Applied Genomics

Catalog description

This course introduces fundamental methods of analyzing large data sets from genomics experiments. Through a combination of lectures, hands-on computational training, and in-depth discussions of current scientific papers, students learn the conceptual foundations of basic analytical methods, the computational skills to implement these methods, and the reasoning skills to read critically the primary literature in genomics. Analysis focuses on data from genome-wide studies of gene expression using microarrays and from genome-wide studies of molecular interactions. Methods covered include clustering, multiple-hypothesis testing, and network inference. A large part of the course is dedicated to students completing an individual project that is tailored to meet their background and training.