392032 Metabolic network analysis (BS) (SoSe 2017)

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This short course will provide an overview of metabolic network
analysis, a topic at the intersection of computational biology, systems
biology and mathematical modelling. It will go into detail into the
modeling and analysis of metabolic networks in the constraint-based
formalism, which complement metabolomics data analysis. By the end of
the course the students will have an appreciation for the advantages and
shortcomings of metabolic network models, the tools used for their
analysis, and the open problems currently facing the field. They will
also learn the use of Mongoose, an open-source metabolic network
analysis platform (mongoose.csail.mit.edu).

Tentative Schedule

Day 1: Metabolic network analysis formalisms

topological analysis and deficiency zero theorem
biochemical systems analysis and control theory
constraint-based formalism and flux balance analysis

Day 2: Structural analysis of metabolic network models

blocked reactions classification
enzyme and isozyme subsets
redundant constraint identification

Day 3: Troubleshooting metabolic network models

unblocking blocked reactions
identifying and correcting “free lunches”
network reconciliation and refinement

Day 4: Extensions

inclusion of thermodynamic constraints
metabolic engineering applications
enumeration of elementary modes and minimal cut sets

Teaching staff

Dates ( Calendar view )

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Subject assignments

Module Course Requirements  
39-Inf-MIKE Modularisierter individueller Kompetenz-Erwerb (MiKE) - Ungraded examination Student information
39-M-Inf-MIKE Modularisierter individueller Kompetenz-Erwerb (MiKE) - Ungraded examination Student information
39-M-MBT-MIKE Modularisierter individueller Kompetenz-Erwerb (MiKE) - Ungraded examination Student information

The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.

Degree programme/academic programme Validity Variant Subdivision Status Semester LP  
Bioinformatik / Promotion Lecture/seminar Wahl 1 unbenotet Graduierte

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Address:
SS2017_392032@ekvv.uni-bielefeld.de
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Last update basic details/teaching staff:
Wednesday, January 25, 2017 
Last update times:
Wednesday, January 25, 2017 
Last update rooms:
Wednesday, January 25, 2017 
Type(s) / SWS (hours per week per semester)
block seminar (BS) / 2
Department
Faculty of Technology
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92130672