Extends structural identifiability analysis to functional components of differential equation models and characterizes conditions for unique recovery using differential algebra techniques.
Determination of parameter identifiability in nonlinear biophysical models: A Bayesian approach
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
Proposes adaptive multiple importance sampling for robust Bayesian model evidence estimation under parameter non-identifiability, shown to outperform deterministic methods on ecological case studies while being cheaper than MCMC.
Trajectory data resolves structural non-identifiability in lattice random walk diffusion models that count data alone cannot, with analysis of experimental design impacts on practical identifiability.
A tutorial on using StructuralIdentifiability.jl to assess local and global identifiability in ODE models with examples from epidemiology, pharmacokinetics, and systems biology.
citing papers explorer
-
Reliable model selection in the presence of parameter non-identifiability
Proposes adaptive multiple importance sampling for robust Bayesian model evidence estimation under parameter non-identifiability, shown to outperform deterministic methods on ecological case studies while being cheaper than MCMC.
-
A Tutorial on Symbolic Structural Identifiability Analysis of ODE Models in Julia
A tutorial on using StructuralIdentifiability.jl to assess local and global identifiability in ODE models with examples from epidemiology, pharmacokinetics, and systems biology.