834313 Phylogenetic principles in genetic and genomic analysis
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- Lecture and exercise
- Semester hours
- Lecturer (assistant)
- Meimberg, Harald , Cardoso Curto, Manuel Antonio
- Offered in
- Wintersemester 2022/23
- Languages of instruction
Attention: This course will be offered online in winter term 2020.
This course will provide an introduction to phylogenetics analysis using DNA data covering methodologies encompassing both traditional analytical tools and the latest state of the art phylogenomic analysis.
More specifically the course will cover the following topics: introduction to phylogenetics analysis concepts; introduction to sequence technologies; the use sequence data for phylogenetics; different phylogenetic inference methodologies such as parsimony, maximum likelihood, and bayesian approaches; the application of the latest sequencing technologies in phylogenetics and how they contributed to the appearance of phylogenomic; and the latest phylogenomic approaches where concepts such as introgression, coalescent theory, and species tree will be covered.
- Previous knowledge expected
Basic evolutionary biology and genetic knowledge
- Objective (expected results of study and acquired competences)
The class will provide the basic principles of DNA sequence analysis for phylogenetics and genomics.
The students will apprehend the analysis principles for data generation, its assembly and pairwise comparison and properties of different methods. They will know the differences between sequence and codominant datasets and their properties and will be able to decide analysis method in dependance of different datasets. This is the prerequisite to apply the procedures to the different relevant research fields, like animal and plant breeding, biotechnology and conservatoion genetics. In particular the class introduces analysis of high through put genome wide sequence or SNP datasets which will be presented as exercise.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.