Computational Methods in Genomics and Genetics

Catalog description

This course covers computational methods applied to genomics and genetics. The course will cover Bayesian statistics, nonparametric inference, phylogenetic trees, sequence analysis, microarray analysis, networks, multivariate methods, linkage analysis, and association genetics. The focus of the course will be to understand the basic concepts underlying the various analyses used in modern genomic and genetic research, and to understand how to use software that is available for basic analyses. A large component of the course will be to provide students with hands-on experience with analysis of datasets. Lecture Hours: 3 Lab Hours: 1 Repeatability: May not be repeated for credit. Grade Mode: Normal Schedule Type (Primary): Lecture/Supervised Lab/Clinic Click here for the Schedule of Classes.