Master’s studies

Syllabus for Genome Analysis

Genomanalys

Syllabus

  • 10 credits
  • Course code: 1MB462
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Technology A1F, Bioinformatics A1F
  • Grading system: Fail (U), 3, 4, 5.
  • Established: 2017-03-07
  • Established by: The Faculty Board of Science and Technology
  • Applies from: week 27, 2017
  • Entry requirements: 120 hp. Molecular Evolution, Script programming
  • Responsible department: Biology Education Centre

Learning outcomes

After passing the course the student should be able to

  • assemble raw sequence data to genome sequences and/or align them to existing reference genomes
  • analyse genome sequence data with regard to e.g. gene expressions, functional genomics, genome evolution and variation in populations
  • choose as well as apply methods in comparative genomics to analyse and draw conclusions about the biology and evolution of organisms
  • choose sequence technology and apply existing software for given biological problems in the area
  • critically analyse, evaluate and compile achieved results of genome analyses
  • discuss and present social, ethical and scientific aspects of genomics.

Content

The course covers bioinformatics with a focus on analysis of genome sequence datasets, and contains the following components and aspects: Methods for large-scale sequencing and its different applications. Assembly of raw sequence data to complete genomes. Mapping of raw sequence data to existing reference genomes. Principles for annotation of genes and other biological information, annotation system, the problems with automatic annotation. Bioinformatic aspects on different methods to study the function, variation and evolution using large-scale sequencing of the genome. Bioinformatic aspects of metagenomics.

Instruction

Lectures, seminars and computer exercises.

Assessment

Written examination (5 credits). Participation in at least 80% of the seminars and presentation of computer exercises (5 credits).

Reading list

Applies from: week 27, 2017

Scientific articles will be used during the course.