中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Network screening of Goto-Kakizaki rat liver microarray data during diabetic progression

文献类型:期刊论文

作者Zhou,Huarong1; Saito,Shigeru2,3; Piao,Guanying1,4; Liu,Zhi-Ping1; Wang,Jiguang1; Horimoto,Katsuhisa2,5; Chen,Luonan1,2,5
刊名BMC Systems Biology
出版日期2011-06-20
卷号5期号:Suppl 1
ISSN号1752-0509
DOI10.1186/1752-0509-5-S1-S16
英文摘要AbstractBackgroundType 2 diabetes mellitus (T2DM) is a complex systemic disease, with significant disorders of metabolism. The liver, a central energy metabolic organ, plays a critical role in the development of diabetes. Although gene expression levels are able to be measured via microarray since 1996, it is difficult to evaluate the contributions of one altered gene expression to a specific disease. One of the reasons is that a whole network picture responsible for a specific phase of diabetes is missing, while a single gene has to be put into a network picture to evaluate its importance. In the aim of identifying significant transcriptional regulatory networks in the liver contributing to diabetes, we have performed comprehensive active regulatory network survey by network screening in 4 weeks (w), 8-12 w, and 18-20 w Goto-Kakizaki (GK) rat liver microarray data.ResultsWe identify active regulatory networks in GK rat by network screening in the following procedure. First, the regulatory networks are compiled by using the known binary relationships between the transcriptional factors and their regulated genes and the biological classification scheme, and second, the consistency of each regulatory network with the microarray data measured in GK rat is estimated to detect the active networks under the corresponding conditions. The comprehensive survey of the consistency between the networks and the measured data by the network screening approach in the case of non-insulin dependent diabetes in the GK rat reveals: 1. More pathways are active during inter-middle stage diabetes; 2. Inflammation, hypoxia, increased apoptosis, decreased proliferation, and altered metabolism are characteristics and display as early as 4weeks in GK strain; 3. Diabetes progression accompanies insults and compensations; 4. Nuclear receptors work in concert to maintain normal glycemic robustness system.ConclusionNotably this is the first comprehensive network screening study of non-insulin dependent diabetes in the GK rat based on high throughput data of the liver. Several important pathways have been revealed playing critical roles in the diabetes progression. Our findings also implicate that network screening is able to help us understand complex disease such as diabetes, and demonstrate the power of network systems biology approach to elucidate the essential mechanisms which would escape conventional single gene-based analysis.
语种英语
WOS记录号BMC:10.1186/1752-0509-5-S1-S16
出版者BioMed Central
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/248]  
专题中国科学院数学与系统科学研究院
通讯作者Zhou,Huarong; Horimoto,Katsuhisa; Chen,Luonan
作者单位1.Chinese Academy of Sciences; Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences
2.National Institute of Advanced Industrial Science and Technology; Computational Biology Research Center
3.INFOCOM Corporation
4.University of Science and Technology of China; Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences
5.Shanghai University; Institute of Systems Biology
推荐引用方式
GB/T 7714
Zhou,Huarong,Saito,Shigeru,Piao,Guanying,et al. Network screening of Goto-Kakizaki rat liver microarray data during diabetic progression[J]. BMC Systems Biology,2011,5(Suppl 1).
APA Zhou,Huarong.,Saito,Shigeru.,Piao,Guanying.,Liu,Zhi-Ping.,Wang,Jiguang.,...&Chen,Luonan.(2011).Network screening of Goto-Kakizaki rat liver microarray data during diabetic progression.BMC Systems Biology,5(Suppl 1).
MLA Zhou,Huarong,et al."Network screening of Goto-Kakizaki rat liver microarray data during diabetic progression".BMC Systems Biology 5.Suppl 1(2011).

入库方式: OAI收割

来源:数学与系统科学研究院

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