Summary:
In their Commentary paper, Villaverde and Massonis (On testing structural identifiability by a simple scaling method: relying on scaling symmetries can be misleading) have commented on our paper in which we proposed a simple scaling method to test structural identifiability. Our scaling invariance method (SIM) tests for scaling symmetries only, and Villaverde and Massonis correctly show the SIM may fail to detect identifiability problems when a model has other types of symmetries. We agree with the limitations raised by these authors but, also, we emphasize that the method is still valuable for its applicability to a wide variety of models, its simplicity, and even as a tool to introduce the problem of identifiability to investigators with little training in mathematics.
Spanish layman's summary:
Cuando un modelo no es identificable, no se puede ajustar unívocamente, con independencia de la calidad de los datos. Aunque existen métodos de identificación precisos, no están al alcance de científicos aplicados, por lo que nuestro método permite una primera aproximación al alcance de todos.
English layman's summary:
When a model is not identifiable, it cannot be uniquely fit, regardless of data quality. Although there are very precise identification methods, they are too sophisticated for applied scientists, so our method allows a first approximation within everyone's reach.
Keywords: identifiability, biomathematics, models, biophysics
JCR Impact Factor and WoS quartile: 4,779 - Q1 (2021); 3,800 - Q1 (2023)
DOI reference:
https://doi.org/10.1371/journal.pcbi.1009425
Published on paper: October 2021.
Published on-line: October 2021.
Citation:
M. Castro, R. J. de Boer, The limitations, dangers, and benefits of simple methods for testing identifiability. Plos Computational Biology. Vol. 17, nº. 10, pp. e1009425-1 - e1009425-2, October 2021. [Online: October 2021]
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