Modeling and Inference in Computational Genomics

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COMP 382 or STAT 310 Description: The course addresses several problems in computational genomics including, but not limited to, sequence alignment, phylogeny reconstruction, phylogenomics, cancer genomics, and viral phylodynamics. In addition to learning about these biological problems, the course emphasizes the mathematical approaches used to formulate these problems mathematically and the algorithmic techniques used to solve them. For mathematical modeling, the students will be introduced to hypothesis testing, probabilistic graphical models, graph theory, and more. For inference, the students will be introduced to combinatorial optimization, maximum likelihood estimation, Bayesian Markov chain Monte Carlo, and more. This is a course about computational problem solving, with genomics being the domain from which we draw problems, rather than a course about using bioinformatics tools. Graduate/Undergraduate Equivalency: COMP 571 . Mutually Exclusive: Cannot register for COMP 471 if student has credit for COMP 571→COMP 471→unlocks 0 courses

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