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270190 VU Introduction to metabolic modelling (2024S)
Continuous assessment of course work
Labels
MIXED
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 03.02.2024 08:00 to Mo 26.02.2024 23:59
- Deregistration possible until Mo 26.02.2024 23:59
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Wednesday 03.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 15.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 16.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Thursday 18.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 22.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 23.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 29.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 30.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Thursday 02.05. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 13.05. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 13.05. 18:30 - 20:00 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 02.07. 09:00 - 14:00 Seminarraum 3, Währinger Straße 29 1.UG
Information
Aims, contents and method of the course
Assessment and permitted materials
Oral 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
CH-CBS-05, Design
Last modified: Th 18.07.2024 14:46
(*) 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