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Explore the power of Julia for systems biology in this comprehensive workshop focused on generating personalized computational models. Learn to implement ODE models using various SciML packages and custom implementations. Dive into parameter estimation and model selection strategies, including parameter sensitivity and identifiability analysis. Discover how to rapidly create personalized models using DifferentialEquations.jl and Optimization.jl. Work with an in-house glucose-insulin system model to understand ODE system implementation and resolution, including SBML import. Gain insights into model selection techniques and parameter estimation strategies, emphasizing the benefits of regularization. Apply these concepts using a publicly available meal response dataset. Benefit from a combination of short theoretical presentations and hands-on practice in Jupyter notebooks, enabling independent learning and practical application of Julia in systems biology.
