Examination arrangement

Course content

Applied bioinformatics builds on biochemistry and cell biology, and connects biology with informatics. The course teaches how biological data can be studied using computer tools. The course basically starts with learning more about bioinformatics databases such as HGNC, EMBL, UniPRot and NCBI. The course deals with what information one finds in the databases and how to use databases to find information for the development of new analytical methods, new medicines or epidemiological investigations. In addition, it is a walkthrough with simple application of excel to structure data, understand file format, plain text versus text with formatting, calculations such as statistics and practical skills that are useful for a working day at the interface between humans and machines. The main goal has been to make the students confident that they can master a digital world and understand that biological data, word processing have their limitations and sources of error. Furthermore, the course covers simple bioinformatics tools such as sequence extractor, in silico PCR analyzes, Primer BLAST, Allignment by Clustal W, BLAST search and prediction tools to study mutations. The focus in this section is analysis of biological data from human experiments, and look at the link between molecular biology, laboratory analyzes and bioinformatics tools to better understand the concept of personalized medicine. The course also covers more about molecular biology analysis methods that generate data for bioinformatics analyzes, and one looks more at genetics, mutations and genotyping based on a selection of molecular biology analysis methods (PCR, electrophoresis, sequencing). The course also uses programs to analyze sequence data and MEGA - molecular evolutionary genetics analysis is used for various phylogenetic studies - with the main focus on prokaryotes.

Learning outcome

Knowledge - the student:

• have basic knowledge of bioinformatics tools
• understands how different bioinformatics tools can be used for nucleotide analyzes
• knowledge of the bioinformatics methods used in molecular biology
• understands how genomes are built and what properties genomes have
• can explain how the genomes are expressed and how gene expression can be regulated
• have knowledge of how bioinformatics can contribute to development in personalized medicine

Skills - the student:

• are able to use bioinformatics tools to analyze nucleotide sequences
• are able to search and find information in databases
• can analyze relevant biological data using bioinformatics tools

Competence the student:

• can discuss at a basic academic level with others within the subject area
• have a basic understanding of the opportunities that exist in the field
• can apply relevant analysis techniques, methods and digital tools
• are able to contribute to solving many of the challenges society has within diagnostics, research and development work
• are be able to work effectively to solve specific problems and find relevant information from available databases within given resource framework conditions, either in the laboratory or in research
• are be able to collaborate well with others with different skills, backgrounds and characteristics
• are be able to contribute constructively in teams and work environments with different forms of diversity in order to achieve common goals and solve challenges that require collaboration across areas of knowledge

Learning methods and activities

Pedagogical methods: Lectures with compulsory computer exercises up to 5 x 4 hours, 4 x compulsory assignments, lectures up to 10 x 2 hours, The student's own contribution to the course is estimated to be 200 hours, of which up to 70 hours are organized activities. Mandatory work requirements: Compulsory participation in computer exercises and lab courses, Approved submissions.

Compulsory assignments

• Mandatory assignment

Further on evaluation

1 week written home exam

Specific conditions

Recommended previous knowledge

HBIOA1003 Biochemistry with cell biology

Credit reductions