Short-term Visitor

Tools to Study the Evolution of Host-Pathogen Interactions

PI(s): Jessica Kissinger (University of Georgia)
Start Date: 10-Aug-2014
End Date: 10-Oct-2014
Keywords: coevolution, database, software, disease, comparative methods

There is a general consensus that semantically annotated data and the availability of metadata (data about the data or study) should greatly facilitate both data reuse and knowledge discovery. Putting this into practice however is quite difficult. This project focuses on defining approaches for data related to identifying and ideally, visualizing larger-scale interactions. My particular interest is in the evolution of interactions between hosts and apicomplexan parasites but this is just one instance of an interaction between organisms, or viewed differently, between an organism and its environment. I have access to numerous large data sets that represent simultaneous data capture over time from both the parasite and the host for multiple parasite species, some in the same host. In some cases the data are of the same type, e.g. RNAseq, in other cases they are not, for example only the host has an immune response. The development of disease, or of different diseases is the result of a dynamic interaction between the host and pathogen. For decades, each has been studied in isolation. Now we can study them together, but is not clear just how one should do this with a host-pathogen pair let alone across pairs in order to study the evolution of the interaction.