Course content

This class will give an introduction to systems biology methods in modeling and analysis of cellular networks, with emphasis on (1) stochastic and deterministic description of simple gene regulatory circuits, (2) protein interaction networks, and (3) genome-level cellular metabolism. Students will learn through lectures and homework, and gain hands-on experience current software in a PC-based lab setting. An interdisciplinary presentation of the topics will be emphasized, making the class accessible to students with a background in computer science, biology, chemistry, and physics.

Learning outcome

At the completion of this course, the students are expected to be able to:
- Explain basic concepts, models, and statistical measures to characterize the properties of general networks, as well as using the software tool Cytoscape to analyze empirical networks.
- Explain and construct models for small genetic circuits and analyze their properties, as well as master the software tool Dizzy for stochastic simulations.
- Explain the organization and construction process of genome-scale metabolic networks, explain the principles behind constraint-based analysis (especially Flux Balance Analysis), as well as being proficient in the use of the COBRA toolbox in MatLab for the numerical analysis of empirical models.

Learning methods and activities

Lectures, homework and exercises (PC-lab). Lectures will be given in English.

Compulsory assignments

• Exercises

Recommended previous knowledge

Basic knowledge in molecular biology similar to TBT4145 Molecular Genetics, statistics similar to ST0103 Statistics with Applications. Some experience with programming.

Course materials

Announced at first lecture.