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NBIB15021U  Fundamental Bioinformatics Volume 2017/2018

Course information

Credit7,5 ECTS
Duration1 block
Block 3
Course capacity125
Continuing and further education
Study boardStudy Board for the Biological Area
Contracting department
  • Department of Biology
Course responsible
  • Jeppe Vinther (8-6e7a6d72786c697644666d73326f7932686f)
Saved on the 08-03-2017

BSc Programme in Biochemistry
BSc Programme in Biology


Biological databases, sequence alignment (pairwise and multiple), phylogeny, genomics, next generation sequencing, expression analysis, RNA structure, introduction to R for data analysis, systems biology.

Learning Outcome

After successfully completing the course students will be able to use, apply and understand the most important bioinformatical tools and theories that can facilitate their future work in biological sciences (e.g. biology, biochemistry, biomedicine etc.).


At the conclusion of the course, the students should be able to:

  • Explain the basic concepts behind the covered topics.
  • Describe the major algorithms covered.
  • Suggest computational tools that could be used to solve a given biological problem.


At the conclusion of the course, the students should be able to:

  • Apply programs for performing sequence alignment (pairwise and multiple), constructing phylogenies, predicting protein and RNA structure and analysing expression data.
  • Find and use Biological databases for retrieving and displaying information.
  • Work with data from next generation sequencing experiments.


At the conclusion of the course, the students should be able to:

  • Perform a correct computational analysis of a given biological problem, which includes the selection of relevant tools.
  • Explain and discuss strengths and weaknesses of the applied tools and how these affect the obtained results.
  • Suggest further analyses that could improve the results obtained.

See Absalon.

Teaching and learning methods
Flipped classroom teaching. The students watch recorded lectures and answer simple multiple choice quizzes before the class. During class exercises are solved in small group. In the workshops, more elaborate exercises are solved with help from assistant teachers.
6 weeks with max 9 hours per week (6 hours class/problemsolving + 3 hours workshop exercises), followed by 1 week to solve an exam assignment.
Feedback form
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
Academic qualifications
Basic genetics, biochemistry (incl. protein chemistry) and molecular biology.

The course is mandatory for Biochemistry. Biology students are recommended to have passed Matematik/Statistik, Almen Biokemi og Almen Molekylærbiologi. Molecular Biomedicine students are recommended to have passed Biokemi and Molekylærbiologi.
Students should bring a laptop computer to fully benefit from the course, since the use of computers is an integrated part of the course. Students should know how to use and administer their computer. No expert knowledge or programming skills are needed. See course homepage for more details.
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Credit7,5 ECTS
Type of assessment
Oral examination, 30 minutes (no preparation)
Individual exam based on a one week practical assignment.
AidWithout aids
Marking scale7-point grading scale
Censorship formNo external censorship
Several internal examiners

Oral exam (30 min.) based on curriculum (no preparation and no aid).

Criteria for exam assesment

To get the grade 12 (outstanding performance, non or very few insignificant omissions):

  • The student can apply the tools covered in the course to solve different bioinformatics problems.
  • The student can correctly interpret the results and explain possible short-comings of the tools.
  • The student can perform a correct computational analysis of a given biological problem, including the selection of the most relevant tools.
  • The student can explain possible weaknesses of the analyses and suggest further analyses.
  • The student can explain the basic concepts behind all topics covered.
  • The student can describe the major algorithms covered.
Theory exercises21
Total 206,0
Saved on the 08-03-2017