ArticleJournal of the Royal Society, Interface2024
Parameter identifiability and model selection for partial differential equation models of cell invasion.
Article in Journal of the Royal Society, Interface, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- From prior knowledge to data-informed models: a review of Boolean network inference.Briefings in bioinformatics · 2026Review
- Identifiability, Sensitivity, and Genetic Algorithms in Bacterial Biofilm Selection Models.Bulletin of mathematical biology · 2026Article
- Modelling the impact of temperature and bird migration on the spread of West Nile virus.One health (Amsterdam, Netherlands) · 2026Article
- Decoding cellular population dynamics through mechanistic modelling and statistical data analysis.NPJ systems biology and applications · 2026Review
- Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning for biological systems.PLoS computational biology · 2026Article
- A Practical Identifiability Criterion Leveraging Weak-Form Parameter Estimation.Bulletin of mathematical biology · 2026Article
- Article
- Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling.Bulletin of mathematical biology · 2025Article
- Actin network heterogeneity tunes activator-inhibitor dynamics at the cell cortex.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Structural and practical identifiability of within-host models of virus dynamics - a review.Current opinion in systems biology · 2025Article
- Inference and prediction for stochastic models of biological populations undergoing migration and proliferation.Journal of the Royal Society, Interface · 2025Review
- Article
- Phenotype structuring in collective cell migration: a tutorial of mathematical models and methods.Journal of mathematical biology · 2025Review
- Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Quantifying cell cycle regulation by tissue crowding.Biophysical journal · 2025Article
- Practical parameter identifiability and handling of censored data with Bayesian inference in mathematical tumour models.NPJ systems biology and applications · 2024Article
- Structural and practical identifiability of contrast transport models for DCE-MRI.PLoS computational biology · 2024Article
- Parameter identifiability and model selection for partial differential equation models of cell invasion.Journal of the Royal Society, Interface · 2024Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
When employing mechanistic models to study biological phenomena, practical parameter identifiability is important for making accurate predictions across wide ranges of unseen scenarios, as well as for understanding the underlying mechanisms. In this work, we use a profile-likelihood approach to investigate parameter identifiability for four extensions of the Fisher-Kolmogorov-Petrovsky-Piskunov (Fisher-KPP) model, given experimental data from a cell invasion assay. We show that more complicated models tend to be less identifiable, with parameter estimates being more sensitive to subtle differences in experimental procedures, and that they require more data to be practically identifiable. As a result, we suggest that parameter identifiability should be considered alongside goodness-of-fit and model complexity as criteria for model selection.
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