• DocumentCode
    191020
  • Title

    A systems biology analysis for the whole genome sequencing data

  • Author

    Jhamb, Deepali ; Pradhan, Meeta P. ; Desai, Amish ; Palakal, Mathew J. ; Duraiswamy, Premkumar

  • Author_Institution
    Sch. of Inf. & Comput., Indiana Univ. Purdue Univ. Indianapolis, Indianapolis, IN, USA
  • fYear
    2014
  • fDate
    2-4 June 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The next generation sequencing technology has enabled the understanding of the whole genome of an organism at a greater coverage and reduced cost. In this study, we provide a systems biology approach to understand the functional relevance of the single nucleotide variants identified by the whole genome sequencing studies. This approach also includes a methodology for the identification of conserved modules among the family members. Our study contributes towards the much needed downstream functional analysis of the variant data, especially for the low frequency and novel variants, and provides a framework for the analysis of multiple genomes to derive relations between variants and diseases.
  • Keywords
    bioinformatics; diseases; genetics; genomics; conserved module identification; diseases; downstream functional analysis; family members; functional relevance; low frequency variants; multiple genomes; next generation sequencing technology; organism; single nucleotide variants; systems biology analysis; variant data; whole genome sequencing data; Bioinformatics; Diseases; Genomics; Sequential analysis; Sociology; Statistics; Systems biology; SNV; low frequency variants; next generation sequencing; systems biology; whole genome sequencing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4799-5786-6
  • Type

    conf

  • DOI
    10.1109/ICCABS.2014.6863922
  • Filename
    6863922