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• W1998604610 abstract "Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths." @default.
• W1998604610 created "2016-06-24" @default.
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• W1998604610 date "2013-01-01" @default.
• W1998604610 modified "2023-09-23" @default.
• W1998604610 title "Bayesian parameter estimation for stochastic models of biological cell migration" @default.
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• W1998604610 doi "https://doi.org/10.1063/1.4819978" @default.
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