ArticleIn silico biology2019
Calibration, Selection and Identifiability Analysis of a Mathematical Model of the in vitro Erythropoiesis in Normal and Perturbed Contexts.
Article in In silico biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- In silico modeling of anterior foregut endoderm differentiation towards lung epithelial progenitors.NPJ systems biology and applications · 2026Article
- In silico modeling of directed differentiation of induced pluripotent stem cells to definitive endoderm.PLoS computational biology · 2025Article
- In silico model development and optimization of in vitro lung cell population growth.PloS one · 2024Article
- Practical identifiability in the frame of nonlinear mixed effects models: the example of the in vitro erythropoiesis.BMC bioinformatics · 2021Article
- Drugs modulating stochastic gene expression affect the erythroid differentiation process.PloS one · 2019Article
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Authors and funding
4 authors.
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Abstract
The in vivo erythropoiesis, which is the generation of mature red blood cells in the bone marrow of whole organisms, has been described by a variety of mathematical models in the past decades. However, the in vitro erythropoiesis, which produces red blood cells in cultures, has received much less attention from the modelling community. In this paper, we propose the first mathematical model of in vitro erythropoiesis. We start by formulating different models and select the best one at fitting experimental data of in vitro erythropoietic differentiation obtained from chicken erythroid progenitor cells. It is based on a set of linear ODE, describing 3 hypothetical populations of cells at different stages of differentiation. We then compute confidence intervals for all of its parameters estimates, and conclude that our model is fully identifiable. Finally, we use this model to compute the effect of a chemical drug called Rapamycin, which affects all states of differentiation in the culture, and relate these effects to specific parameter variations. We provide the first model for the kinetics of in vitro cellular differentiation which is proven to be identifiable. It will serve as a basis for a model which will better account for the variability which is inherent to the experimental protocol used for the model calibration.
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