• DocumentCode
    573701
  • Title

    Network clustering along diabetes progression in three tissues of Goto-Kakizaki rats

  • Author

    Xinrong Zhou ; Saito, Sakuyoshi ; Horimoto, Katsuhisa ; Luonan Chen ; Huarong Zhou

  • Author_Institution
    Tongji Hosp., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2012
  • fDate
    18-20 Aug. 2012
  • Firstpage
    86
  • Lastpage
    91
  • Abstract
    We investigated the macroscopic changes in the regulatory coordination of diabetes progression during three periods in three tissues, adipose, liver and muscle, of Goto-Kakizaki (GK) rats. For this purpose, we performed network clustering by the Newman algorithm for the regulatory networks inferred by a modified path consistency algorithm, and investigated the biological functions of each cluster by an enrichment analysis of the constituent genes. We then compared the network clusters characterized by biological functions with the diabetes progression of GK rats in each of the three tissues. The network structure, the number of clusters, and the number of clusters characterized by biological functions during the three periods showed similar patterns in the three tissues. In contrast, further scrutiny of the biological functions at coordinated clusters revealed characteristic differences between the three tissues along the diabetes progression. In particular, the hypothetical roles of each tissue emerged: adipose and liver function at the cellular and molecular levels at the early stage, respectively, and all three tissues are responsible for diabetes progression, under the control of various transcriptional regulators.
  • Keywords
    cellular biophysics; diseases; liver; molecular biophysics; muscle; pattern clustering; Goto-Kakizaki rat; Newman algorithm; adipose; cellular level; diabetes progression; enrichment analysis; liver; modified path consistency algorithm; molecular level; muscle; network clustering; network structure; regulatory coordination macroscopic change; regulatory network; Biological tissues; Clustering algorithms; Diabetes; Liver; Muscles; enrichment analysis; network clustering; tissue relationship; type 2 diabetes progression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Biology (ISB), 2012 IEEE 6th International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-4396-1
  • Electronic_ISBN
    978-1-4673-4397-8
  • Type

    conf

  • DOI
    10.1109/ISB.2012.6314117
  • Filename
    6314117