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2025年4月6日 星期日
  2016, Vol. 24 Issue (11): 1790-1800    
  研究资源与技术改进 本期目录 | 过刊浏览 | 高级检索 |
成脂调控网络(ARN)数据库的分析和预测功能
黄艳1,王力1,昝林森2
1. 西北农林科技大学
2. 西北农林科技大学,国家肉牛改良中心
Analysis and Forecast Function of the Adipogenesis Regulation Network (ARN) Database
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摘要 脂肪组织中脂类的过量积累会导致肥胖,进而引发心血管疾病、二型糖尿病和其他疾病。成脂是指干细胞分化为能够积聚脂滴的脂肪细胞的过程,受到一个复杂且高度协调的基因表达网络的调节,为促进成脂调控中关键基因和通路的发现,探索脂肪生成的分子调控机理,在之前的研究中,本实验室通过对成脂相关文献进行文本挖掘构建出一个包含3万多条成脂相关数据和信息的成脂调控网络(Adipogenesis Regulation Network, ARN)数据库(http://210.27.80.93/arn/)。为了进一步充分发掘ARN数据库促进成脂相关研究的潜在价值,本研究通过“开放的”和“闭合的”两种构建假说的原理,设计出能够用于分析成脂分化相关试验数据或构建科学假说的在线分析工具-ARN-analysis。另外,通过对成脂调控网络中各节点(基因和小分子RNA)的互作关系数、差异表达记录数和互作关系预测数进行统计分析,计算得到体现各节点重要性的节点影响值(impact factor, IF)。最后,通过对成脂调控网络中各节点的互作关系进行统计分析和作图,探索了成脂调控网络的拓扑结构。结果显示,ARN数据库的分析工具能够有效分析“节点相关”、“表达相关”及“用户录入”3类数据,帮助科研人员分析试验数据或构建科学假说。节点的IF值能够帮助科研人员快速识别重要的节点或假说,对调控网络拓扑结构的分析能加深对成脂调控机理的认识。本研究对成脂专业数据库的分析和预测功能的探索,为专业研究人员分析数据和构建假说提供了新的途径,探索了运用过去积累的大量科研数据促进未来的科研实践的可能性。
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黄艳
王力
昝林森
关键词 肥胖成脂调控网络数据库大数据    
Abstract:Excess accumulation of lipids in the adipose tissue leads to obesity, which is associated with cardiovascular diseases, type Ⅱ diabetes and other pathologies. Adipogenesis is the process by which precursor stem cells differentiate into lipid laden adipocytes. Adipogenesis is regulated by a complex and highly orchestrated gene expression program. In order to discovery key regulatory genes and pathways in adipogenesis and explore the molecular regulation mechanism of adipogenesis, in the previous study, we constructed a Adipogenesis Regulation Network (ARN) Database (http://210.27.80.93/arn/) by mining over 9 000 papers related to adipogenesis, which contains more than 30 000 adipogenesis related data and information. In order to fully explore the potential value of ARN database to promote the study of adipogenesis, in this study, we designed an online analysis tool "ARN-analysis" to analyze the experimental data or to construct the scientific hypothesis about adipogenesis through two hypothesis construction processes: "open" and "closed". Furthermore, by count the number of the relation records, the number of the expression records and the number of the prediction records for each node (gene and micro RNA), the impact factor (IF) value which reflects the importance of each node was calculated. Finally, by analyzing and mapping the number of the relation records of nodes, the topology of the adipogenesis regulation network was explored. The results showed that the analysis tool of ARN database can effectively analyze 3 kinds of data: "node" and "expression" and "user input", it would be useful for researchers to analyze test data or build scientific hypotheses. Understanding of the regulation network topology can deepen our understanding of the mechanism of the formation of fat. In this study the analysis and prediction functions of ARN database was explored, ARN provided a new way for professional researchers to analyze data and construct hypotheses, explored the possibility of using a large number of scientific research data accumulated in the past to promote future research and practice.
Key wordsObesity    Adipogenesis    Regulation Network    Database    Big data
收稿日期: 2016-04-28      出版日期: 2016-10-01
基金资助:国家自然科学基金;国家“863”计划;国家“863”计划
通讯作者: 昝林森     E-mail: zanlinsen@163.com
引用本文:   
黄艳 王力 昝林森. 成脂调控网络(ARN)数据库的分析和预测功能[J]. , 2016, 24(11): 1790-1800.
链接本文:  
http://journal05.magtech.org.cn/Jwk_ny/CN/     或     http://journal05.magtech.org.cn/Jwk_ny/CN/Y2016/V24/I11/1790
 
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