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Danielle Albers, Colin Dewey, and Michael Gleicher (University of Wisonsin - Madison, 1210 W Dayton St., Madison, WI;)Sequence alignment visualization is an important tool for understanding genomics data. As sequencing techniques improve and more data becomes available, greater demand is being placed on existing tools to scale to the size of these new data sets. However, current tools do not scale to the challenges of growing data sets, as they focus on visualizing details of the data instead of global trends. We introduce overview visualization tools for large-scale multiple sequence alignment data. When viewing such large data, we necessarily cannot convey details, rather we specifically design overview tools to help elucidate large scale patterns. Perceptual science and signal processing theory provide a framework for the design of such visualizations that can scale well beyond current approaches. We present Sequence Surveyor, a prototype that embodies these ideas for scalable multiple sequence alignment overview visualization. We demonstrate how perceptual science and signal processing concepts can be used to support scalability in visualization and use these techniques to simultaneously visualize over 100 aligned genomic sequences.