ArticleScientific reports2015
A Branching Process to Characterize the Dynamics of Stem Cell Differentiation.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior.Briefings in bioinformatics · 2025Review
- FGF2 modulates simultaneously the mode, the rate of division and the growth fraction in cultures of radial glia.Development (Cambridge, England) · 2020Article
- A multiscale mathematical model of cell dynamics during neurogenesis in the mouse cerebral cortex.BMC bioinformatics · 2019Article
- Timing the spinal cord development with neural progenitor cells losing their proliferative capacity: a theoretical analysis.Neural development · 2019Article
- The age-regulated zinc finger factor ZNF367 is a new modulator of neuroblast proliferation during embryonic neurogenesis.Scientific reports · 2018Article
- Neurogenic decisions require a cell cycle independent function of the CDC25B phosphatase.eLife · 2018Article
- Feedback between tissue packing and neurogenesis in the zebrafish neural tube.Development (Cambridge, England) · 2018Article
- High content imaging quantification of multiple in vitro human neurogenesis events after neurotoxin exposure.BMC pharmacology & toxicology · 2016Article
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Authors and funding
1 author.
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Abstract
The understanding of the regulatory processes that orchestrate stem cell maintenance is a cornerstone in developmental biology. Here, we present a mathematical model based on a branching process formalism that predicts average rates of proliferative and differentiative divisions in a given stem cell population. In the context of vertebrate neurogenesis, the model predicts complex non-monotonic variations in the rates of pp, pd and dd modes of division as well as in cell cycle length, in agreement with experimental results. Moreover, the model shows that the differentiation probability follows a binomial distribution, allowing us to develop equations to predict the rates of each mode of division. A phenomenological simulation of the developing spinal cord informed with the average cell cycle length and division rates predicted by the mathematical model reproduces the correct dynamics of proliferation and differentiation in terms of average numbers of progenitors and differentiated cells. Overall, the present mathematical framework represents a powerful tool to unveil the changes in the rate and mode of division of a given stem cell pool by simply quantifying numbers of cells at different times.
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