Instructor: Carlos Aguilar, Ph.D.
The dramatic reductions in cost and accessibility of next-generation sequencing technologies has facilitated new approaches to understand disease and cellular biology. Understanding how to read sequencing datasets is not only incredibly useful for researchers seeking to glean insights into their own experiments but also the capacity to generate data-driven hypotheses. The overarching goal of this class is to develop an understanding of foundational methods in bioinformatics to enable engineering students to process, contextualize and visualize basic high-throughput sequencing experiments with a focus on RNA and gene expression.
Prerequisites: This class requires programming experience and some background in biology (Introductory Biology course). The object-oriented language Python and the Bioconductor package within R will be utilized. If possible, students should try to bring a laptop to participate in class. Laptops generally require 8 GB of RAM to run some of the programs.