Bayesian parameter identification for Turing systems on stationary and evolving domains
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Publication:670616
DOI10.1007/s11538-018-0518-zzbMath1409.92006OpenAlexW2895346454WikidataQ57475013 ScholiaQ57475013MaRDI QIDQ670616
Chandrasekhar Venkataraman, Eduard Campillo-Funollet, Anotida Madzvamuse
Publication date: 18 March 2019
Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11538-018-0518-z
inverse problemsMarkov chain Monte Carlopattern formationparameter identificationreaction-diffusionTuring instabilityBayesian inverse problems
Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Reaction-diffusion equations (35K57)
Related Items (10)
Statistical approach for parameter identification by Turing patterns ⋮ A mathematical analysis of an activator-inhibitor Rho GTPase model ⋮ Bespoke Turing systems ⋮ Classification of parameter spaces for a reaction-diffusion model on stationary domains ⋮ A Bayesian Approach to Modeling Biological Pattern Formation with Limited Data ⋮ Learning system parameters from Turing patterns ⋮ Parameter estimation for network-organized Turing system based on convolution neural networks ⋮ A moving grid finite element method applied to a mechanobiochemical model for 3D cell migration ⋮ Stability Analysis and Parameter Classification of a Reaction-Diffusion Model on an Annulus ⋮ Parameter identification via optimal control for a Cahn-Hilliard-chemotaxis system with a variable mobility
Uses Software
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