Benchmarking tools for a priori identifiability analysis

Motivation The theoretical possibility of determining the state and parameters of a dynamic model by measuring its outputs is given by its structural identifiability and its observability. These properties should be analysed before attempting to calibrate a model, but their a priori analysis can be challenging, requiring symbolic calculations that often have a high computational cost. In recent years, a number of software tools have been developed for this task, mostly in the systems biology community. These tools have vastly different features and capabilities, and a critical assessment of their performance is still lacking.Results Here, we present a comprehensive study of the computational resources available for analysing structural identifiability. We consider 13 software tools developed in 7 programming languages and evaluate their performance using a set of 25 case studies created from 21 models. Our results reveal their strengths and weaknesses, provide guidelines for choosing the most appropriate tool for a given problem and highlight opportunities for future developments.Availability and implementation.

Automated summary

In this study, we conducted a comprehensive investigation on the available computational resources for analyzing structural identifiability. We evaluated the performance of 13 different software tools developed in 7 programming languages. Our results provide insights into the strengths and weaknesses of these tools, and offer guidance for selecting the most appropriate tool for specific problems. We also identify opportunities for future developments in this field.