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Zurich, Switzerland
July 4, 2007 to July 6, 2007
ISBN: 0-7695-2907-0
pp: 326-334
Matthew Hibbs , Princeton University, Princeton
Grant Wallace , Princeton University, Princeton
Maitreya Dunham , Princeton University, Princeton
Kai Li , Princeton University, Princeton
Olga Troyanskaya , Princeton University, Princeton
Genomics is an important emerging scientific field that relies on meaningful data visualization as a key step in analysis. Specifically, most investigation of gene expression microarray data is performed using visualization techniques. However, as microarrays become more ubiquitous, researchers must analyze their own data within the context of previously published work in order to gain a more complete understanding. No current method for microarray visualization and analysis enables biology researchers to observe the greater context of data that surrounds their own results, which severely limits the ability of researchers draw novel conclusions. Here we present a system, called HIDRA, that visually integrates the simultaneous display of multiple microarray datasets to identify important parallels and dissimilarities. We demonstrate the power of our approach through examples of real-world biological insights that can be observed using HIDRA that are not apparent using other techniques.
Matthew Hibbs, Grant Wallace, Maitreya Dunham, Kai Li, Olga Troyanskaya, "Viewing the Larger Context of Genomic Data through Horizontal Integration", IV, 2007, 2013 17th International Conference on Information Visualisation, 2013 17th International Conference on Information Visualisation 2007, pp. 326-334, doi:10.1109/IV.2007.120
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