5 papers
Framing local structural identifiability and observability in terms of parameter-state symmetries
Johannes G. Borgqvist, Alexander P. Browning, Fredrik Ohlsson +1
We introduce a subclass of Lie symmetries, called parameter-state symmetries, to analyse the local structural identifiability and observability of mechanistic models consisting of…
A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models
Arianna Ceccarelli, Alexander P. Browning, Tai Chaiamarit +2
Advances in experimental techniques allow the collection of high-resolution spatio-temporal data that track individual motile entities. These tracking data can be used to calibrate…
Exact identifiability analysis for a class of partially observed near-linear stochastic differential equation models
Alexander P Browning, Michael J Chappell, Hamid Rahkooy +2
Stochasticity plays a key role in many biological systems, necessitating the calibration of stochastic mathematical models to interpret associated data. For model parameters to be…
Structural identifiability of linear-in-parameter parabolic PDEs through auxiliary elliptic operators
Yurij Salmaniw, Alexander P Browning
Parameter identifiability is often requisite to the effective application of mathematical models in the interpretation of biological data, however theory applicable to the study of…
Framing structural identifiability in terms of parameter symmetries
Johannes G Borgqvist, Alexander P Browning, Fredrik Ohlsson +1
A key step in mechanistic modelling of dynamical systems is to conduct a structural identifiability analysis. This entails deducing which parameter combinations can be estimated fr…