Content of the Lecture Notes
Basic concepts in Genetics and Genomics.
Dynamic programming. Longest common subsequence, DNA, RNA, protein structure alignment, linear space alignment, heuristics for multiple alignment.
Sequence database search. Blast, Patternhunter.
Next Generation Sequencing. De Bruijn graph, Burrows–Wheeler transform.
Phylogeny - parsimony-based. Fitch, Wagner, Sankoff parsimony.
Phylogeny - distance-based. UPGMA, Neighbour Joining.
Clustering. K-means, Markov Clustering algorithm.
Applications of Hidden Markov Models.
Searching motifs in sequence alignment. Gibbs sampling.
Biological networks: reverse engineering algorithms and dynamics; Wagner, Gillespie.
Example Questions and answers
1 slides/page colour (see note below)