TBT4165 - System Biology and Biological Networks
This class will give an introduction to systems biology methods in modeling and analysis of cellular networks, with strong relevance to synthetic biology and the iGEM competition. This course has a special emphasis on (1) biological interaction networks, and (2) genome-level cellular metabolism. Students will learn through lectures and homework, and gain hands-on experience using 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.
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 basic concepts, principles and methods of metabolic engineering.
- 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.
- Computer lab
Further on evaluation
Portfolio assessment is the basis for the grade in the course. The portfolio includes a final written exam (50%) and exercises (50%). The results for the parts are given in %-scores, while the entire portfolio is assigned a letter grade. If there is a re-sit examination, the examination form may be changed from written to oral. In cases of rescheduled examination, there will be an exam in the whole portfolio.
Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.
Recommended previous knowledge
Basic knowledge in molecular biology similar to TBT4145/TBT4146 Molecular Genetics, statistics similar to ST0103 Statistics with Applications. Some experience with programming.
E.O.Voit "A First Course In Systems Biology" (2012).
A.-L. Barabási "Network Science" (2016).
Examination arrangement: Portfolio assessment
|Term||Statuskode||Evaluation form||Weighting||Examination aids||Date||Time||Room *|
- * The location (room) for a written examination is published 3 days before examination date.