激酶与磷酸酶交互网络的中枢(英文)  

The centers of kinase and phosphatase interaction network

作　　者：丁德武[1] 谢杨梅[1] 夏启寿[1] 

机构地区：[1]池州学院数学与计算机科学系,安徽池州247000

出　　处：《计算机与应用化学》2011年第6期783-786,共4页Computers and Applied Chemistry

基　　金：安徽省教育厅自然科学基金资助项目(KJ2010B133);安徽高校省级优秀青年人才基金资助项目(2011SQRL162)

摘　　要：蛋白激酶与磷酸酶是细胞信号转导途径中的最重要元素,最近出版了酵母的全局蛋白激酶与磷酸酶交互(KPI)网络。由于缺乏详尽的热力学参数,拓扑的(或结构的)分析方法被用于研究该网络,例如,度中心化指标被用于识别该网络中央的蛋白。但是,对真实世界的网络模型使用单一的中心化指标明显不合理,需要组合多种指标综合考虑。本文首先比较了14种不同的中心化指标,然后将它们应用于蛋白激酶与磷酸酶交互网络,最后确定了该网络的10个中央的蛋白并讨论了它们的生物学意义。Protein kinases and phosphatases are the most important elements in cellular signal transduction pathways,a global protein kinase and phosphatase interaction（KPI）network in budding yeast is recently published.Due to the absence of detailed kinetic parameters,topological（or structural）analyses are used in the network,e.g.degree centrality is used to analysis of KPI network for the identification of the central proteins. However,it is clear that any single centrality measure in real-world networks is very limited,and multi-centrality measures should be combined for these networks.In the present paper,14 different centrality measures are compared firstly,and then their application to the KPI network are analyzed, at last the top 10 central proteins in the network are identified,and their biological signification are discussed.

关 键 词：中心化 巨强连通成分 蛋白交互 信号途径 系统生物学 

分 类 号：TP339[自动化与计算机技术—计算机系统结构] Q5[自动化与计算机技术—计算机科学与技术]