Project Leader: Deryc Painter
At the intersection between medicine and evolutionary biology, evolutionary medicine is an emerging trend through which our knowledge of evolutionary processes is applied to biomedical research and treatments. This perspective challenges what it could mean to receive cancer treatment, how we view mental illness, the increase in antibiotic resistant diseases, our bodies as a microbiome, treatment of autoimmune diseases, and social theory involved in pathogen communities. Until recently, most historical analysis was done through anecdotal or qualitative means. My project takes a computational approach, using annotations and topic modeling, to provide a quantitative overview of the history of evolutionary medicine. By creating a corpus, a meaningful collection of topically connected information, within our repository, I annotate and data mine large amounts of texts to create relationships between people, places, research topics. A sequential deployment of tools like Quadriga and Vogon, topic modeling and annotation tools, have allowed for a shift towards “big data” analysis for historical research; far beyond what could previously be done by hand, it's similar to the beginnings of bioinfomatics or genomics. This topic modeling allows for the creation of visual networks where concentrations of research, people, and diseases become readily apparent. By analyzing these networks, the influence of evolutionary medicine on biomedical research can be quantitatively expressed visually, allowing for the concentrations of clusters, when compared to the classical, clinical approach, to indicate the major changes that occur when health is viewed through an evolutionary lens.