Computing for Data-Driven Biology, 7.5 credits

Contents

The course introduces working on the command line and in Linux, with a focus on file systems, essential command-line tools and file formats used in bioinformatics. Students gain an overview of major biological databases and practical strategies for retrieving, analysing, and processing data. The course also covers the foundations of reproducible and FAIR bioinformatics, including version control, environment and container technologies, and construction of workflows and pipelines in HPC environments.

Expected learning outcomes

Knowledge and understanding

After completing the course, the student should be able to:
1. Understand fundamental concepts for working on the command line and be familiar with common command-line tools.
2. Understand file system structures and management.
3. Describe principles of reproducible and FAIR bioinformatics.
4. Explain common bioinformatics file formats and their applications.
5. Identify key biological databases and how to query them.
6. Describe core components of workflows and HPC environments.

Skills and abilities
The student should be able to:

7. Select and apply appropriate command-line tools to extract information and perform routine operations on common bioinformatics file formats.
8. Execute file system administration tasks.
9. Conduct routine file parsing and QC in Linux.
10. Run and monitor jobs on HPC systems with schedulers.
11. Build a reproducible workflow using environment managers or containers.
12. Use Git for version control.

Judgement and approach
The student should be able to:

13. Evaluate reproducibility and data governance in large-scale analyses.

Required Knowledge

General entry requirements and Biology 2/level 2, Chemistry 1/level 1, Mathematics 3c Mathematics Further level 1c or Mathematics D

Form of instruction

Teaching consists of lectures, supervised exercises and computer-based practicals. Lectures introduce theoretical foundations of command-line tools, file formats, databases, workflows, version control and HPC environments. Through practical exercises, students apply these concepts in tasks relevant to bioinformatics workflows.
Teaching is normally in English but may be given in Swedish if there is no need for English. Each student must have access to a personal computer with internet connectivity and the ability to install required software.

Examination modes

The following assessments are conducted and graded U, G, or VG:
1. Individual practical assignments assessing outcomes (ILOs 7–12).
2. Group code review assessing outcome (ILO 13).
3. Individual written essay on FAIR/reproducibility assessing outcomes (ILOs 1–6).
To pass the course (grade G), all assessments must be passed. To receive VG, all assessments must be passed and at least two must be graded VG.
Students who fail an assessment are entitled to a re-examination. The first re-exam must be offered within two months of the original exam, but not earlier than ten working days after results are announced. For exams held in May or June, the first re-exam may be offered within three months. At least one additional re-exam must be offered within one year.
Students who have passed an exam may not retake it for a higher grade.
A student who has failed an exam twice is entitled to request a different examiner, unless special reasons oppose it (Higher Education Ordinance, Chapter 6, Section 22). Requests should be submitted to the Head of the Department of Plant Physiology.
The examiner may allow deviations from the examination format. Individual adaptation must be considered based on student needs and within the expected learning outcomes. Students with formal decisions on support due to disabilities must request adapted examination at least ten working days before the exam.

Transitional provisions

If the course syllabus is discontinued or significantly revised, students are guaranteed at least three examination opportunities (including the original) according to the original syllabus for up to two years after the change.