• DocumentCode
    3714659
  • Title

    Developing automated pipeline for identifying disease-related genomic variants

  • Author

    Chad Hayden; Dan Li;Kenji Yoshigoe;Mary Yang

  • fYear
    2015
  • Firstpage
    1789
  • Lastpage
    1789
  • Abstract
    Summary form only given. Advances in Next-Generation Sequencing technologies have opened unprecedented opportunities for identifying disease-associated genetic variations using whole genome / whole exome sequencing data. Precisely detecting all disease-related variants using computational tools is important but challenging. Presently such software tools have not been well developed. It is difficult to comprehensively and exactly capture genomic variations for systematic understanding of complex disease initialization and progression, such as cancer.
  • Keywords
    "Genomics","Bioinformatics"
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/BIBM.2015.7359964
  • Filename
    7359964