Analysis of Metabolic Networks

This course focuses on the quantitative analysis of cellular metabolism and its interaction with the environment. Central to this is understanding how genetic and environmental factors shape key cellular rates, such as growth rate, uptake, and product rates, through complex and interconnected networks, including:

• Metabolic reaction networks

• Genetic regulatory networks

Throughout the course, students will explore various modeling approaches to evaluate and predict cellular metabolism. Emphasis is placed on how genetic modifications and environmental changes affect metabolic rates.

Modeling serves as a useful tool to test hypotheses and interpret biological behavior, but it must be grounded in experimental data. Therefore, the course also covers experimental techniques for quantifying fluxes within metabolic networks.

We will approach the material at two levels of detail:

• Black-box kinetics, building on Bachelor-level foundations with additional new material

• Medium-scale stoichiometric and thermodynamic models, suitable also for analyzing larger metabolic systems

Topics include:

• Refresher on mass balances, conversion rates, stoichiometry, and energy/product/growth pathways

• Validation and reconciliation of experimental data, including error propagation

• Metabolic flux analysis of medium-to-large networks

• Transport mechanisms across cellular membranes

• Kinetics of metabolic pathways

• Mathematical modeling of central carbon metabolism

• Resource allocation modeling in metabolism and growth

• Dynamic modeling of metabolic networks

• Integration of biological databases and bioinformatics resources

Python will be used as the primary simulation tool for modeling and analysis throughout the course.