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.

  • Education cycle

    Second cycle
  • Main field of study

  • Grading scale

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

Course offerings

Autumn 18 for programme students

Autumn 18 Doktorand for single courses students

  • Periods

    Autumn 18 P2 (7.5 credits)

  • Application code


  • Start date


  • End date


  • Language of instruction


  • Campus


  • Tutoring time


  • Form of study


  • Number of places *

    Max. 1

    *) If there are more applicants than number of places selection will be made.

  • Course responsible

    Lukas Käll <>

  • Teacher

    Lars Arvestad <>

    Lukas Käll <>

    Olof Emanuelsson <>

  • Target group

    For doctoral students at KTH

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 main content

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.


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.


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


  • LABA - Computer Exercises, 1.5, grading scale: P, F
  • PRO1 - Project, 6.0, grading scale: A, B, C, D, E, FX, F

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

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.

Offered by

CBH/Gene Technology


Lukas Käll <>

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.


Course syllabus valid from: Spring 2016.
Examination information valid from: Spring 2019.