| Summary: | International Conference on Scientific Computation and Differential Equations, July 25–29, 2022, Reykjavík, Iceland Mathematical optimisation is at the core of many problems related to the modelling and design in the context of systems and synthetic biology. For example, it has been the underlying hypothesis for model development in flux balance analysis (FBA) or the activation of metabolic pathways; is at the kernel of model identification (parameter estimation and optimal experimental design) and enables the computation of optimal controls to achieve a desired biological goal or process performance, etc. Here we consider two of such problems and their combination to address the multi-scale modelling of cellular metabolism: 1) The use of optimisation to identify dynamic models of biological systems: parameter estimation and model selection. 2) The use of optimality as the underlying hypothesis to model the intracellular dynamics of metabolism. Both problems are usually formulated as non-linear programming problems with dynamic and algebraic constraints. The non-linearity of models and their dimension pose a challenge for its numerical solution. Therefore emphasis will be paid on the need to use suitable numerical techniques, including global optimisers, and available software tools to succeed No
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