8MEA16 · 7.5 credits · Advanced level (A1N) · Medicinsk biologi
Bioinformatics for the Life Sciences
Active · next start HT 2026
56%
passed the latest ordinary exam
EXAM · 3 Dec 2025 · 16 students
73%
passed the ordinary exams, all sittings over the last 5 years
EXAM · 48 students
Unusually hard in 2025/26
56% passed the ordinary exam in 2025/26 (16 students), against 79% on average in earlier years (32 students).
Part of 1 programme
Exam
EXAM Written Exam
- VG
- G
- U
Ordinary exams
73% passed · 48 students
- 56%16
- 83%24
- 75%8
Re-exams
60% passed · 5 students
- 60%5
- Pass the re-exam: 60% (5 students), compared with 73% (48 students) on the ordinary exam
- Get VG: 26% (53 students)
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%3
- 0%1
- 100%3
- 100%2
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
UPG1 Individual assignment
- G
Main rounds
100% passed · 6 students
- 100%6
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%1
- 100%1
Other module
GRU1 Group assignment
- G
Main rounds
100% passed · 41 students
- 100%16
- 100%25
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%1
- 100%2
Other module
IDU1 Individual assignment
- G
Main rounds
100% passed · 38 students
- 100%12
- 100%26
Later rounds
No sittings with at least 5 students.
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%1
Other module
GRP1 Group assignment
- G
Main rounds
100% passed · 7 students
- 100%7
Later rounds
No sittings with at least 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%1
About the course
Aim
By the end of the course the student will be able to:
Knowledge and understanding
- Identify suitable bioinformatics tools for specific high-throughput biomedical analyses
- Justify the need for the reproducibility of scientific computational analysis
Competence and skills
- Use command-line interfaces (CLI) to work on a remote high-performance computer cluster (HPC)
- Produce clean, transparent and reproducible code taking into consideration the good practices for data analysis
- Apply common bioinformatic methods and workflows to specific biomedical data analyses
Judgement and approach
- Critically interpret the results obtained through computational analysis
- Choose and apply the most appropriate data analysis approach for a specific NGS dataset and assess the weakness and strengths of the approach
Content
Modern technical progress in biomedicine has led to the generation of large amounts of data and this has placed far-reaching demands on high data analysis capacity and requires formalized analysis workflows. This data-driven approach is a growing discipline in the life sciences.
Students will apply commonly used bioinformatic tools for the analysis of next-generation sequencing (NGS) data relevant to biomedicine, including for example sequence quality control, quantification of gene expression, detection of genetic variants or metagenomics. In addition, the students will learn how to work with analysis pipelines and document their own code in an efficient and reproducible manner.
The course includes:
- Remote high-performance cluster use
- Good practices in coding and documentation
- NGS data formats and Quality Control
- Differential gene expression
- Metagenomics
- DNA methylation and epigenetics
- Examiner
- Peter Wilhelmsson
- Main field of study
- Medicinsk biologi