Computational Approaches for Microbial Systems

3.0 credits · Undergraduate

High-throughput sequencing has revolutionized and become common practice across the field of microbiology. This course will prepare students for analyzing large sequencing datasets through a meaningful biological lens. Via a combination of lectures, discussions of primary literature, and hands-on, data-driven computational labs, we will learn how to organize computational projects, work in the command line, perform cloud computing, and gather, interpret, and analyze amplicon and (meta)genomic data to advance our understanding of microbial systems. We will evaluate the distribution of microbial biodiversity and gene abundances and compare the taxonomic and genomic composition of microbial communities. This course is geared towards graduate students and upper-level undergraduate students across biology. We will focus on how to use software for biological analyses while touching on broader concepts of statistical algorithms. (Note: the specifics of statistical models will not be the focus.)