Universität Wien

270151 VU Computational Systems Biology: from enzymes to networks (2022W)

3.00 ECTS (2.00 SWS), SPL 27 - Chemie
Continuous assessment of course work
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

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).

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

Computer models of biochemical networks are able to connect the genotype with the phenotype. In this primer we will give an introduction to biochemical network analysis. We will introduce basic concepts of network reconstruction, kinetic modelling and constraint based analysis of biological networks. In addition you will get a brief introduction to COPASI and cobrapy to carry simple computational analyses.

(*) Basic mathematical concepts in systems biology
(*) Reconstruction of biochemical networks
(*) Stoichiometric networks and their analysis
(*) Applications in biotechnology

After 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

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