Visualizing mutations of a virus sequence

This thesis addresses a synthetic health-dataset, introduced at the IEEE VAST Challenge 2010. My research team participated in this contest to evaluate the pre-designed tool, ”IMAS” using a benchmark dataset.Learning from this contest, I designed an Information Visualization InfoVis prototype, ”FilooT” to gain a better understanding of that dataset. Following the Nested Model for Visualization Design, my thesis’ qualitative methodology consists of a design study and evaluation. To make an effective design, I followed well-cited InfoVis principles of perception and cognition. I also utilized prior knowledge produced by the proposed solutions that had been tackled the contest’s dataset. To understand the tool’s design capabilities for target domain analysts, I observed domain-users’ reactions to FilooT in a User-Experience scenario. The findings of the study indicated how analysts employ each of the visualization and interaction designs in their Bioinformatics’ task-analysis process. The critical analysis of the results inspired design informing suggestions.