Genetic Analysis BIOR92
7,5 credits
The general aim of the course is that students on completion of the course should have developed a population genetic way of thinking and use this to plan and perform genetic analyses, including analyses of results from population genetics research.
The course is renewed and is offered for the first time in the new form spring term 2023.
Course description
Central for the course is population genetic theory and its applications. The course focuses on the gene, family and population level. The course consists of different components including inheritance analyses of cross breeding and pedigree-data, use and properties of genetic markers and sequence data, non-Mendelian inheritance and epigenetic phenomena, basic linkage analyses and mapping, quantitative genetics and analysis of complex properties, classical population genetics and evolution of genetic and reproductive systems. Basic mathematical computing models will be used and discussed. Applications in medical genetics, plant breeding and evolution will be highlighted and discussed.
Teaching consists of lectures, multi-media material, computation exercises, computer exercises, group work, written assignments, seminars, project work, literature project and presentation. Compulsory participation is required in exercises, written assignments, project work and associated elements.
The assessment is based on the written examination at the end of the course, written assignments during the course and through compulsory components. Students who do not pass an assessment will be offered another opportunity for assessment soon thereafter.
Spring period 2a
Full-time, on campus, in English
Application
Course literature, 2024
An Introduction to Genetic Analysis, 12th ed., Griffiths et. al. (2020). W. H. Freeman & Co
Schedule
TBA
Evaluation
You find the latest evaluation on our web page with course evaluations.
Note that the course will be given for the first time spring 2023.
Questions?
Christina Ledje, study advisor, molecular biology
Telephone: +46 46 222 73 16
Email: molbiol_master [at] biol [dot] lu [dot] se