Advanced Topics in Bioinformatics

Course content

The course covers advanced topics in Bioinformatics. The course is based mostly on scientific papers and texts. The topics include

  • The Bayesian view of probability and its history, foundations and applications
  • The Bayesian probability calculus and its approximations
  • Analyzing high throughput sequencing of nuclear DNA
    • Mapping algorithms
    • How to analyze next generation sequencing (NGS) data with a focus on how to deal with the uncertainty of the data in order to perform population genetic and medical genetic analysis
  • Assembly of genomes and transcripts
  • Other topics relating to high-throughput DNA sequencing
Education

MSc Programme in Bioinformatics
MSc Programme in Biochemistry

Learning outcome

Knowledge:

The student will know and understand the main methods used in the course. More specifically, the student will obtain knowledge of

  • Fundamentals of Bayesian statistics
  • Analysis of high-throughput sequencing data
  • Genome and transcriptome assembly


Skills:

The student will be able to

  • Do the types of data analyses covered in the course
  • Interpret results of such analyses in a biological context
  • Explain the methods covered in the course
  • Select the appropriate methods and tools for a given problem covered in the course


Competences:

The student will obtain or improve these general competences

  • Will be able to discuss and explain methods in bioinformatics with researchers in bioinformatics and related sciences
  • Will be able to contribute to interdisciplinary projects involving biological sequence analysis
  • Will be able to read, understand, and discuss scientific literature in bioinformatics

Lectures and exercises (7 hours per week), and homework (4 in total).

See Absalon.

Competencies corresponding to 3 out of 4 of the mandatory courses in the bioinformatics graduate programme or equivalent.

The course is prepared for the bioinformatics graduate programme, but it is open to third year BSc students and MSc students in general.

ECTS
7,5 ECTS
Type of assessment
Continuous assessment
Mandatory homework assignments. Grade based on the average number of points obtained in the assignments.
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

In order to achieve the grade 12 the student must be able to demonstrate an excellent fulfilment of the learning outcome described above.

Single subject courses (day)

  • Category
  • Hours
  • Exam
  • 20
  • Preparation
  • 122
  • Lectures
  • 40
  • Practical exercises
  • 24
  • English
  • 206