270190 VU Introduction to metabolic modelling (2025S)
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 Tu 04.02.2025 08:00 to Tu 25.03.2025 23:59
- Deregistration possible until Tu 25.03.2025 23:59
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Seminarraum der Zukunft (Prominentenzimmer), Universitätsring 1, https://www.univie.ac.at/uploads/media/plan-hauptgebaeude-universitaet-wien-2020-v1.pdf
- Monday 24.03. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 25.03. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Thursday 27.03. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 28.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 29.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Wednesday 30.04. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Tuesday 06.05. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Friday 09.05. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Monday 12.05. 16:45 - 18:15 Prominentenzimmer Hauptgebäude, Tiefparterre Hof 4
- Friday 16.05. 16:45 - 18:15 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
Literature references to the scientific literature will be available on Moodle.
Association in the course directory
CH-CBS-05, BC-CHE II-8, Design
Last modified: We 07.05.2025 00:02
(*) 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