732A51 · 6 credits · Advanced level (A1F) · Statistik
Bioinformatics
Active · next start HT 2026
100%
passed the latest regular sitting
LAB1 · 12 Jan 2026 · 7 students
100%
passed the regular sittings, all sittings over the last 5 years
LAB1 · 36 students
This module only reports passing results, so the pass rate does not show how many did not pass.
Hand-in or lab
LAB1 Laboratory
- P
Main rounds
100% passed · 36 students
- 100%7
- 100%8
- 100%6
- 100%6
- 100%9
Later rounds
No sittings with at least 5 students.
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%2
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Other module
DAT1 Examination
- A
- B
- C
- D
- E
- F
Main rounds
68% passed · 34 students
- 67%6
- 100%6
- 100%7
- 14%7
- 63%8
Later rounds
No sittings with at least 5 students.
- Get B or A: 41% (34 students)
Show small sittings (7)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
- 33%3
- 100%1
- 100%1
- 100%3
- 50%2
Other module
FRIV Voluntary Assignment
- A
- P
Main rounds
100% passed · 5 students
- 100%5
Later rounds
No sittings with at least 5 students.
- Get A: 0% (5 students)
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%3
About the course
Aim
After completing the course, the student shall be able to
- Explain concepts in molecular biology and have a primary understanding of various techniques used to generate data.
- Explain important algorithms and principles for statistical models used for the analysis of high-dimensional molecular data.
- Apply some of the most important computer programs in bioinformatics and statistics to molecular data examples.
The teaching consists of lectures and computer exercises. In addition, the student should engage in self-study. The language of instruction and examination is English.
Content
The course introduces basic molecular biology concepts and how to analyze data with bioinformatics and statistics. More specifically, the course includes:
- Basics of molecular biology and genetics
- Hidden Markov models, genetic sequence analysis
- Sequence similarity, sequence alignment
- Phylogeny reconstruction
- Quantitative trait modelling
- Microarray analysis
- Network biology
- Examiner
- Krzysztof Bartoszek
- Main field of study
- Statistik