As a Master of Science student in Dr. Lloyd Elliott's lab I am studying computational biology from a few directions. Below, I briefly describe these directions and present some entertaining materials from my studies.
My primary research is in genomics and metabolomics with the objective of understanding aging in humans. Our lab explores statistical methods to learn about biological processes that influence longevity using the Canadian Longitudinal Study on Aging and an exceptional cohort of Super-Seniors (conducted by my supervisor Dr. Angela Brooks-Wilson).
I am particularly interested in complex networks of metabolites, and how to learn about them to make clinically relevant insights. Methods for learning about metabolomics networks include sparse or other specialized estimation methods for the covariance, correlation and partial correlation matrices. These matrix estimators inform models like Bayesian networks such as Gaussian graphical models. In particular, after reading Fisher's (1924) paper "The distribution of the partial correlation coefficient" I have been inspired to adopt a geometrical interpretion of theoretical concepts wherever possible.
I am studying the best methods of estimating the correlation and partial correlation (precision) matrices in our data context. As listed below, I began with Serra et al. (2018) and proposed an extension to improve their method's sensitivity without losing its superior specificity performance. From here, I am applying various methods to answer my thesis question and explore their usefulness in other contexts, collaborating with others in my lab.
To complement my studies in human health, I am collaborating with Dr. Arne Mooers and Dr. Jonathan Davies to study the relationships between species abundance and how those relationships can help us estimate change in global biodiversity over time.
In addition to the research areas listed above, I am keen to collaborate on additional interdisciplinary topics. Most recently, I worked with my close friend Dr. Eric MacFadden to design, conduct and analyze data for his study on computer assisted implant surgery. This work was selected to be presented by Dr. MacFadden at the 2026 Ramfjord Symposium.