BB2490 Analysis of Data from High-throughput Molecular Biology Experiments 7.5 credits

Analys av data från storskaliga molekylärbiologiska experiment

This is an advanced course in bioinformatics. The course contains the fundamentals of bioinformatics analysis of large-scale data sets from genomics and proteomics experiments (in particular, DNA sequencing and mass spectrometry). The course is primarily aimed at students at the Biotechnology Master of Science in Engineering Degree program and the Medical Biotechnology Masters' program. The course consists of lectures and computer-based laboratory exercises.

Offering and execution

Course offering missing for current semester as well as for previous and coming semesters

Course information

Content and learning outcomes

Course contents *

The course contains the fundamental theory of, and the use of, bioinformatics analysis of large data sets from high-throughput genomics and proteomics experiments – in particular, massively parallel DNA sequencing and protein mass spectrometry: how this theory is implemented in state-of-the-art tools for handling, analyzing, and visualizing the data; how these tools are applied on real high-throughput molecular biology data; and how the outcome of the analysis may be interpreted in a biologically or medical relevant context.

The course consists of lectures, student-prepared presentations, computer-based laboratory exercises, and a project.

The course is primarily aimed at students at the Biotechnology Master of Science in Engineering Degree program and the master programmes Medical Biotechnology and Molecular Techniques in Life Science.

Intended learning outcomes *

This is an advanced course in bioinformatics. After passing the course, the student should be able to:

  • describe widely used high-throughput experimental techniques employed to investigate the DNA, RNA, and protein contents of a cell, tissue, or organism
  • explain the theory of state-of-the-art tools/algorithms for processing data from high-throughput molecular biology experiments.
  • choose appropriate methods and tools for processing data from high-throughput molecular biology experiments.
  • Use tools for processing data from high-throughput molecular biology experiments.
  • interpret the results of the data analyses in a biologically or medical relevant context.
  • reflect over the choice of methods and tools and how it influences the outcome of the analyses

Course Disposition

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Literature and preparations

Specific prerequisites *

Admission requirements for programme students at KTH:
At least 150 credits from grades 1, 2 and 3 of which at least 100 credits from years 1 and 2, and bachelor's work must be completed.  The 150 credits should include a minimum of 20 credits within the fields of Mathematics, Numerical Analysis and Computer Sciences, 5 of these must be within the fields of Numerical Analysis and Computer Sciences, 20 credits of Chemistry, possibly including courses in Chemical Measuring Techniques and 20 credits of Biotechnology or Molecular Biology.

Admission requirements for independent students:
A total of 20 university credits (hp) in biochemistry, microbiology and gene technology/molecular biology. 30 university credits (hp)  chemistry, as well as 20 university credits (hp) in mathematics and computer science as well as bioinformatics 3,5 university credits (hp) and statistics 3,5 university credits (hp) or corresponding. Documented proficiency in English corresponding to English B.

Recommended prerequisites

The following courses, or equivalent, are recommended: Bioinformatics and basic probability theory corresponding to BB2440 Bioinformatics and Biostatistics, (or bioinformatics corresponding to DD2396 Bioinformatics and probability theory corresponding to SF1901 Probability theory and statistics). Computer acquaintance equivalent to the course DD2397 Applied bioinformatics.


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Scientific articles and web resources as assigned during the course. Handouts from the lectures.

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 *

  • LABA - Computer Exercises, 1.5 credits, Grading scale: P, F
  • PRO1 - Project, 6.0 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.

No aids are allowed other than those specified in the course PM.

Other requirements for final grade *

The final grade on the course is determined by the grade on the project (PRO1, grade scale A-F). Passed grade also in the LABA. There are parts of the course that has compulsory attendance.

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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Lukas Käll

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 web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web BB2490

Offered by

CBH/Gene Technology

Main field of study *


Education cycle *

Second cycle

Add-on studies

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Supplementary information

Students are required to sign up at least two weeks in advance for examination.

The course is given provided at least seven students are admitted.