ArticleBulletin of mathematical biology2014
Mathematical model of stem cell differentiation and tissue regeneration with stochastic noise.
Article in Bulletin of mathematical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Close to Optimal Cell Sensing Ensures the Robustness of Tissue Differentiation Process: The Avian Photoreceptor Mosaic Case.Entropy (Basel, Switzerland) · 2021Article
- Large fluctuations in multi-scale modeling for rest hematopoiesis.Journal of mathematical biology · 2021Article
- A General Theoretical Framework to Study the Influence of Electrical Fields on Mesenchymal Stem Cells.Frontiers in bioengineering and biotechnology · 2020Article
- A computational model of feedback-mediated hematopoietic stem cell differentiation in vitro.PloS one · 2019Article
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1 author.
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Abstract
Differentiation and self-renewal of stem cells is an essential process for the maintenance of tissue composition. The promise of novel medical therapies combined with the complexity of this process encourage us to employ numerical and mathematical methods. This will allow us to understand better the mechanisms which regulate stem cell behaviour. Perturbations to the cellular environment may have an influence on the death rate, proliferation rate and on the fraction of self-renewal at every stage of differentiation. In this paper, we present mathematical study of the effect of stochastic noise on the process of tissue regeneration. Here, a system of Itô stochastic differential equations with linear diffusion coefficients that is based on a deterministic model of multistage cell lineages is investigated. Numerical simulations of the stochastic model are shown for a different number of stages of differentiation. Interactions between the noise, added to the different stages, are characterised using numerical simulations. The long-time behaviour of the two-dimensional version of the model is fully characterised; asymptotic stability of the related Markov semigroup is proved using the theory of the Markov semigroups and the method of the Khasminskií function.
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