Critical Assessment of Parameter Estimation Methods in Models of Biological Oscillators⁎. Issue 19 (2018)

• Record Type: Journal Article
• Authors: Pitt, Jake Alan; Gomoescu, Lucian; Pantelides, Constantinos C.; Chachuat, Benoît; Banga, Julio R.
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 19(2018)
• Page Start: 72
• Page End: 75
• Publication Date: 2018
• Subjects: biological oscillators -- model calibration -- regularisation -- overfitting -- identifiability -- frequentist estimation -- Bayesian estimation -- set-membership estimation; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.09.040
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Many biological systems exhibit oscillations in relation to key physiological or cellular functions, such as circadian rhythms, mitosis and DNA synthesis. Mathematical modelling provides a powerful approach to analysing these biosystems. Applying parameter estimation methods to calibrate these models can prove a very challenging task in practice, due to the presence of local solutions, lack of identifiability, and risk of overfitting. This paper presents a comparison of three state-of-the-art methods: frequentist, Bayesian and set-membership estimation. We use the Fitzhugh-Nagumo model with synthetic data as a case study. The computational performance and robustness of these methods is discussed, with a particular focus on their predictive capability using cross-validation.