Week |
Course Content |
Week 1 |
Some basic principles. Artificial and natural classifications. Reconstructing phylogenies. Different kinds of evidences used in systematics. Morphological evidence: homology and its criteria. Trait evolution, divergent and convergent evolution, parallelism. Plesiomorphic and advanced characters. Homoplasy. Higher taxonomic categories, basis for their recognition, ranking. Monophyletic and non-monophyletic taxa. Phenetics, cladistics. |
Week 2 |
An introduction to cladistics: basic concepts and terms. Taxonomic characters, their kinds and importance in the cladistic paradigm. Character coding, transformation series and ordering. Character state polarity and its determination, ordering character states. Handling missing data. Tree thinking. |
Week 3 |
Introduction to online resources and softwares of application in systematics. Getting familiar with softwares and file formats. Selecting and coding of characters, building a character matrix. |
Week 4 |
Constructing a cladogram from morphological datasets. Principle of parsimony in biology; finding the most parsimonious cladogram; exact and heuristic methods; parsimony versus likelihood. Weighting data. Character optimization. Performing simple searches, dealing with outputs, tree formats, simple tree manipulation, saving results; practice. |
Week 5 |
The quality of the cladogram. Measures of character fit: cladogram length, consistency index, retention index. A priori and a posteriori character weighting. Measures of support of individual clades, Bremer support, bootstrap, jackknife. |
Week 6 |
Comparison of trees. Consensus trees. Understanding and interpreting cladograms, common misconceptions. Using trees to study character evolution. Testing hypotheses of adaptation. Ancestral reconstructions. |
Week 7 |
Further discussion and practice on selected concrete problems. |
Week 8 |
Mid-semester test. |
Week 9 |
Special features of molecular datasets, similarities and differences to morphological data. Acquiring sequences: databases and online resources. Getting familiar with softwares and file formats. Homology in molecular datasets. Sequence alignment. |
Week 10 |
Constructing a cladogram from molecular datasets. Basic features of nucleotide substitutions. Nucleotide substitution models. Distance-based methods. Neighbour-joining trees, their advantages and disadvantages. Chosing an evolutionary model. |
Week 11 |
Constructing a cladogram from molecular datasets. Basic features of nucleotide substitutions. Nucleotide substitution models. Parsimony analysis of molecular data, problems. Distance-based methods. Neighbour-joining trees, their advantages and disadvantages. Chosing an evolutionary model. |
Week 12 |
Maximum likelihood in theory and practice. Estimating support of clades of a molecular tree by bootstrapping. |
Week 13 |
Bayesian inference in theory and practice. |
Week 14 |
Combining different sources of data: simultaneous and partitioned analysis. Application of results in taxonomy: turning cladograms into formal classifications. Phylogenies and taxonomic ranks. Artifacts. Applications and case studies. Phylogenetic approaches to special problems (coevolution, biogeography). |
Week 15 |
Further practice, discussion of additional topics and interesting problems. |
Week 16 |
Student self-directed learning: analyzing data sets provided by instructor. |
Week 17 |
Student self-directed learning: analyzing data sets provided by instructor. |
Week 18 |
Final test. |