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Bulletin of Mathematical Biology|May 27, 2024
Making Predictions Using Poorly Identified Mathematical ModelsMatthew J Simpson, Oliver J MaclarenPlos Computational Biology|September 29, 2023
Profile-Wise Analysis: A profile likelihood-based workflow for identifiability analysis, estimation, and prediction with mechanistic mathematical modelsMatthew J Simpson, Oliver J MaclarenJournal of Theoretical Biology|January 13, 2024
Modelling count data with partial differential equation models in biologyMatthew J Simpson, Ryan J Murphy, Oliver J MaclarenJournal of the Royal Society, Interface|March 4, 2020
Practical parameter identifiability for spatio-temporal models of cell invasionMatthew J Simpson, Ruth E Baker, Sean T Vittadello, et al.Journal of Theoretical Biology|June 25, 2022
Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic modelsMatthew J Simpson, Ruth E Baker, Pascal R Buenzli, et al.Journal of Theoretical Biology|January 1, 2022
Parameter identifiability and model selection for sigmoid population growth modelsMatthew J Simpson, Alexander P Browning, David J Warne, et al.Proceedings. Mathematical, Physical, and Engineering Sciences|July 12, 2021
Profile likelihood analysis for a stochastic model of diffusion in heterogeneous mediaMatthew J Simpson, Alexander P Browning, Christopher Drovandi, et al.Mathematical Biosciences|December 4, 2022
Profile likelihood-based parameter and predictive interval analysis guides model choice for ecological population dynamicsMatthew J Simpson, Shannon A Walker, Emma N Studerus, et al.Journal of Theoretical Biology|August 6, 2021
Model-based data analysis of tissue growth in thin 3D printed scaffoldsAlexander P Browning, Oliver J Maclaren, Pascal R Buenzli, et al.Journal of the Royal Society, Interface|December 7, 2022
Computationally efficient framework for diagnosing, understanding and predicting biphasic population growthRyan J Murphy, Oliver J Maclaren, Alivia R Calabrese, et al.Pageof 19