Entry requirements

60 credits within the Master's Programme in Molecular Biotechnology Engineering including Introductory Organic Chemistry and Probability and Statistics. Participation in Structural Bioinformatics of which 2 credits should be completed, and participation in Database Design I and Computer Programming II.

Learning outcomes

On completion of the course, the student should be able to:

• describe the function of the genome in humans and model organisms
• explain the principles of alignment, pattern recognition in sequences and phylogenetic analysis
• account for methods for studying genomes, such as microarray analysis, association study (GWAS), sequencing genomes and transcriptomes, and evaluate the quality fo data from such studies
• describe methods to modify genomes (e.g. with CRISPR) and briefly describe methods for studying proteomes and metabolomes
• design strategies to bioinformatically and/or experimentally address given biological and biomedical questions with methodology treated during the course, and compile, analyse and evaluate the results of such experiments
• describe and evaluate how progress in research have commercial and ethical consequences for society by the development of genomics and bioinformatics.

Content

The course discusses theories about the genome structure with focus on the human genome. How genomes, transcriptomes, proteomes and metabolomes relate to and regulate each other. Genome variation and their importance for phenotype variation and diseases. Modern large-scale methods for analyses in these fields are presented, including how large-scale platforms function logistically and how the quality of the processes is guaranteed. Among the technologies that are discussed, 'inter alia sequence' is included, as well as hybridisation technology for genome and transcriptome analysis and proteome and metabolome analysis.

The course also deals with bioinformatics with focus on sequence data including public bioinformatic databases, their design and search tools; Identification of coding sequences; Pair-wise and multiple sequence alignment; Heuristic methods for sequence alignment (e.g. BLAST); Methods for pattern recognition in sequences (e.g. identification of the promotors); Methods for phylogenetic analysis; Automation of bioinformatic analyses by means of script programming.

Furthermore, strategies for ways to utilise experimental technologies to find and examine the importance of genome variation for diseases, and strategies for bioinformatically solving given biological problems by identifying and using appropriate public databases in combination with existing software.

The course also addresses how progress in bioinformatics, genomics, functional genomics and systems biology has reserach, commercial and ethical consequences for society.

Instruction

Lectures, seminars, and computer exercises.

Assessment

Written exam (5 credits), reports on computer exercises (3 credits), seminars and written assignments (2 credits).

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.