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DD2399 Omic Data and Systems Biology 7.5 credits

Advanced course in computer science focusing on the analysis of high troughput omics data (i.e., genomic, transcriptomic, and proteomic data).

Course offering missing for current semester as well as for previous and coming semesters
Headings with content from the Course syllabus DD2399 (Spring 2013–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Overview of classic and modern high-throughput methods for sequencing DNA and analysis of proteins with mass spectrometry. Methods for gene and genome assembly from DNA data. Mapping of short DNA reads to a genome for further analysis of genome variation and gene structure. Techniques for analysis gene structure and activity.
Identification and quantification of proteins given mass spectrometry data.

Intended learning outcomes

The students should after the course

  • be able to discuss modern high-throughput methods with biologists,
  • know current public databases well enough to be able to evaluate the feasibility of a project,
  • be able to use popular tools for analysis of omics data as wells as explain and discuss the relative benefits of these,
  • be able to give intuitive descriptions of algorithms and methods for analysis of omics data as well as, using the course literature, immediately implement those.

Course disposition

No information inserted

Literature and preparations

Specific prerequisites

Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.

Recommended prerequisites

Bioinformatics corresponding DD2397/DD2404 Applied Bioinformatics.
Computer science corresponding to DD1339/DD1340/DD1341 Introduction to Computer Science or DD1320/DD1321 Applied Computer Science. Probability theory corresponding to SF190 Probability Theory and Statistics.


No information inserted


To be announced at the web page for the course at least 4 weeks before the course starts.

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


  • LAB1 - Laboratory Work, 7.5 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.

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see:

Other requirements for final grade

Three laborations.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted


Profile picture Lars Arvestad

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 DD2399

Offered by

CSC/Computer Science

Main field of study

Biotechnology, Computer Science and Engineering

Education cycle

Second cycle

Add-on studies

Please discuss with the instructor.


Lars Arvestad, e-post: