Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models

This is a supplementary code repository for the article: N. Tsiantis, A. F. Villaverde, and J. R. Banga. Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models. Submitted, 2019. In this article, we investigate the simultaneous inference of states, time-invariant parameters and time-dependent inputs in biological modelling. In other words we consider both the theoretical observability problem (FISPO) and the practical full system reconstruction problem (optimal tracking). Here we provide the scripts to run the optimal tracking problem for the case studies presented in the aforementioned article. The implementation is based on the methodology presented in [1] (see references), using the AMIGO2 toolbox. DEPENDENCIES The users will need: - a Matlab R2015b (or later) installation, under Windows, Linux or Mac operating systems - the AMIGO2 toolbox with the IOC add-on, available at: https://sites.google.com/site/amigo2toolbox/home/amigo2_ioc Users need to make sure that the above AMIGO2 toolbox is fully functional before attempting to run the inverse optimal control case studies. Please refer to the AMIGO2 documentation. More detailed examples of IOC case studies can be also found in [2] (see references) For any questions please contact us at: nikolaostsiantis@gmail.com, afvillaverde@iim.csic.es , julio@iim.csic.es