Algorithms in computational genomics 1000-2M12AGO
1. Introduction. Elementary defintions, genes, species, genomes, ewolution, alignments, sequence comparison (2 lectures).
2. Models of sequence evolution (1).
3. Maximum likelihood estimation, maximum parsimony, nearest neighbor joining (2)
4. Bayes methods (1-2)
5. Consesus trees and supertrees (2)
6. Hierarchical clustering (1)
7. Reconciled trees, networks, horizontal transfer (2-3).
8. Suffix trees, suffix arrays (1-2).
Założenia Basics of algorithmics, programming skills (e.g. python, c/c++ or java)
Type of course
Learning outcomes
Has knowledge on advanced methods from comparative genomics (K_W04)
can perform computations related to genome comparison and can interpret their results (K_U07)
Assessment criteria
Exam 60% + compulsory lab project 35% + project presentation 5%.
Bibliography
1. Inferring Phylogenies Joseph Felsenstein
2. Paul G. Higgs, Teresa K. Attwood, Bioinformatyka i ewolucja molekularna,
3. R. Durbin, S. Eddy, A. Krogh, G. Mitchson, Biological Sequence Analysis, .
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: