Algorithms and Data Structures in Bioinformatics (3) This course covers elegant algorithmic and data structure techniques that underpin modern biological data analysis.
CSE 566 Algorithms and Data Structures in Bioinformatics (3)
Bioinformatics is a growing field with immediate implications for our understanding of biology and treatment of disease. This course covers elegant algorithmic and data structure techniques and their use in bioinformatics. The emphasis is on recurrent ideas that underpin modern biological data analysis, presented in conjunction with their biological applications. The course is suitable both for students interested in doing bioinformatics research and those interested in applications of algorithms to the natural sciences.
Some of the algorithms/data-structures that may be covered include exact string matching, suffix trees, suffix arrays, de Bruijn graphs, hidden Markov models, breakpoint graphs, succinct data structures, the Burrows-Wheeler transform, the FM-index, network flow, and bidirected graphs. Some of the biological applications will include sequence alignment and assembly, cancer genomics, phylogeny, gene finding, and variation detection.
No prior biological or bioinformatics knowledge is required. A basic understanding of data structures and algorithms (equivalent to CMPSC465) is a prerequisite; however, exceptionally motivated students can contact the instructor to discuss their options. This course is complementary to existing bioinformatics courses offered through other programs on campus. These courses may be taken concurrently but are not prerequisites.
Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.