Studies from University of Paris Saclay Have Provided New Information about Data Acquisition (Asas-nanp Symposium: Mathematical Modeling In Animal Nutrition: the Power of Identifiability Analysis for Dynamic Modeling In Animal Science:a...).

A recent study from the University of Paris Saclay explores the use of identifiability analysis in the field of animal science. Identifiability analysis is a mathematical tool that helps determine if unique values of model parameters can be recovered from experimental data. The researchers propose adopting an upstream approach, integrating identifiability analysis before data collection, to improve the accuracy and robustness of predictive models. They emphasize the availability of freely accessible software tools that make identifiability analysis more accessible to practitioners in the field. The study concludes that the modeling community in animal science can easily incorporate identifiability analysis into their model development process. [Extracted from the article]