Visual exploration across biomedical databases

Michael D. Lieberman, Sima Taheri, Huimin Guo, Fatemeh Mirrashed, Inbal Yahav, Aleks Aris, Ben Shneiderman

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number5383347
Pages (from-to)536-550
Number of pages15
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume8
Issue number2
DOIs
StatePublished - 2011
Externally publishedYes

Keywords

  • Data exploration and discovery
  • bioinformatics
  • information visualization

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Genetics
  • Applied Mathematics

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