蛋白复合物超网络特性分析及应用

胡枫; 刘猛; 赵静; 雷蕾; 胡枫; 刘猛; 赵静; 雷蕾

doi:10.13306/j.1672-3813.2018.04.005

复杂系统与复杂性科学 >

2018 , Vol. 15 >Issue 4: 31 - 38

DOI: https://doi.org/10.13306/j.1672-3813.2018.04.005

蛋白复合物超网络特性分析及应用

胡枫 ,
刘猛 ,
赵静 ,
雷蕾 ,
胡枫 ,
刘猛 ,
赵静 ,
雷蕾

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1.青海师范大学,西宁 810008;
2.青海省藏文信息处理与机器翻译重点实验室,西宁 810008;
3.藏文信息处理教育部重点实验室,西宁 810008;
4.陆军勤务学院,重庆 401331

胡枫(1970),女,青海民和人,博士,教授,主要研究方向为复杂网络、超网络理论及应用。

网络出版日期: 2019-05-16

基金资助

国家自然科学基金(61663041);青海科技计划项目(2015ZJ723,2018ZJ718);重庆市自然科学基金(cstc2018jcyjAX0090)

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Analysisand Application of the Topological Properties of Protein Complex Hypernetworks

HU Feng ,
LIU Meng ,
ZHAO Jing ,
LEI Lei ,
HU Feng ,
LIU Meng ,
ZHAO Jing ,
LEI Lei

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1.Qinghai Normal University, Qinghai Xining 810016;
2.Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province, Qinghai Xining 810008;
3.Tibetan intelligent information processing and Machine Translation Key Laboratory, Qinghai Xining 810008;
4.Army Logistics University of PLA,Chongqing, 401331

Online published: 2019-05-16

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摘要

研究蛋白复合物超网络的拓扑性质,并根据超网络的相关拓扑指标识别网络的关键蛋白质。根据获取的蛋白复合物数据集,以蛋白质为节点,复合物为超边,构建了蛋白复合物的超网络模型。在此超网络模型上,通过蛋白质的度、超度和子图中心度拓扑指标分析了超网络的结构特性,得到了识别网络中的关键蛋白的方法,并通过在线基因必需性数据库(Online GEne Essentiality, OGEE)中的数据进行了验证。

关键词： 超网络; 蛋白复合物网络; 关键蛋白; 拓扑分析

本文引用格式

胡枫 , 刘猛 , 赵静 , 雷蕾 , 胡枫 , 刘猛 , 赵静 , 雷蕾 . 蛋白复合物超网络特性分析及应用[J]. 复杂系统与复杂性科学, 2018 , 15(4) : 31 -38 . DOI: 10.13306/j.1672-3813.2018.04.005

Abstract

This paper aims to study the topological properties of protein complex hypernetwork and to solve some practical problems based on topology characteristics of the hypernetwork, including the identification of key proteins of the network. Based on the obtained data set of protein complexes, a hypernetwork model of protein association relationship is constructed, in which each protein is represented by a node and each complex by a hyperedge. We study the topological featuresof the protein complex hypernetwork such as hyperdegree distribution, degree distribution, and sub-hypergraph centrality to identifying the key proteins. Furthermore, the results are verified by Online GEne Essentiality (OGEE) data set.

Key words： hypernetwork; protein complex network; key proteins; topological analysis

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