University of Washington Pathobiology 536 Taught by David Sherman, Shuyi Ma, and Tige Rustad With guest lectures by Andrew Gustin, Fred Mast, Bart Staker, and Sandhya Subramanian [Add TAs, guest lecturers, etc]

The goal of this class is to introduce students to a set of bioinformatic tools to further their future research. The first section of the class will introduce the basics of Github, python, and several python libraries for data handling, analysis, and presentation. We will then focus on tools for analyzing sequence data, with an emphasis on RNAseq analysis. We will take the resulting data into the next class, where we will cover various ways of describing data using networks. The last classes will cover bioinformatic approaches to dealing with the added complexity of proteins. We will wrap up the course with a self guided project, where students use the tools from this class to solve a reasonable problem of interest to them or their lab.

This repository will hold Jupyter notebooks for some classes, small datasets for practice, and some homework assignments.

If you would like to try any of these notebooks in your browser you can launch this repository through MyBinder.org by clicking this button: