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

AutorVillaverde, A. F. ; Banga, Julio R.
Fecha de publicación2017
EditorPublic Library of Science
CitaciónPLoS Computational Biology 13(11): e1005878 (2017)
ResumenThe 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
Descripción18 pages, 4 figures, 1 table.-- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Versión del editorhttps://doi.org/10.1371/journal. pcbi.1005878
DOI10.1371/journal. pcbi.1005878
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