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27634 Bioinformatics 2 for It and Health

Primarily for students at the study line "It and Health" at Copenhagen University

Danish title:

Bioinformatik 2 for It og Sundhed


Point( ECTS )


Course type:



E1A (Mon 8-12) and E2A (Mon 13-17)
Teaching period Mondays November 16 to December 14 and January 4 and 11.


Campus Lyngby

Scope and form:

Lectures, computer-based exercises and project

Duration of Course:

13 weeks + 3 weeks

Date of examination:

Exam January 18, 2016.

Type of assessment:

Exam duration:



Recommended prerequisites:


General course objectives:

The goal of the course is to learn to use and combine existing bioinformatics tools to build a complete pipeline to collect, analyze, visualize and model biological and clinical data.

The students will acquire the practical knowledge to build scripts and use libraries (BioPython) to access remote databases for biological molecules such as Genbank, RefSeq, and UniProt. The students will learn how to collect and analyze large volume of data from files and databases using simple scripts made using UNIX commands.
The students will learn how to load, visualize and compute basic operations and statistical analysis on their data using R. Finally, we aim to provide insights into the principles and pros and cons of statistical modeling, classification and prediction so that students can critically evaluate and compare performances of such tools.

The students are expected to have basic IT skills and should be comfortable with programming in Python and R prior to attending the course.

Learning objectives:

A student who has met the objectives of the course will be able to:
  • Put together bioinformatics tools in a pipeline using Unix shell scripts and small programs (scripts).
  • Write scripts to collect and filter datasets.
  • Process data using Unix commands.
  • Analyze sequences in Python.
  • Process data with R.
  • Visualize data in R.
  • Compute basic statistical analysis with R.
  • Perform basic statistical modeling with R.
  • Analyze and evaluate biological and medical predictions.


The course introduces the participants to the practical usage of bioinformatics tools for common biological data analysis tasks. The course covers the methods of accessing remote databases using BioPython and methods for data manipulation and visualization using Unix and R. The course presents the usage of common statistical and modeling methods used in bioinformatics, such as artificial neural networks and random forests, and introduces the use of these methods in the relevant biological systems. There is a strong emphasis on streamlining work processes with those using programming.


online materials, papers

Green challenge participation:

Please contact the teacher for information on whether this course gives the student the opportunity to prepare a project that may participate in DTU´s Study Conference on sustainability, climate technology, and the environment (GRØN DYST). More infor http://www.groendyst.dtu.dk/english


Lasse Folkersen , Lyngby Campus, Building 208 , lasfol@cbs.dtu.dk


27 Department of Systems Biology

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Last updated: 24. september, 2015