ArticleSIAM review. Society for Industrial and Applied Mathematics2011
ON IDENTIFIABILITY OF NONLINEAR ODE MODELS AND APPLICATIONS IN VIRAL DYNAMICS.
Article in SIAM review. Society for Industrial and Applied Mathematics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 200 papers.
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Who cites it
200 citing papers in PubMed.
- Modelling HIV-1 2-LTR dynamics following raltegravir intensification.Journal of the Royal Society, Interface · 2013Trial
- Resurgence of large-scale influenza A (H1N1) outbreaks: Modeling the interplay of transmission, loss of immunity, and vaccination.Infectious Disease Modelling · 2027Article
- Parameter identifiability of a neuroendocrine-inflammatory model across experimental designs.ArXiv · 2026Article
- Quantifying target antigen-dependent CAR T-cell performance against AML.Cancer cell international · 2026Article
- A comparative study of simulation-based inference methods for epidemic models with identifiability considerations.PLoS computational biology · 2026Article
- Clinical trial simulation of antiviral drugs.Journal of virology · 2026Review
- A Multiscale Signaling-Biophysical Framework Reveals Mechanisms of Macrophage-Mediated RBC Clearance in Sickle Cell and Gaucher Disease.bioRxiv : the preprint server for biology · 2026Article
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- Leveraging mathematical models to predict and control T-cell activation.PLoS computational biology · 2026Article
- A Practical Identifiability Criterion Leveraging Weak-Form Parameter Estimation.Bulletin of mathematical biology · 2026Article
- Infectious disease modeling for public health practice: projections, scenarios, and uncertainty in three phases of outbreak response.American journal of epidemiology · 2026Article
- Hazard-based distributional regression via ordinary differential equations.Statistical methods in medical research · 2026Article
- Article
- A multi-source data-based modelling study on brucellosis transmission risk analysis and control strategies in Zhejiang Province, China.BMC infectious diseases · 2026Article
- On the structural and practical identifiability of multi-echo BBB-ASL tracer kinetic models.Magnetic resonance in medicine · 2026Article
- A Nonparametric Approach to Practical Identifiability of Nonlinear Mixed Effects Models.Bulletin of mathematical biology · 2026Article
- Review
- Inverse analysis of patient-specific parameters of a 3D-0D closed-loop cardiovascular model with an exemplary application to an adult tetralogy of Fallot case.Biomechanics and modeling in mechanobiology · 2025Article
- From Bird Viremia to Bird Surveillance: Identifiability in a Multiscale Vector-Borne Model of Usutu Virus Infection.bioRxiv : the preprint server for biology · 2025Article
- CrossLabFit: A novel framework for integrating qualitative and quantitative data across multiple labs for model calibration.PLoS computational biology · 2025Article
140 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
Ordinary differential equations (ODE) are a powerful tool for modeling dynamic processes with wide applications in a variety of scientific fields. Over the last 2 decades, ODEs have also emerged as a prevailing tool in various biomedical research fields, especially in infectious disease modeling. In practice, it is important and necessary to determine unknown parameters in ODE models based on experimental data. Identifiability analysis is the first step in determing unknown parameters in ODE models and such analysis techniques for nonlinear ODE models are still under development. In this article, we review identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiability analysis, practical identifiability analysis and sensitivity-based identifiability analysis. Some advanced topics and ongoing research are also briefly reviewed. Finally, some examples from modeling viral dynamics of HIV, influenza and hepatitis viruses are given to illustrate how to apply these identifiability analysis methods in practice.
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