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Graduate courses

Departments' graduate courses for PhD-students.

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Syllabus for

Academic year
KMG060 - Systems biology
 
Syllabus adopted 2014-02-24 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: 28 - BIOLOGY AND BIOLOGICAL ENGINEERING


Teaching language: English
Open for exchange students

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5 c Grading: TH   7,5 c   14 Jan 2016 am H,  07 Apr 2016 am M,  23 Aug 2016 pm SB

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



Eligibility:


In order to be eligible for a second cycle course the applicant needs to fulfil the general and specific entry requirements of the programme that owns the course. (If the second cycle course is owned by a first cycle programme, second cycle entry requirements apply.)
Exemption from the eligibility requirement: Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling these requirements.

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

The course involves lectures and computer exercises. The computer exercises are compulsory and reports from these have to be approved for passing the course. The exam is a four hour written exam.

Literature

See separate list.

Examination

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


Page manager Published: Thu 04 Feb 2021.