Figure 1.

Concept figure. pyPESTO covers the full parameter estimation workflow, from problem definition (i.e. defining the parameter estimation problem based on dynamic model, data, parameters, and objective function), parameter optimization (i.e. finding parameters optimally explaining the data under the assumed objective function), uncertainty quantification (i.e. assessing uncertainty in parameter values), to visualization and analysis of results, and provides various features such as storage, parallelization, and advanced algorithms. See the main text for a contextualization of the key words indicated in the figure.