In November’s Junior Researcher Feature, we have an interview with Ruby Kim, Ph.D. Student in Mathematics, Duke University.
When did you first become interested in mathematics and biology?
I was always very interested in math and biology growing up. Those were my favorite subjects in school, and I’d spend a lot of time outside of class researching different topics in biology. However, as a first-generation college student, I didn’t have much exposure to what these interests meant for my long-term future. During the summer after my 2nd year of undergrad, I attended a week-long mathematical biology workshop at Duke where I learned for the first time what mathematical biology is. I’ve pursued mathematical biology ever since.
Was the decision to do a Ph.D. an obvious and easy choice?
My decision to do a Ph.D. in mathematics was not an obvious choice, initially. I majored in math in college and immersed myself in research, but didn’t have any specific career goals for much of my undergraduate career. A Ph.D. seemed out of the question at the time. In my junior year, however, one of my math professors gave me the opportunity to work on an extremely exciting project modeling tumor-immune interactions. This experience made me realize that mathematical biology research was something I could see myself enjoying for the rest of my life. She later became my undergraduate thesis advisor and played a pivotal role in my decision to apply to graduate school. Her mentorship helped to demystify graduate school for me.
What are the main biological research questions that you are interested in?
I am currently interested in mammalian circadian rhythms and the dopaminergic system. Dopamine is an important neurotransmitter involved in learning, motivation, and motor control, and disruptions in the dopaminergic system are linked to many different neurological and psychiatric conditions such as Parkinson’s disease, Tourette’s syndrome, and mood disorders. These conditions are also often accompanied by disturbed circadian rhythms but the links between the circadian clock and the dopaminergic system aren’t well understood. I’ve created the first mathematical model to describe the mechanisms by which the circadian clock influences dopamine. Details about the project can be found in the paper A mathematical model of circadian rhythms and dopamine that I coauthored with Dr. Mike Reed. I have also recently worked on a project modeling sex differences in one-carbon metabolism.
What types of questions do you think will be important to answer in the future in your field?
The interactions between the circadian clock and systems involving different neurotransmitters and hormones like dopamine, serotonin, and melatonin have many important health consequences, and this is widely accepted in the biological literature. It’s known for example that the symptoms of the dopamine-related condition restless legs syndrome (RLS) follow a circadian pattern. However, the underlying cellular and molecular mechanisms remain elusive. Creating mathematical frameworks to investigate these connections would be extremely helpful in understanding and predicting the health consequences of clock-related dynamics.
What mathematical and computational tools do you find useful in your work?
Throughout graduate school, I’ve primarily worked with MATLAB and tools from dynamical systems and scientific computing to create and study models comprised of ordinary differential equations. The primary motivation of my work is to understand the biology, so I am very open to using different mathematical and computational tools as needed. I’ve worked on smaller projects involving stochastic agent-based modeling, equation learning, and bifurcation analysis.
How would you describe the results of a recent paper you contributed to?
I recently worked on a project modeling hepatic one-carbon metabolism (OCM) throughout the menstrual cycle and pregnancy. Sex hormones like estrogen and testosterone are known to significantly affect OCM, resulting in sex differences in disease outcomes and reactions to drugs. One of the first major findings of this project was an explanation for why menstruating women tend to have lower levels of homocysteine (Hcy) than men. This finding has large health implications because Hcy is an important biomarker for cardiovascular disease. I’ve extended and improved the mathematical model to understand the effects of estradiol variation on OCM during the menstrual cycle and pregnancy. The mathematical model can be used for in silico experiments, to identify drug targets for menstrual disorders, and to help understand how OCM disruptions lead to pregnancy complications. The paper is currently under revision at PLOS Computational Biology.
What makes you passionate about your work?
My research is very exciting to me because I’m always learning new things and I get to work on challenging, applicable problems. However, what I’ve appreciated the most during my Ph.D. are the people and community I interact with on a day-to-day basis. I enjoy discussing research with my advisor and collaborators, connecting with the students I teach, and chatting with other mathematical biologists at workshops or conferences. I love that my work is collaborative.
What do you like to do in your spare time outside of work?
I realized recently that I really enjoy sports that require some sort of problem solving or strategy. I’ve been going bouldering a lot! I also like cooking and spending quality time with friends and family.