The work presented here has two primary components: 1) the identification and annotation of transposable elements (TEs) and 2) a spatially-aware agent-based model of pathogen transmission. Recent advances in sequencing technology have resulted in an explosion of genomic data. The identification of TEs is an important part of every genome project. This dissertation presents an automated homology-based approach to identify TEs, implemented as TESeeker, that produces consensus TEs up to 98 identical to manually annotated sequences. It also offers a design and implementation plan to allow for the inclusion of TEs on VectorBase's community annotation pipeline. Agent-based modeling is very adept at modeling natural phenomena. Coupling geographical information system (GIS) data with agent-based modeling further increases the utility of such simulations. This dissertation presents a GIS aware agent-based model of pathogen transmission as well as methods and recommendations for incorporating GIS data into a simulation. The model, named LiNK, was specifically developed to study the impact of landscape on pathogen transmission.