Introduction to Bioinformatics

MBG 326 is where molecular biology meets the command line: you learn to treat sequences, expression matrices, and genomes as data you can actually query, align, and model rather than just memorize. Most of the work happens in R — weekly labs and five homeworks walk you through tidyverse, ggplot2, clustering, PCA, and eventually a full RNA-seq project, scaffolded by Akalin's Computational Genomics with R. It's the course that turns the wet-lab intuition from earlier MBG classes into the computational fluency you'll need for genomics electives, thesis work, or anything downstream of a sequencer.