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
Wednesday
03.04.
20:15 - 22:00
Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
Monday
15.04.
16:45 - 18:15
Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
Monday
15.04.
18:30 - 20:00
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
N
Monday
13.05.
16:45 - 18:15
Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
Monday
13.05.
18:30 - 20:00
Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
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
AN-2, CH-CBS-05,Design
Last modified: Mo 11.03.2024 13:06
(*) 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