Rachel Shrode


Graduate Research Assistant, Interdisciplinary Graduate Program in Informatics
rachel-shrode@uiowa.edu

Rachel Shrode

Department of Pathology
1080 Medical Laboratories
500 Newton Road
University of Iowa
Iowa City, IA 52242-1109

Lab: 319-335-8205

Education

BS, Biology and Spanish

I have moved all over the country in the last 6 years. I grew up in Waunakee, WI, finished highschool in Parker, CO, and received my undergraduate degree in Laramie, WY at the University of Wyoming. My main interest throughout school was in Biology. By the time I got to college I knew I wanted to be a part of a research lab, but I wasn’t sure what area of biology or what role in the lab. First I joined Dr. Brent Ewers’ Botany lab my sophomore year at the University of Wyoming. I did basic data collection work in their greenhouse. During my time in his lab, a PhD student, Mallory Lai taught me some of the basics of program R. I analysed some sets of data they had from previous experiments. Right away I found data analysis to be the most interesting part of an experiment. That following summer I was a teaching assistant in a highschooler’s introduction to R class. Then my junior year I decided I wanted to find a lab that would allow me to work more in R. I was also in a Microbiology lab and asked my lab instructor how to become a TA for the lab because I enjoyed it so much. We got to talking and she, Amy Rhoad, was a PhD student who happened to need a TA for lab and help with microbiome data analysis using R in her graduate work! She hired me for both positions and as I learned more about the intestinal microbiome, it’s effects on human health, and how to model the interaction, I knew I wanted to pursue further education on how to computationally analyse the microbiome. Then by the spring of my senior year I was hired for a position in Dr. Mangalam’s lab where I will be helping to find the most efficient and in-house pipeline for computational microbiome analysis. With that pipeline I will then help analyse the current data from the lab’s experiments on MS (multiple-sclerosis) and it’s interaction with the microbiome