• 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