Flexible information visualization of multivariate data from biological sequence similarity searches

Ed Huai hsin Chi, John Riedl, Elizabeth Shoop, John V Carlis, Ernest Retzel, Phillip Barry

Research output: Contribution to conferencePaperpeer-review

14 Scopus citations


Information visualization faces challenges presented by the need to represent abstract data and the relationships within the data. Previously, we presented a system for visualizing similarities between a single DNA sequence and a large database of other DNA sequences. Similarity algorithms generate similarity information in textual reports that can be hundreds or thousands of pages long. Our original system visualized the most important variables from these reports. However, the biologists we work with found this system so useful they requested visual representations of other variables. We present an enhanced system for interactive exploration of this multivariate data. We identify a larger set of useful variables in the information space. The new system involves more variables, so it focuses on exploring subsets of the data. We present an interactive system allowing mapping of different variables to different axes, incorporating animation using a time-axis, and providing tools for viewing subsets of the data. Detail-on-demand is preserved by hyperlinks to the analysis reports. We present three case studies illustrating the use of these techniques. The combined technique of applying a time axis with a 3D scatter plot and query filters to visualization of biological sequence similarity data is both powerful and novel.

Original languageEnglish (US)
Number of pages8
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE Visualization Conference - San Francisco, CA, USA
Duration: Oct 27 1996Nov 1 1996


OtherProceedings of the 1996 IEEE Visualization Conference
CitySan Francisco, CA, USA


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