Bioinformatics - Michaelmas 2013
Lecturer: Dr P. Lio'
Lecture Theatre 2, WGB
News
Content
Introduction to biological data: Bioinformatics as an interesting field in computer science.
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
Lectures
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Reading
Jones, Pevzner Introduction to Bioinformatics algorithms, MIT Press
Material/links
Programming: Matlab: http://www.mathworks.com/products/bioinfo/
Past exam papers