1. To introduce main bioinformatics methods, primarily sequence analysis methods and series of associated techniques,
2. The focus of the course will mainly be on algorithmic and computational aspects of the subject, while being aware of the statistical and mathematical background,
3. It is intended that the course serves as a preparation for studying real-life problems in biology and medicine, especially proteomics and genomics.
1. biological sequences,
2. pairwise alignment: mutation and substitution matrices, local and global alignment, dynamic programming; posterior probabilities, extreme value distributions,
3. introduction to hidden Markov models: Viterbi, forward and backward algorithms, posterior decoding; model optimization, EM-algorithm, Viterbi training.