CS 481 Bioinformatics Algorithms
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This course is intended for advanced undergraduates who are interested in learning fundamental methods related to problems in bioinformatics. Some background in algorithms and data structures is required. We will start with algorithms for biomolecular sequence analysis, in particular the Needleman/Wunsch global alignment algorithm, the Smith/Waterman local alignment, pattern matching algorithms and sequence similarity search data structures. We will then move to multiple sequence similarity and alignment, phylogenetic trees, in particular distance based hierarchical clustering and protein and genome sequence database search. We will also talk about the structure of the human genome, genome repeats and problems related to genome sequencing and assembly. We will then move to structural bioinformatics, in particular, the RNA secondary structure prediction problem, and talk about the thermodynamic model. We will also briefly mention problems in systems biology. The computational techniques that will be emphasized include dynamic programming, learning algorithms and in particular those related to Hidden Markov Models, approximation algorithms especially for clustering problems and randomized algorithms and heuristics. Grading will be based on a number of theoretical and practical assignments in addition to one midterm examination and one final exam.
Credit units: 3 ECTS Credit units: .
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