Statistical approach for parameter identification by Turing patterns

DOI10.1016/j.jtbi.2020.110319zbMath1455.92014OpenAlexW3024888318WikidataQ94950705 ScholiaQ94950705MaRDI QIDQ827856

Heikki Haario, Alexey Kazarnikov

Publication date: 13 January 2021

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://lutpub.lut.fi/handle/10024/161231

zbMATH Keywords

pattern formationparameter identificationreaction-diffusion systemsMCMCmodel identificationgeneralized correlation integral

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Developmental biology, pattern formation (92C15)

Related Items (7)

Bespoke Turing systems ⋮ A Bayesian Approach to Modeling Biological Pattern Formation with Limited Data ⋮ Learning system parameters from Turing patterns ⋮ A time independent least squares algorithm for parameter identification of Turing patterns in reaction-diffusion systems ⋮ Parameter estimation for network-organized Turing system based on convolution neural networks ⋮ Data based quantification of synchronization ⋮ Two different approaches for parameter identification in a spatial-temporal rumor propagation model based on Turing patterns

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