Universität Wien

270127 VU Introduction to metabolic modelling (2022S)

3.00 ECTS (3.00 SWS), SPL 27 - Chemie
Moodle

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Details

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 02.03. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP
  • Wednesday 09.03. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP
  • Wednesday 16.03. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP
  • Wednesday 23.03. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP
  • Wednesday 30.03. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP
  • Wednesday 06.04. 18:00 - 21:00 Kleiner Hörsaal 3 Chemie Boltzmanngasse 1 HP

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 and constraint based analysis of biological networks. In particular we will cover the process of building (genome scale) metabolic models and study the steady state behavior of these networks with flux balance analysis (FBA) and related methods. Finally we will show that these methods are successfully used in metabolic engineering, where FBA is a standard approach for the rationally designing microbial cell factories.

(*) 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

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

Last modified: Tu 18.10.2022 09:09