• DocumentCode
    2767634
  • Title

    Integration of statistical models and visualization tools to characterize microRNA networks influencing cancer

  • Author

    Karnia, James ; Delfino, Kristin R. ; Villamil, Maria B. ; Caetano-Anolles, Gustavo ; Rodriguez-Zas, Sandra L.

  • Author_Institution
    Dept. of Animal Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2011
  • fDate
    12-15 Nov. 2011
  • Firstpage
    1009
  • Lastpage
    1011
  • Abstract
    Gene expression microarray experiments can be used to infer the topology of co-expression networks between genes in the immune-system pathways. Immune-system pathways are highly dimensional, including numerous gene nodes and edges connecting nodes. A bioinformatics strategy to infer and confirm gene co-expression networks was developed and applied to two major immune-system pathways. In total, 182 and 356 co-expression profiles between pairs of genes were identified in the NOD-like and B-cell receptor signaling pathways. The distinct distribution of the sign of the relationships among the pathways offered additional insights into the network.
  • Keywords
    DNA; bioinformatics; cancer; cellular biophysics; genetics; medical diagnostic computing; molecular biophysics; statistical analysis; B-cell receptor signaling pathway; NOD-like receptor signaling pathway; bioinformatics; cancer; edge connecting nodes; gene expression microarray; gene nodes; immune-system pathways; microRNA networks; statistical models; visualization tools; Bioinformatics; Correlation; Gene expression; Immune system; Mice; Probes; Solids; B-cell receptor; Cytokine; NOD-like receptor; chemokine; microarray;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4577-1612-6
  • Type

    conf

  • DOI
    10.1109/BIBMW.2011.6112541
  • Filename
    6112541