Many elegant computational problems arise naturally in the modern study of molecular biology. This course is an introduction to the design, implementation, and analysis of algorithms with applications in genomics. Topics include bioinformatic algorithms for dynamic programming, tree-building, clustering, hidden Markov models, expectation maximization, Gibbs sampling, and stochastic context-free grammars. Topics will be studied in the context of analyzing DNA sequences and other sources of biological data. Applications include sequence alignment, gene-finding, structure prediction, motif and pattern searches, and phylogenetic inference. Course projects will involve significant computer programming in Java. No biology background is expected.
Max Enrollment: 18
Prerequisites: CS 230 or permission of the instructor.
Distribution Requirements: MM - Mathematical Modeling and Problem Solving
Typical Periods Offered: Every other year
Semesters Offered this Academic Year: Spring