PEtab.jl - Efficient Parameter Estimation for Dynamic Models
Offered By: The Julia Programming Language via YouTube
Course Description
Overview
Explore efficient parameter estimation for dynamic models in biology and pharmaceutical research using PEtab.jl, a Julia package leveraging the SciML ecosystem. Learn how to import problems specified in the PEtab standard format, utilize SBMLImporter.jl for importing SBML models, and set up parameter estimation problems directly in Julia using Catalyst.jl or ModelingToolkit.jl. Discover various gradient computation methods, including ForwardDiff and SciMLSensitivity, and gain insights on selecting the most appropriate approach. Evaluate the performance of PEtab.jl compared to existing tools like pyPESTO and AMICI through an extensive benchmark on real models with real data, addressing the question of Julia's suitability for parameter estimation in dynamic models within biological and pharmaceutical contexts.
Syllabus
PEtab.jl - Efficient parameter estimation for dynamic models | Persson | JuliaCon 2024
Taught by
The Julia Programming Language
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