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Detalle de: Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

Title Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation
Abstract

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Apa Reference Villaverde, A. F., & Banga, J. R. (2017). Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation. PLOS Computational Biology, 13(11), e1005878. 10.1371/journal.pcbi.1005878
Doi 10.1371/journal.pcbi.1005878
Publication Date 29 Nov 2017
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Biosystems Modeling
Research Groups Computational Biology Lab at MBG
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