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Daniel Janies (University of North Carolina at Charlotte)
Our goal is to make and apply tools that provide value for scientific communication and the development of hypothesis driven work in the field of disease surveillance. The majority of existing systems for disease surveillance rely primarily on syndromic data. Of the few systems that use genetic sequence information, our tool stands out in providing a user-driven workflow capable of analyzing any molecular dataset and associated metadata. This main image represents the spread of Zika virus over time and space. The yellow color indicates the origins of a key mutation in the Zika genome associated with the shift severe disease outcomes. We created this image with an in house application called Nvector. Nvector is a simple visualization tool that runs in any web browser or in iOS and is designed for large-scale geographic visualizations. Use of a javascript-centric stack reduces server costs while increasing performance by avoiding tile server paradigms. To support our new tool we established a server system and API that uses an interoperable file format, JSON. The nvector application has a user interface with three tabs (views, data, and edit) that I will demonstrate.