models for detecting the driving forces of biomolecular interactions.Scientific reports · 2022Article
- Kinetic Modeling ofMetabolites · 2022Review
- Intelligent host engineering for metabolic flux optimisation in biotechnology.The Biochemical journal · 2021Review
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Authors and funding
25 authors.
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Abstract
We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a "cycle of knowledge" strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought.
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