More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability
@article{Ilmer2022MoreEI, title={More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability}, author={Ilia Ilmer and Alexey Ovchinnikov and Gleb Pogudin and Pedro Soto}, journal={ArXiv}, year={2022}, volume={abs/2204.01623} }
Structural global parameter identifiability indicates whether one can determine a parameter’s value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer…
References
SHOWING 1-10 OF 34 REFERENCES
Obtaining weights for Gröbner basis computation in parameter identifiability problems
- Mathematics, Computer ScienceArXiv
- 2022
We consider a specific class of polynomial systems that arise in parameter identifiability problems of models of ordinary differential equations (ODE) and discover a method for speeding up the…
Web-based Structural Identifiability Analyzer
- Computer Science, MathematicsCMSB
- 2021
This work presents a web-based software tool that can determine identifiability of individual parameters of the model and also provide all functions of parameters that are identifiable (also called identifiable combinations) from single or multiple experiments.
Computing all identifiable functions of parameters for ODE models
- Computer Science, MathematicsSyst. Control. Lett.
- 2021
Differential elimination for dynamical models via projections with applications to structural identifiability
- Computer Science, Mathematics
- 2021
An algorithm is proposed that computes a description of the set of differential-algebraic relations between the input and output variables of a dynamical system model and allows the identification of models that could not be tackled before.
Global Identifiability of Differential Models
- Computer Science, MathematicsCommunications on Pure and Applied Mathematics
- 2020
First, an algebraic criterion for global identifiability is rigorously derived, which yields a deterministic algorithm, which improves the efficiency by randomizing the algorithm while guaranteeing the probability of correctness.
DAISY: An efficient tool to test global identifiability. Some case studies
- Mathematics2008 16th Mediterranean Conference on Control and Automation
- 2008
The DAISY software checking the a priori global identifiability of two well-known nonlinear physiological models from the literature are demonstrated: a glucose minimal model which has been widely used in clinical studies to estimate the insulin sensitivity from an oral glucose tolerance test and a four-state HIV/AIDS model.
Multi-experiment parameter identifiability of ODEs and model theory
- Mathematics, Computer ScienceSIAM J. Appl. Algebra Geom.
- 2022
An algorithm to determine the exact number of experiments for multi-experiment local identifiability and obtain an upper bound that is off at most by one for the number of ExperimentsBound, a Monte Carlo randomized version of the algorithm with a polynomial arithmetic complexity.
A New Version of DAISY to Test Structural Identifiability of Biological Models
- MathematicsCMSB
- 2019
A novel extension of the software tool DAISY (Differential Algebra for Identifiability of SYstems) is presented, which performs structural identifiability analysis for linear and nonlinear dynamic models described by polynomial or rational ODE’s.
On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation
- MathematicsPloS one
- 2014
Novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS are developed and implemented.
SIAN: software for structural identifiability analysis of ODE models
- MathematicsBioinform.
- 2019
A new software SIAN (Structural Identifiability ANalyser) that can tackle problems that could not be tackled by previously developed packages is presented.