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Main Title: Diffusivity estimation for activator–inhibitor models: Theory and application to intracellular dynamics of the actin cytoskeleton
Author(s): Pasemann, Gregor
Flemming, Sven
Alonso, Sergio
Beta, Carsten
Stannat, Wilhelm
Type: Article
Language Code: en
Abstract: A theory for diffusivity estimation for spatially extended activator–inhibitor dynamics modeling the evolution of intracellular signaling networks is developed in the mathematical framework of stochastic reaction–diffusion systems. In order to account for model uncertainties, we extend the results for parameter estimation for semilinear stochastic partial differential equations, as developed in Pasemann and Stannat (Electron J Stat 14(1):547–579, 2020), to the problem of joint estimation of diffusivity and parametrized reaction terms. Our theoretical findings are applied to the estimation of effective diffusivity of signaling components contributing to intracellular dynamics of the actin cytoskeleton in the model organism Dictyostelium discoideum.
Issue Date: 3-May-2021
Date Available: 31-May-2021
DDC Class: 510 Mathematik
Subject(s): parametric drift estimation
stochastic reaction–diffusion systems
maximum likelihood estimation
actin cytoskeleton dynamics
Sponsor/Funder: DFG, 318763901, SFB 1294: Datenassimilation: Die nahtlose Verschmelzung von Daten und Modellen
TU Berlin, Open-Access-Mittel – 2021
Journal Title: Journal of Nonlinear Science
Publisher: Springer Nature
Publisher Place: Heidelberg
Volume: 31
Article Number: 59
Publisher DOI: 10.1007/s00332-021-09714-4
EISSN: 1432-1467
ISSN: 0938-8974
Appears in Collections:FG Mathematische Stochastik / Stochastische Prozesse in den Neurowissenschaften » Publications

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