• DocumentCode
    2767851
  • Title

    Identifying smoking associated gene co-expression networks related to oral cancer initiation

  • Author

    Zhang, Jie ; Knobloch, Thomas ; Parvin, Jeffrey ; Weghorst, Christopher ; Huang, Kun

  • Author_Institution
    OSUCCC Biomed. Inf. Shared Resource, Columbus, OH, USA
  • fYear
    2011
  • fDate
    12-15 Nov. 2011
  • Firstpage
    1039
  • Lastpage
    1041
  • Abstract
    We present a workflow to identify smoking specific gene co-expression networks and then screen them for specific networks with relationship to oral cancer initiation and development. Interestingly, we found the network with highest activity (based on mutual information metric) is a network uniquely identified from the smoking cohort in pre-cancerous stage, which is consistent with the role of smoking in oral cancer initiation. In addition, this network is highly enriched with oral and esophagus tissue specific genes. The discovery suggests that putative smoking associated genes can also be potential targets for cancer therapeutics.
  • Keywords
    bioinformatics; biological techniques; cancer; data mining; genetics; molecular biophysics; cancer therapeutics; esophagus tissue specific genes; mutual information metric; oral cancer development; oral cancer initiation; oral tissue specific genes; smoking associated gene coexpression networks; Algorithm design and analysis; Esophagus; Gene expression; Metastasis; Mouth; Mutual information;
  • 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.2011.6112553
  • Filename
    6112553