NBIA09043U Population Genetics
MSc Programme in Bioinformatics
MSc Programme in Biology
MSc Programme in Biology-Biotechnology
The amount of molecular genetic data (especially nucleotide sequences) has increased tremendously in recent years and is expected to explode as the next generation sequencing methods become standard tools. This has implications for a wide spectrum of biological disciplines spanning conservation genetics, molecular ecology, molecular medicine, genome research and evolutionary biology. The purpose of the course is to provide the students with knowledge about the principles of population genetics and phylogenetics and their applications in the diverse areas mentioned above. In addition, the course will train the students to choose suitable methods to analyze molecular genetic data.
Students with a limited background in bioinformatics will be offered additoinal exercises in bioinformatics skills necessary to handle the large amount of genomic data that are available today. This includes an introduction to the operating system Linux and the R environment for statistical computing.
Knowledge:
By completing the course the student has been introduced to
- Natural selection
- Genetic drift and inbreeding
- The neutral theory and molecular population genetics
- Population structure
- Evolutionary quantitative genetics
- Phylogenetic inference (using distance, parsimony, maximum likelihood, and Bayesian methods)
- Population genomics
- Human population genetics
- Applied aspects; depending on the participants’ interests
Skills:
By completing the course the student has learned how to analyse population genetic data and to explain how they have been influenced by:
- Natural selection
- Genetic drift and inbreeding
- Population structure
- Mutation
The student has obtained skills within the disciplines
- Evolutionary quantitative genetics
- Phylogenetic inference (using distance, parsimony, maximum likelihood, and Bayesian methods)
- Population genomics
- Human population genetics
and will be able to communicate in writing the results of an
analysis of a selected topic within the subject field.
Competences:
By completing the course the student can:
- employ basic population genetic and phylogenetic principles
- discuss, put into perspective, and criticize original research papers in population genetics and phylogenetics
- choose the most suitable molecular methods to analyze a particular hypothesis
- choose the most suitable analytical tools to analyze molecular genetic data
- perform bioinformatics and statistical analyses of population genetic and phylogenetic data, present the results, and put them into perspective
See Absalon.
- Category
- Hours
- Exam
- 16
- Lectures
- 27
- Preparation
- 81
- Project work
- 55
- Theory exercises
- 27
- Total
- 206
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentOral defence, 20 min.Written assignment: The student must analyse population genetic data sets and write a scientific paper of about 10 pages. The written assignment must be handed in in the exam week.
Oral defence: The student presents the paper that has been handed in.
50:50 weight of the paper and oral exam - Marking scale
- 7-point grading scale
- Censorship form
- External censorship
- Re-exam
- If the written assignment is not handed in prior to ordinary exam, it can be handed in before the reexamination by agreement with the teacher.
Criteria for exam assesment
The grade 12 is used when the student has an exhaustive knowledge about how to analyse population genetic data and to explain comprehensively how they have been influenced by various evolutionary forces.
Course information
- Language
- English
- Course code
- NBIA09043U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 3
- Schedule
- C
- Continuing and further education
- Study board
- Study Board of Biomolecular Sciences and Technology
Contracting department
- Department of Biology
Course responsibles
- Hans Redlef Siegismund (11-4b566c686a6c767078716743656c72316e7831676e)
Lecturers
Rasmus Heller, Søren Rosendahl