• DocumentCode
    2791444
  • Title

    Scalable, Dynamic Analysis and Visualization for Genomic Datasets

  • Author

    Wallace, Grant ; Hibbs, Matthew ; Dunham, Maitreya ; Sealfon, Rachel ; Troyanskaya, Olga ; Li, Kai

  • Author_Institution
    Dept. of Comput. Sci., Princeton Univ., NJ
  • fYear
    2007
  • fDate
    26-30 March 2007
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    A challenge in data analysis and visualization is to build new-generation software tools and systems to truly accelerate scientific discoveries. The recent focus of Princeton´s next-generation software project is to investigate how to develop new-generation data analysis and visualization capabilities for genomic scientists to analyze high-throughput genomic datasets. This paper describes the software tools we have recently developed to enable dynamic, large-scale data analysis and visualization of multiple datasets on large-scale, high-resolution display wall systems. Our initial experience with the deployed tools at Princeton´s Lewis-Sigler Institute for Integrative Genomics is very encouraging. Scientists can effectively learn new knowledge from multiple datasets, find new insights, and generate new hypotheses that are not possible with current methods.
  • Keywords
    biology computing; data analysis; genetics; data analysis; data visualization; genomic dataset; software tool; Bioinformatics; Computer science; Data analysis; Data visualization; Displays; Explosions; Genomics; Laboratories; Large-scale systems; Software tools;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    1-4244-0910-1
  • Electronic_ISBN
    1-4244-0910-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2007.370529
  • Filename
    4228257