Abstract
Biological sequence similarity analysis presents visualization challenges, primarily because of the massive amounts of discrete, multi-dimensional data. Genomic data generated by molecular biologists is analyzed by algorithms that search for similarity to known sequences in large genomic databases. The output from these algorithms can be several thousand pages of text, and is difficult to analyze because of its length and complexity. We developed and implemented a novel graphical representation for sequence similarity search results, which visually reveals features that are difficult to find in textual reports. The method opens new possibilities in the interpretation of this discrete, multi-dimensional data by enabling interactive investigation of the graphical representation.
| Original language | English (US) |
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| Title of host publication | Proceedings of the IEEE Visualization Conference |
| Editors | Gregory M. Nielson, Deborah Silver |
| Publisher | IEEE |
| Pages | 44-51 |
| Number of pages | 8 |
| State | Published - Dec 1 1995 |
| Event | Proceedings of the 1995 6th Annual IEEE Conference on Visualization - Atlanta, GA, USA Duration: Oct 29 1995 → … |
Other
| Other | Proceedings of the 1995 6th Annual IEEE Conference on Visualization |
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| City | Atlanta, GA, USA |
| Period | 10/29/95 → … |