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Syllabus for

Academic year
KMG060 - Systems biology
 
Syllabus adopted 2012-02-21 by Head of Programme (or corresponding)
Owner: MPBIO
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Bioengineering
Department: 21 - CHEMISTRY AND CHEMICAL ENGINEERING


Teaching language: English
Open for exchange students
Block schedule: B

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5c Grading: TH   7,5c   19 Dec 2013 am V,  25 Apr 2014 am M,  26 Aug 2014 pm V

In programs

MPBIO BIOTECHNOLOGY, MSC PROGR, Year 1 (compulsory)
MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 2 (elective)
MPENM ENGINEERING MATHEMATICS AND COMPUTATIONAL SCIENCE, MSC PROGR, Year 1 (elective)

Examiner:

Professor  Jens B Nielsen


Course evaluation:

http://document.chalmers.se/doc/c1edbf5f-437c-4aaf-827a-b6673ad48c5d


  Go to Course Homepage

Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

Chemistry, Biochemistry, Mathematics (linear algebra, multivariable analysis, differential equations), Cell and Molecular Biology.

Aim

To teach the student about methods for data generation, data analysis and mathematical modelling in systems biology.

Learning outcomes (after completion of the course the student should be able to)

have knowledge of available general data generation techniques in
systems biology, their applicability and limitations.

be able to analyse transcriptome data using different bioinformatics methods.
be able to evaluate different mathematical models for simulation of biological systems

have hands-on experience from a data analysis and model simulations.

Content

The course considers the following topics:

Genomics: genome sequencing methods, genome sequence analysis, comparative genomics.
Transcriptomics: DNA arrays and gene expression data, cluster analysis
Proteomics: measurement of the proteome, protein interaction networks.
Metabolomics: measurement of the metabolome.
Metabolic networks: setting up genome-scale metabolic models, analysis of metabolic networks.
Integrated data analysis: analysis of molecular interaction networks.
Mathematical modelling: setting up dynamic models, simulation of dynamic models

The course includes a project corresponding to 2.5 credits.

Organisation

.

Literature

See separate list.

Examination

The student is examined by exercises, project work and a written exam.


Published: Mon 28 Nov 2016.