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CB2030 Systems biology 7.5 credits

Information per course offering

Termin

Information for Autumn 2024 Start 28 Oct 2024 programme students

Course location

AlbaNova

Duration
28 Oct 2024 - 13 Jan 2025
Periods
P2 (7.5 hp)
Pace of study

50%

Application code

51222

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Places are not limited

Target group
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Planned modular schedule
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Contact

Examiner
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Course coordinator
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Teachers
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Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus CB2030 (Autumn 2021–)
Headings with content from the Course syllabus CB2030 (Autumn 2021–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course is based on the fundamental theory of Systems Biology, i.e. the holistic understanding of biology as large numbers of interacting biomolecules. The following subjects will be covered:

  • Hypothesis Testing and Multiple Hypothesis Corrections
  • Basic machine learning and clustering
  • Principal Component Analysis
  • Pathway Analysis
  • Graph algorithms, and their applications to interaction networks and co-expression networks
  • Genome-scale metabolic models
  • Flux Balance Analysis
  • Co-regulation of genes
  • Expression Quantitative Trait Loci (eQTLs)
  • Time-dependent regulatory changes in transcription and translation

Intended learning outcomes

After the successful completion of the course the student will be able to:

  1. Describe methods essential for the representation of a system using some fundamental Systems Biology approaches.
  2. Explain the theory behind the statistical methods commonly used within Systems Biology, and reflect on their applicability to different biological contexts.
  3. Apply achieved methodological knowledge to biologically relevant problems.
  4. Interpret the results from commonly used Systems Biology methods.
  5. Design and justify the processing of omics data for the interpretation within Systems Biology.

Literature and preparations

Specific prerequisites

The following courses, or equivalent, are recommended:

  • Bioinformatics corresponding to BB2441 Bioinformatics,
  • Programming corresponding to BB1000 Programming in Python
  • Probability theory corresponding to SF1911 Statistics for Bioengineering 6.0 credits
  • Knowledge of modern omics experiments corresponding to BB2255 Applied Gene Technology

Recommended prerequisites

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Equipment

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Literature

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LAB1 - Computer Exercises, 2.5 credits, grading scale: P, F
  • TEN2 - Written exam, 5.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Biotechnology, Molecular Life Science

Education cycle

Second cycle

Add-on studies

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