• DocumentCode
    3409561
  • Title

    A workflow for parallel and distributed computing of large-scale genomic data

  • Author

    Hyun-Hwa Choi ; Byoung-Seob Kim ; Shin-Young Ahn ; Seung-Jo Bae

  • Author_Institution
    Dept. of Cloud Comput. Res., Electron. & Telecommun. Res. Inst., Daejeon, South Korea
  • fYear
    2013
  • fDate
    9-12 Dec. 2013
  • Firstpage
    215
  • Lastpage
    218
  • Abstract
    Workflow management systems are emerging as dominant solution in bioinformatics because they enable researchers to analyze the huge amount of data generated by modern laboratory equipment. The growth of genomic data generated by next generation sequencing (NGS) results in an increasing need to analyze data on distributed computer clusters. In this paper, we construct a semi-automated workflow system for the analysis of large-scale sequence data sets, describe a pipeline designed with parallel computation to perform the optimal computational steps required to analyze whole genome sequence data, and report the overall execution time of the pipeline using cores on multiple machines.
  • Keywords
    bioinformatics; data handling; parallel processing; workflow management software; NGS; bioinformatics; distributed computer clusters; distributed computing; laboratory equipment; large scale genomic data; multiple machines; next generation sequencing; parallel computing; workflow management systems; Bioinformatics; Employment; Genomics; Pipelines; Sequential analysis; Servers; Software tools; bioinformatics; genomic data; next generation sequencing; pipeline;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Internet Technology and Secured Transactions (ICITST), 2013 8th International Conference for
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/ICITST.2013.6750194
  • Filename
    6750194