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Exam preparation (midterm exam).
The exam will take place on Fri, 13 June 2014, in Aula F, from 8.15 to 10.15. Please arrive a bit ahead of time and make sure you have identification (with photo) with you.
| Heuristics for sequence alignment |
Theoretical: What is a heuristic? Explain the underlying ideas of BLAST. What is the advantage over the DP-algorithms? What is the primary application? Why are heuristics used and not the DP-algorithms? Practical: Compute a dotplot for two sequences. Interpret a given dotplot. Find high-scoring w-words (= q-grams, seeds) as does BLAST (for given scoring scheme). |
| Descriptive Statistics |
Theoretical: What is the difference between descriptive statistics and inferential statistics? What is a sample? What is a population? Def. of sample and population mean, variance, standard deviation. Practical: Compute mean, median, mode, variance, standard deviation, percentiles, quartiles, IQR of a small data set (only simple examples that can be done without a calculator). Interpret example histograms, pie charts, bar charts, box plots. |
| Hypothesis testing |
Theoretical: What does null hypothesis mean? What is the p-value? What are type I and type II errors? What are the significance and power of a test? Practical: Define the null hypothesis for a given problem. Decide whether or not to reject the null hypothesis (given p-value and alpha). Compute the p-value using Z-statistic and the tables of the normal distribution (either one). |
| Graphs, trees, phylogenetic trees | Theoretical: How many ways are there to root a tree? How many edges does a tree on n nodes have? What is a phylogenetic tree? How many phylogenetic trees are there on a given set of taxa? What are the types of input data? Practical: Identify in a tree leaves, root, parent, sibling, child, ancestor, descendant of a node. Check whether two drawings depict the same phylogenetic tree (very small examples). Root unrooted trees. Identify whether a phylogenetic tree is rooted/unrooted, whether the branch lengths matter. |
| Character based data |
Theoretical: Def. of compatibility (of a character with a tree). Def. of Perfect Phylogeny. Does it always exist? Define/explain Small Parsimony and Large Parsimony. Which of these problems can be solved efficiently? Practical: Check whether a phylogenetic tree is a PP for a character-state matrix M. Compute the parsimony score of a given labelled tree. Apply Fitch's algorithm. |