Benjamin Ulfenborg
Senior Lecturer in BioInformatics
School of Bioscience
Bioinformatic Workflows for Large-Scale Sequencing Data A1N
Course, Master's (2nd cycle),
7.5 credits,
BI764A
Application
Choose a course instance to see course syllabus and admission requirements.
Spring 2026, Location: Skövde, Pace of study: 50%
Application
Application is done after nomination.
Course syllabus, with reading list
When? Where? How?
Study period: 19 January 2026 - 29 March 2026
Location: Skövde, Campus, Daytime
Pace of study: 50%
Admission Requirements
Entry requirements higher education not set. (or the equivalent). 150 approved higher education credits, of which a total of at
least 90 credits in one or more of the subjects biology, biomedicine or
computer science (or the equivalent). The biological field refers here to programs
with a bioinformatics, systems biology, molecular biology or microbiology
focus. Of these, at least 15 credits must be at level G2E (or the equivalent). Furthermore, courses of at least 7.5 credits in the subject bioinformatics,
7.5 credits in cell biology and 15 credits in programming (or the equivalent) are required. A further requirement is proof of skills in English equivalent of studies at upper secondary level in Sweden, known as the Swedish course English 6 or English level 2 (or the equivalent) is required. This is normally
demonstrated by means of an internationally recognized language test, e.g. IELTS
or TOEFL or the equivalent.
Selection
Guaranteed admission.
Language
The courses are conducted in English.
Want to take your bioinformatics to the next level? In this course, you'll learn how to build your own workflows, keep your code organized, and work in virtual environments to ensure everything works as it should. You'll also learn how to use computer clusters and cloud computing to run your analyses on truly powerful resources!
In this course, you will learn how to use powerful tools to analyze biological data, such as DNA sequences. You will create your own analysis flows, which are like recipes for processing data in a structured way, and ensure that they work every time by using virtual environments and version control. You will also gain practical experience running analyses on large computer clusters and cloud-based systems, which allows you to handle really heavy calculations without being dependent on a regular computer. This gives you both the technical knowledge and understanding to be able to tackle the big biological questions in today's research world.
