Statistical Inference for Dynamical Systems

What it is about

In this module you will learn how to model biological reaction networks with ordinary differential equations and how parameter values of these models can be reliably estimated from experimental data. You will acquire methods for parameter estimation (frequentist and Bayesian) as well as techniques for analyzing uncertainty and practicality of parameters and implement these in MATLAB.

What you will be able to do

• Model biochemical reaction networks with ODEs
• Solve parameter estimation problems for ODE models in MATLAB
• Analyze uncertainties of parameter estimates in MATLAB
• Critically evaluate parameter estimation methods

What the module consists of

• VorlesungTheoretical foundations of model building, estimation methods, identifiability, Bayesian statistics and properties of estimators
• Übung/PraktikumAccompanying practical sessions with exercises and solutions for deepening understanding and application (including MATLAB implementations)

Teaching method

• Lecture with demonstration examplesPresentation of content and examples for introduction
• DiscussionInteraction with students for deepening understanding and reflection
• Problem sheets with solutionsIndependent practice and verification of understanding
• Practical MATLAB implementationsHands-on experience with modeling, estimation and uncertainty analysis