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Proceedings Paper

Hypergraph visualization and enrichment statistics: how the EGAN paradigm facilitates organic discovery from big data
Author(s): Jesse Paquette; Taku Tokuyasu
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Paper Abstract

The EGAN software is a functional implementation of a simple yet powerful paradigm for exploration of large empirical data sets downstream from computational analysis. By focusing on systems-level analysis via enrichment statistics, EGAN enables a human domain expert to transform high-throughput analysis results into hypergraph visualizations: concept maps that leverage the expert's semantic understanding of metadata and relationships to produce insight.

Paper Details

Date Published: 2 February 2011
PDF: 18 pages
Proc. SPIE 7865, Human Vision and Electronic Imaging XVI, 78650E (2 February 2011); doi: 10.1117/12.890220
Show Author Affiliations
Jesse Paquette, Univ. of California, San Francisco (United States)
Taku Tokuyasu, Univ. of California, San Francisco (United States)

Published in SPIE Proceedings Vol. 7865:
Human Vision and Electronic Imaging XVI
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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