On structural and practical identifiability

We discuss issues of structural and practical identifiability of partially observed differential equations, which are often applied in systems biology. The development of mathematical methods to investigate structural nonidentifiability has a long tradition. Computationally efficient methods to dete...

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Bibliographic Details
Published in:Current opinion in systems biology 2021-03, Vol.25, p.60-69
Main Authors: Wieland, Franz-Georg, Hauber, Adrian L., Rosenblatt, Marcus, Tönsing, Christian, Timmer, Jens
Format: Article
Language:English
Subjects:
Experimental design
Fisher information matrix
Identifiability
Model reduction
Nonlinear dynamics
Observability
ODE models
Practical identifiability
Profile likelihood
Structural identifiability
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Summary:We discuss issues of structural and practical identifiability of partially observed differential equations, which are often applied in systems biology. The development of mathematical methods to investigate structural nonidentifiability has a long tradition. Computationally efficient methods to detect and cure it have been developed recently. Practical nonidentifiability, on the other hand, has not been investigated at the same conceptually clear level. We argue that practical identifiability is more challenging than structural identifiability when it comes to modeling experimental data. We discuss that the classical approach based on the Fisher information matrix has severe shortcomings. As an alternative, we propose using the profile likelihood, which is a powerful approach to detect and resolve practical nonidentifiability. [Display omitted] •With recent advances, identifying structural identifiability is no longer a major issue.•Practical identifiability is still challenging.•Fisher information matrix is misleading.•Profile likelihood can solve practical identifiability challenge.
ISSN:2452-3100
2452-3100
DOI:10.1016/j.coisb.2021.03.005