Jane Synnergren
Professor of BioInformatics
School of Bioscience
Bioinformatics Analysis with R A1N
Course, Master's (2nd cycle),
7.5 credits,
BI731A
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: 30 March 2026 - 7 June 2026
Location: Skövde, Campus, Daytime
Pace of study: 50%
Admission Requirements
Entry requirements higher education not set. (or the equivalent). The course has the following entry requirements: a total of at least 90 passed credits in one or some of the subjects of Biology, Medicine or Computer Science. Of these 90 credits, at least 15 credits must be on the level of progression G2F (or the equivalent).An additional 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. 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.
R is today a standard tool in bioinformatics for working professionally with data analysis, machine learning and AI-based applications.
A continuing challenge within bioinformatics is to integrate and analyze large amounts of data from different large-scale experiments (for example proteomics, genomics and metabolomics). This course introduces the programming language R to efficiently solve various bioinformatics problems. You will learn the basics in R such as data types, functions, statistics and visualization, and in an advanced way apply the knowledge on various types of data. We examine how the experimental design can influence results and introduce various normalization methods. Within bioinformatics, R can be applied in many ways from identification of new cancer specific genes to analyze metabolite changes caused by drug treatment.
