Practical identifiability in the frame of nonlinear mixed effects models: the example of the in vitro erythropoiesis.

Autor: Duchesne R; Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, Université de Lyon, ENS de Lyon, Université Claude Bernard Lyon 1, 46 allée d'Italie, 69007, Lyon, France. ronan.duchesne@ens-lyon.fr.; Inria Team Dracula, Inria Center Grenoble Rhône-Alpes, Lyon, France. ronan.duchesne@ens-lyon.fr., Guillemin A; Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, Université de Lyon, ENS de Lyon, Université Claude Bernard Lyon 1, 46 allée d'Italie, 69007, Lyon, France., Gandrillon O; Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, Université de Lyon, ENS de Lyon, Université Claude Bernard Lyon 1, 46 allée d'Italie, 69007, Lyon, France.; Inria Team Dracula, Inria Center Grenoble Rhône-Alpes, Lyon, France., Crauste F; CNRS, MAP5 UMR 8145, Université de Paris, Paris, France.
Jazyk: angličtina
Zdroj: BMC bioinformatics [BMC Bioinformatics] 2021 Oct 04; Vol. 22 (1), pp. 478. Date of Electronic Publication: 2021 Oct 04.
DOI: 10.1186/s12859-021-04373-4
Abstrakt: Background: Nonlinear mixed effects models provide a way to mathematically describe experimental data involving a lot of inter-individual heterogeneity. In order to assess their practical identifiability and estimate confidence intervals for their parameters, most mixed effects modelling programs use the Fisher Information Matrix. However, in complex nonlinear models, this approach can mask practical unidentifiabilities.
Results: Herein we rather propose a multistart approach, and use it to simplify our model by reducing the number of its parameters, in order to make it identifiable. Our model describes several cell populations involved in the in vitro differentiation of chicken erythroid progenitors grown in the same environment. Inter-individual variability observed in cell population counts is explained by variations of the differentiation and proliferation rates between replicates of the experiment. Alternatively, we test a model with varying initial condition.
Conclusions: We conclude by relating experimental variability to precise and identifiable variations between the replicates of the experiment of some model parameters.
(© 2021. The Author(s).)
Databáze: MEDLINE
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