• DocumentCode
    680181
  • Title

    Differential coexpression analysis in gene modules level and its application to type 2 diabetes

  • Author

    Lin Yuan ; Wen Sha ; Jun Zhang ; Chun-Hou Zheng ; Jun-Feng Xia

  • Author_Institution
    Coll. of Electr. Eng. & Autom., Anhui Univ., Hefei, China
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    193
  • Lastpage
    196
  • Abstract
    More and more studies have shown many complex diseases are contributed jointly by alterations of numerous genes. In this paper, we propose a gene differential coexpression analysis algorithm in the level of gene sets and apply the algorithm to a publicly available type 2 diabetes (T2D) expression dataset. The experimental results on simulated data show that the new approach performed well. Moreover, we apply the new approach to clinical data, many additional discoveries can be found through our method.
  • Keywords
    diseases; genetics; T2D; diseases; gene differential coexpression analysis algorithm; gene module level; gene set level; type 2 diabetes expression dataset; Algorithm design and analysis; Biology; Correlation; Diabetes; Diseases; Noise; Standards; biweight midcorrelation; differential coexpression analysis; k-clique algorithm; threshold strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732487
  • Filename
    6732487