CTS505

042764

This course is designed as an introduction to bioinformatics principles, algorithms, and their application to hypothesis-driven, basic and translational research. The course covers important protein and nucleotide alignment algorithms, such as BLAST and Smith-Waterman, crucial public databases, RNA biology, and different approaches for DNA and RNA sequencing. We will introduce important concepts, such as differential gene expression, functional enrichment analysis, genome assembly, and gene finding. The open-source statistical computing language R, employed for many bioinformatics analyses, will be covered, together with an introduction to Linux-based operating systems used in high performance computing (HPC) environments to enable students to perform their own analyses on HPC systems as well as on their own laptops.

GRD - Regular Grades A, B, C, D, E

Graduate

Ability to use a statistical computing package (such as R).