DocumentCode
2185115
Title
PQuad: visualization of predicted peptides and proteins
Author
Havre, Susan L. ; Singhal, Mudita ; Payne, Deborah A. ; Webb-Robertson, Bobbie-Jo M.
Author_Institution
Pacific Northwest Nat. Lab., Richland, WA, USA
fYear
2004
fDate
10-15 Oct. 2004
Firstpage
473
Lastpage
480
Abstract
New high-throughput proteomic techniques generate data faster than biologists can analyze it. Hidden within this massive and complex data are answers to basic questions about how cells function. The data afford an opportunity to take a global or systems approach studying whole proteomes comprising all the proteins in an organism. However, the tremendous size and complexity of the high-throughput data make it difficult to process and interpret. Existing tools for studying a few proteins at a time are not suitable for global analysis. Visualization provides powerful analysis capabilities for enormous, complex data at multiple resolutions. We developed a novel interactive visualization tool, PQuad, for the visual analysis of proteins and peptides identified from high-throughput data on biological samples. PQuad depicts the peptides in the context of their source protein and DNA, thereby integrating proteomic and genomic information. A wrapped line metaphor is applied across key resolutions of the data, from a compressed view of an entire chromosome to the actual nucleotide sequence. PQuad provides a difference visualization for comparing peptides from samples prepared under different experimental conditions. We describe the requirements for such a visual analysis tool, the design decisions, and the novel aspects of PQuad.
Keywords
DNA; cellular biophysics; data visualisation; genetics; proteins; DNA; genomic information; interactive visualization tool; peptides; proteins; proteomic technique; visual analysis; wrapped line metaphor; Bioinformatics; Biological cells; DNA; Data visualization; Genomics; Organisms; Peptides; Protein engineering; Proteomics; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Visualization, 2004. IEEE
Print_ISBN
0-7803-8788-0
Type
conf
DOI
10.1109/VISUAL.2004.82
Filename
1372232
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