Computational Biology Research as a Chemical Engineering and Mathematics Major
Man presenting in a classroom of people.

Presenting my retinal computation work at SUMS 2024.

Author: Jared Noel | Major: Chemical Engineering, Mathematics  | Semester: Fall 2024

My name is Jared Noel, and I am a junior at the University of Arkansas, double majoring in chemical engineering and applied mathematics. This past summer, I had the opportunity to participate in the National Institute for Theory and Mathematics in Biology Summer Undergraduate Research Program (NITMB SURP). For this program, I lived in Chicago for eight weeks. I conducted research on retinal computations with Dr. Gregory Schwartz at Northwestern University’s Feinberg School of Medicine and Dr. Stephanie Palmer at the University of Chicago. The retina has a remarkable capacity for predicting future trajectories of moving objects in its natural environment, and this phenomenon is known as motion anticipation. In this project, I programmed a stimulus to move with statistics consistent with natural motion, and I showed this stimulus to a mouse retina. I then analyzed this data to beOer understand the mechanisms behind re?nal mo?on an?cipa?on. An example of one of these natural trajectories is seen below.

The type of research I conducted this summer is broadly defined as computational biology research, and this is the research I am primarily interested in pursuing. To get involved in this interdisciplinary field as an undergraduate student, I am double majoring in chemical engineering and applied mathematics. These two subjects allow me to take a unique combination of classes that effectively supplement my computational biology research experience. However, a necessary part of conducting research in any field is connecting with fellow researchers and learning about their work. Up to this point, as an undergraduate student, I had only attended chemical engineering conferences. While these conferences benefitted me as a student researcher, they were outside my primary field of interest. That is why I participated in the 2024 Shenandoah Undergraduate Mathematics and Statistics (SUMS) conference at James Madison University in Harrisonburg, VA, where I presented my computational biology research. This conference was the first mathematics conference I have attended, and it introduced me to a broad array of research topics I was unaware of before.

At this conference, I heard a talk given by Dr. Gretchen Matthews related to coding theory and cybersecurity. Additionally, I heard several other student presenters give talks on biology-related topics. Overall, hearing about this research showed me the wide variety of mathematical research applications, reaffirming my passion for my own computational biology research. Further, I presented my own work at this conference as a 15-minute oral presentation. This was the first time I had talked about my research to a group of primarily mathematicians. As such, the questions I received about my work after presenting were very different than the questions I have been asked in the past. These questions focused more on the mathematical underpinnings of my work, whereas questions I have been asked previously tended to focus on the broader applications of my work. Being asked these more theoretical questions changed how I view my research, effectively broadening my perspective. Moving forward, this new perspective will positively impact my research, allowing me to consider questions and ideas I would not have before.

Ultimately, attending the SUMS 2024 conference was incredibly beneficial for me and my future goals. I plan to continue conducting computational biology research as an undergraduate student and attend more mathematics conferences to continue to network and learn about other computational biology research. After graduating, I plan to pursue a Ph.D. in computational biology, where I continue to examine biological systems from a mathematical perspective. I aim to then pursue a translational research career where I work to use this computational biology framework to improve the healthcare landscape for patients in the United States.