Teaching

BIOL 3000 - Genetics

In spring semesters, I teach the large introductory genetics course that is a required course for all majors in Biology. I team-teach this course with colleagues, including Dr. Rita Graze and Dr. Brian Counterman. We use a mix of traditional lecture format and active learning activities to help students build a strong foundation in the principles of genetics. We place a strong emphasis on explaining the experiments that led to our current knowledge of heredity. We also cover advanced topics in genetics such as genomics, cancer biology, and genetic engineering.

Honors Contract for Genetics 

Based on a New York Times article, I scaffolded a series of self-guided assignments to integrate an honors podcast assignment equivalent to a term paper, but a product that could be included in their e-Portfolios. In the three years that we've used these assignments, we have helped 12 students complete honors contracts in Genetics with the final product being most impressive. 

BIOL 5800/6800 - Intro to Computational Biology

pre-req STAT 2510; Every fall semester, I teach this combined lecture and lab course in an active learning (EASL) classroom. This is a survey course in computational biology where I teach students (1) command line utilities, (2) basic scripting and programming skills, (3) how to effectively use regular expressions, and (4) using R for generating scientific quality graphics. Students can expect to learn the use of text manipulation applications (e.g. sed/awk), remote High Performance Computers (HPCs) via the Alabama Super Computer, reproducibility and version control concepts (via use of github), and code documentation via markdown formatting of README files. As part of the course, there are ten laboratory exercises that are started as in class lab activities and completed outside of class for a grade. There are four quizzes, five "capstone projects", and a comprehensive final project. Each lab and project has been designed to offer a “real world” application of computer science to biology. Students encounter physiological, genetic/genomic, biogeographical and other types of biological data throughout the semester. This course is required for the graduate certificate in Computational Biology and for the new Genetics Major.

BIOL 5860/6860 - Bioinformatics and Genome Analysis

pre-reqs BIOL 5800/6800; BIOL 3000; Every other spring semester (even years; next anticipated Spring 2024), I teach this research-based combined lecture and lab course in an active learning (EASL) classroom. As bioinformatics is a very fast-paced field, the central goal of this course is to make students comfortable approaching new bioinformatics tools later in their careers. Students are immersed into bioinformatics by having working on a collaborative research project throughout the semester. Throughout the course, students also design an independent genomics research project, write a research grant proposal, and edit it through peer editing. We then hold a mock grant review panel to demystify the grant review process for students. The students learn best practices for data-processing and quality control filtering. As they complete their research project, they become proficient in genome analysis and are exposed to a variety of bioinformatics tools. They also hone their skills on the command line, using a supercomputer, and using R for statistical analysis and generating quality graphics to depict quantitative scientific information. I also expose them to a variety of other data types and analysis through additional in-class lab assignments and exercises. This course is an approved elective for the graduate certificate in Computational Biology and for the new Genetics Major.