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. (Read more...)
One of the research questions of this project focuses on the transformation of textual data into a “computer-understandable” format. The approach of the Quadriga System is to transform information into contextualized relationship triples, so-called “quadruples.” We have designed the quadruple data model and implemented a prototype of an application called Vogon that is used to extract quadruples from texts. Quadruples form semantic networks that can be used to develop advanced search engines that answer questions such as “who has stated that Darwin...(Read more...)
This project is a reconstruction of the field of plant experimental taxonomy (or "genecology") in post-war Britain, an important pre-cursor to the contemporary field of evolutionary ecology. We seek to understand not only the social and material relationships that characterized that field, but also the complex interplay of those evolving relationships with the changing questions, patterns of language, and core assumptions of its practitioners. (Read more...)
Developmental Evolution is a tradition within evolutionary biology with a very long history. It focuses on the mechanistic (cellular, developmental, genomic) causes that generate phenotypes and phenotypic variation. While it is often seen as an "alternative" to mainstream population genetics, it is in fact a complementary and necessary approach to theories of evolutionary dynamics. This project looks at the history of this tradition as a big data problem, combining the reconstruction of individual contributions... (Read more...)
Our ultimate goal in history of biology is to gain insights into the nature of scientific innovation. Besides analyzing conceptual transformation of knowledge systems, as we do in many of our projects, we also study the investigative pathways of researchers and research groups that have generated innovative transformations in our understanding of specific scientific problems. We focus on two prominent biologists, Nobel Laureate Sydney Altman, co-discoverer of the catalytic properties of RNA, and developmental biologist Eric Davidson, whose ideas about the role of gene regulatory networks have revolutionized our understanding of developmental evolution. Again, we are using computational approaches to study and reconstruct these investigative pathways.and research programs with computational analysis of the conceptual dynamics of evolutionary biology at large. (Read more...)
For more information about the digital infrastructure at the core of our computational research, visit the Digital HPS Consortium.