ArticleScientific reports2016
Modelling chronotaxicity of cellular energy metabolism to facilitate the identification of altered metabolic states.
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 12 papers.
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12 citing papers in PubMed.
- Modelling brain metabolism with interacting nonautonomous phase oscillators.Frontiers in network physiology · 2026Article
- An order parameter for synchronisation of angular velocities.The European physical journal. Special topics · 2026Article
- Causal interaction of metabolic oscillations in monolayers of Hela cervical cancer cells: emergence of complex networks.Scientific reports · 2025Article
- Roles of calcium in ameloblasts during tooth development: A scoping review.Journal of Taibah University Medical Sciences · 2025Review
- Glycolytic oscillations under periodic drivings.Journal of the Royal Society, Interface · 2024Article
- Metabolic Oscillations and Glycolytic Phenotypes of Cancer Cells.International journal of molecular sciences · 2023Article
- Oscillations and Dynamic Symbiosis in Cellular Metabolism in Cancer.Frontiers in oncology · 2022Article
- Extracellular ionic fluxes suggest the basis for cellular life at the 1/f ridge of extended criticality.European biophysics journal : EBJ · 2020Article
- Modeling Cell Energy Metabolism as Weighted Networks of Non-autonomous Oscillators.Frontiers in physiology · 2020Article
- In-vivo correlations between skin metabolic oscillations and vasomotion in wild-type mice and in a model of oxidative stress.Scientific reports · 2019Article
- Biological Oscillators in Nanonetworks-Opportunities and Challenges.Sensors (Basel, Switzerland) · 2018Review
- Oscillatory signatures underlie growth regimes in Arabidopsis pollen tubes: computational methods to estimate tip location, periodicity, and synchronization in growing cells.Journal of experimental botany · 2017Article
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4 authors.
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Abstract
Altered cellular energy metabolism is a hallmark of many diseases, one notable example being cancer. Here, we focus on the identification of the transition from healthy to abnormal metabolic states. To do this, we study the dynamics of energy production in a cell. Due to the thermodynamic openness of a living cell, the inability to instantaneously match fluctuating supply and demand in energy metabolism results in nonautonomous time-varying oscillatory dynamics. However, such oscillatory dynamics is often neglected and treated as stochastic. Based on experimental evidence of metabolic oscillations, we show that changes in metabolic state can be described robustly by alterations in the chronotaxicity of the corresponding metabolic oscillations, i.e. the ability of an oscillator to resist external perturbations. We also present a method for the identification of chronotaxicity, applicable to general oscillatory signals and, importantly, apply this to real experimental data. Evidence of chronotaxicity was found in glycolytic oscillations in real yeast cells, verifying that chronotaxicity could be used to study transitions between metabolic states.
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