Caporaso Lab Teaching Website

Current courses (Spring 2018)

An Introduction to Applied Bioinformatics (IAB)

Dr. Caporaso’s interactive, IPython Notebook-based introductory bioinformatics text, An Introduction to Applied Bioinformatics, is available for free here. For more information see Dr. Caporaso’s microbe.net blog post on IAB and the IAB website.

Caporaso Lab Office Hours

All lab member office hours are open to the public. These are held in ARD 220.

Bioinformatics @ Northern Arizona University

There is not an undergraduate or graduate bioinformatics program at NAU, but there are some courses that will start to prepare you for a career in bioinformatics. Biology, Computer Science and Statistics are the most relevant undergraduate degrees. If you’re interested in a graduate degree, you may want to do that in the Biology Department. or in the School of Informatics, Computing and Cybersystems. You would then work with a faculty member whose research is bioinformatics-heavy, and they would guide you toward relevant coursework.

BIO 450/CS 499 Fundamentals of Bioinformatics (three credits)

This course covers fundamental concepts in bioinformatics, method and tool benchmarking, and in depth coverage of several specific high-interest topics. This course was previously taught under various different course numbers between 2011 and 2017 as it went through a few design iterations.

You do not need to know how to program to take this course!

For students who are looking to get a head-start on the material, I recommend An Introduction to Applied Bioinformatics and the materials in my resources section below.

CS 499 counts as a Technical Elective for Computer Science and Applied Computer Science degree programs. BIO 450 counts as a major elective for the Biology degree programs.

This course is generally taught every Spring semester.

Independent research

Instructor: Dr. Greg Caporaso (gregcaporaso@gmail.com)

I occasionally mentor exceptional undergraduate and graduate students in bioinformatics-related research projects. If you’re interested in this, contact me with details about the type of project you’d like to work on, and about your educational background. These are considerably harder than a single semester course in bioinformatics, and require you to be highly self-motivated. I do not accept all students who are interested.

Resources for getting started with bioinformatics and Python

See the IAB reading list for resources for getting started in bioinformatics.