Approximate Bayesian computation reveals the importance of repeated measurements for parameterising cell-based models of growing tissues

DOI10.1016/J.JTBI.2018.01.020zbMath1397.92165OpenAlexW2950220557WikidataQ47553045 ScholiaQ47553045MaRDI QIDQ1649432

Jochen Kursawe, Ruth E. Baker, Alexander G. Fletcher

Publication date: 6 July 2018

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

Full work available at URL: http://eprints.whiterose.ac.uk/127202/8/vertex-model-inference.pdf

zbMATH Keywords

vertex modelsapproximate Bayesian computationparameter inference\textit{Drosophila} wing imaginal disccell-based models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Developmental biology, pattern formation (92C15) Cell biology (92C37) Computational methods for problems pertaining to biology (92-08)

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Cites Work

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• Bayesian inference of force dynamics during morphogenesis
• Incorporating chemical signalling factors into cell-based models of growing epithelial tissues
• Choice of summary statistic weights in approximate Bayesian computation
• Adapting the ABC distance function
• Relating cell shape and mechanical stress in a spatially disordered epithelium using a vertex-based model
• Sequential Monte Carlo without likelihoods

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