DocumentCode
3041978
Title
Visualizing Quantitative Proteomics Datasets using Treemaps
Author
Halligan, Brian D. ; Mirza, Shama P. ; Pellitteri-Hahn, Molly C. ; Olivier, Michael ; Greene, Andrew S.
Author_Institution
Med. Coll. of Wisconsin, Milwaukee
fYear
2007
fDate
4-6 July 2007
Firstpage
527
Lastpage
534
Abstract
One of the major challenges of large scale mass spectrometry based proteomics experiments is organizing and visualizing the data in such a way so that meaningful biological conclusions can be drawn from the data. Our tool, ZoomQuant, is capable of quantitating relative protein abundance between two samples in stable isotope labeled quantitative proteomics experiments. The resulting protein ratios are then annotated and categorized using the GO ontology terms. Sets of data representing different biological states can then be compared quantitatively and the results formatted for dynamic visualization. Using TreeMap, the user can visualize the quantitative differences between the biological states in a single view. The peptide or scan count and ratio for individual proteins are displayed and organized by the GO ontologies so that the user can easily see the global differences in protein expression between the two samples.
Keywords
biology computing; data visualisation; mass spectroscopy; ontologies (artificial intelligence); proteins; tree data structures; gene ontology; mass spectrometry; quantitative proteomics dataset visualization; treemaps; Biotechnology; Data visualization; Isotopes; Labeling; Large-scale systems; Mass spectroscopy; Ontologies; Peptides; Proteins; Proteomics;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Visualization, 2007. IV '07. 11th International Conference
Conference_Location
Zurich
ISSN
1550-6037
Print_ISBN
0-7695-2900-3
Type
conf
DOI
10.1109/IV.2007.136
Filename
4272031
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