This course introduces algorithms, statistical methods and data analysis programming routines relevant for genome biology. It consists of three main components: lectures, hands-on practicals and student course projects. The lecture topics cover databases, sequence (NGS) analysis, phylogenetics, comparative genomics, genome-wide profiling methods, network biology and more. The hands-on practicals include homework assignments and course projects focusing on data analysis programming of next generation genome data using command-line tools on a computer cluster and the programming environment R. Depending on student interests, one or more specialty topics may be included, such as the analysis of single cell (e.g. scRNA-Seq) experiments, multi-omics data, or the development of web-based analysis tools (e.g. Shiny Apps).
Who should take this class?
Students with a strong interest and motivation in acquiring the skills required for mastering the computational aspects of modern genome research. The class is mainly targeting graduate students but senior undergraduate students are welcome to enroll as well. The main audience of this class are usually students from bioscience, biomedical and bioengineering programs as well as CS and statistics students with interest in computational biology.
Can I audit this class?
It is possible to audit this class. However, due to the emphasis on active participation in practicals and course projects, students usually learn much more if they enroll into the class rather than auditing it in a passive manner.