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Graduate courses

Departments' graduate courses for PhD-students.

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Syllabus for

Academic year
KMG060 - Systems biology  
Systembiologi
 
Syllabus adopted 2017-02-09 by Head of Programme (or corresponding)
Owner: MPBIO
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: Second-cycle
Major subject: Bioengineering
Department: 28 - BIOLOGY AND BIOLOGICAL ENGINEERING


Teaching language: English
Open for exchange students: Yes

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5 c Grading: TH   7,5 c   27 Oct 2018 pm M   09 Jan 2019 am M   27 Aug 2019 pm M  

In programs

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

Examiner:

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

The aim of the course is to give the students a fundamental understanding of: 1) how mathematical modeling of biological systems can be used to gain novel biological insight and 2) how high-throughput biological data can be analyzed. The overall objective is that by passing this course the students should have a solid overview of how systems biology impacts modern medical, biotechnological and nutritional research.

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

A student that has passed the course is expected to be able to:
  • Describe the principles of systems biology
  • Describe key cellular processes like transcription, translation, signaling and protein secretion in a quantitative fashion
  • Perform metabolic network reconstruction based on biochemical and genomic information
  • Describe how genome-scale metabolic models (GEMs) can be used for analysis of cellular physiology and how they are used in modern biology.
  • Perform analysis of the stoichiometric matrix generated by metabolic reconstructions
  • Describe how cellular growth is constrained and how biological and physical constraints can be applied for modeling cellular growth
  • Define objective functions for cellular growth and describe how these can be used for prediction of cellular growth
  • Describe the concept of equivalent states in cellular metabolism
  • Quantify the biosynthetic requirements for cellular growth
  • Describe the principles of RNAseq, proteomics and metabolomics.
  • Describe how meta-omics data can be analyzed

Content

The course gives a description of how systems biology is impacting medicine, biotechnology and nutrition. The core of systems biology is quantitative analysis of cellular functions and in the course all key cellular processes will be discussed in a quantitative fashion. Focus will be on metabolism, which is a part of cellular functions that is best understood, but also a part that is linked to all other cellular processes and hereby represents the core of cellular function and operation. The course will further give insight into how metabolic networks can be reconstructed from biochemical and genomic information. Topological analysis of large genome-scale metabolic models (GEM) will be performed and the basic principles for operation of large metabolic networks will be discussed. The students will also use a small metabolic network to simulate the growth of a living cell.

The course will give a brief introduction to different methods for generating so-called omics data, e.g. transcriptome, proteome and metabolome data. The students will be presented with a number of examples from analysis of transcriptome data from different organisms. They will further get hands-on experience with analysis of raw data from transcriptome experiments, and will be introduced to how proteome and metabolome data can be analyzed using similar statistical techniques. Finally the course will present, using quantitative data, what are key drivers for cellular growth and what are constraining cellular growth. Throughout the course there will be given examples from studies of yeast, nutritional studies, and from analysis of clinical data.

Organisation

The course involves lectures and computer exercises.

Literature

Systems Biology: Constraint-Based Reconstruction and Analysis by Bernhard Ø Palsson and lecture notes.

Examination including compulsory elements

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.


Page manager Published: Thu 04 Feb 2021.