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
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