On testing structural identifiability by a simple scaling method: Relying on scaling symmetries can be misleading

A recent paper published in PLOS Computational Biology [1] introduces the Scaling Invariance Method (SIM) for analysing structural local identifiability and observability. These two properties define mathematically the possibility of determining the values of the parameters (identifiability) and sta...

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Bibliographic Details
Main Authors: Massonis, G. (Author), Villaverde, A.F (Author)
Format: Article
Language:English
Published: Public Library of Science 2021
Subjects:
Online Access:View Fulltext in Publisher
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245 1 0 |a On testing structural identifiability by a simple scaling method: Relying on scaling symmetries can be misleading 
260 0 |b Public Library of Science  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1371/journal.pcbi.1009032 
520 3 |a A recent paper published in PLOS Computational Biology [1] introduces the Scaling Invariance Method (SIM) for analysing structural local identifiability and observability. These two properties define mathematically the possibility of determining the values of the parameters (identifiability) and states (observability) of a dynamic model by observing its output. In this note we warn that SIM considers scaling symmetries as the only possible cause of non-identifiability and non-observability. We show that other types of symmetries can cause the same problems without being detected by SIM, and that in those cases the method may lead one to conclude that the model is identifiable and observable when it is actually not. Copyright: © 2021 Villaverde, Massonis. 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. 
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650 0 4 |a biology 
650 0 4 |a Computational Biology 
650 0 4 |a Models, Theoretical 
650 0 4 |a procedures 
650 0 4 |a theoretical model 
700 1 |a Massonis, G.  |e author 
700 1 |a Villaverde, A.F.  |e author 
773 |t PLoS Computational Biology