Visual Exploration across Biomedical Databases

Authors:
Michael D. Lieberman;Sima Taheri;whatever Guo;Fatemeh Mirrashed;Inbal Yahav;Aleks Aris;Ben Shneiderman
Affiliations:
University of Maryland, College Park;University of Maryland, College Park;University of Maryland, College Park;University of Maryland, College Park;University of Maryland, College Park;University of Maryland, College Park;University of Maryland, College Park
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2011

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Abstract

Though biomedical research often draws on knowledge from a wide variety of fields, few visualization methods for biomedical data incorporate meaningful cross-database exploration. A new approach is offered for visualizing and exploring a query-based subset of multiple heterogeneous biomedical databases. Databases are modeled as an entity-relation graph containing nodes (database records) and links (relationships between records). Users specify a keyword search string to retrieve an initial set of nodes, and then explore intra- and interdatabase links. Results are visualized with user-defined semantic substrates to take advantage of the rich set of attributes usually present in biomedical data. Comments from domain experts indicate that this visualization method is potentially advantageous for biomedical knowledge exploration.