270151 VU Computational Systems Biology: from enzymes to networks (2022W)
Continuous assessment of course work
Labels
ON-SITE
17.10.-21.10. von 16:00-18:30 im Hörsaal 1
21.11. von 16:00-18:30 im Hörsaal 3
22.11. von 15:30-18:00 im Hörsaal 3
23.11. von 16:30-19:00 im Seminarraum 2
24.11. von 16:00-18:30 im Seminarraum 2
25.11. von 16:00-18:30 im Hörsaal 3
21.11. von 16:00-18:30 im Hörsaal 3
22.11. von 15:30-18:00 im Hörsaal 3
23.11. von 16:30-19:00 im Seminarraum 2
24.11. von 16:00-18:30 im Seminarraum 2
25.11. von 16:00-18:30 im Hörsaal 3
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Sa 10.09.2022 08:00 to We 28.09.2022 23:59
- Deregistration possible until We 28.09.2022 23:59
Details
max. 20 participants
Language: German
Lecturers
Classes
17.10.-21.10. von 16:00-18:30 im Hörsaal 1
21.11. von 16:00-18:30 im Hörsaal 3
22.11. von 15:30-18:00 im Hörsaal 3
23.11. von 16:30-19:00 im Seminarraum 2
24.11. von 16:00-18:30 im Seminarraum 2
25.11. von 16:00-18:30 im Hörsaal 3
Information
Aims, contents and method of the course
Assessment and permitted materials
Written exam (75%) + small scale research project (25%) + home work (bonus points, 4% per home work)
Minimum requirements and assessment criteria
Some knowledge of linear algebra is advantageous and very helpful but not a prerequisite
Examination topics
Content of the lectures
Reading list
Association in the course directory
AN-2, BC-1, CHE II-1, BC-3, CH-CBS-05, BC-CHE II-8, Design
Last modified: Mo 03.10.2022 14:09
(*) Reconstruction of biochemical networks
(*) Stoichiometric networks and their analysis
(*) Applications in biotechnologyAfter successful completion of this course, students
(*) Understand the challenges in mathematical modeling
(*) Know important types of mathematical models
(*) Are able to set up simple reaction network models
(*) Use metabolic models for exploration and strain design
(*) Know various data sources supporting metabolic analyses