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evolution of a protein domain interaction network

Chinese Physics B 2010年第1期19卷 204-211页

作者：高丽锋石建军官山 Institute of Crop Sciences Chinese Academy of Agricultural Sciences College of Physics Science and Technology Yangzhou University

In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows：（i） there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; （ii） few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; （iii） in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases.

关键词： complex network protein domain network evolution

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Hierarchical networks of food exchange in the black garden ant Lasius niger

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Insect Science 2021年第3期28卷 825-838页

作者： Martin Quque Olivier Bles Annaelle Benard Amelie Heraud Bastien Meunier Frangois Criscuolo Jean-Louis Deneubourg Cedric Sueur CA/RS IPHCUniversite de StrasbourgStrasbourgUMR718France Centre for Nonlinear Phenomena and Complex Systems(Cenoli)-CP 231 Universite libre de Bruxelles(ULB)BruxellesBelgium Universite de Bourgogne Franche-Comte DijonFrance Universite de Rennes 1 RennesFrance Institut Universitaire de France ParisFrance

In most eusocial insects,the division of labor results in relatively few individuals foraging for the entire colony.Thus,the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members.Here,we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination.We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants(Lasius niger).We tested the influence of brood and colony size on(i)global indices at the network level(i.e.,efficiency,resilience,centralization,and modularity)and(ii)individual values(i.e.,degree,strength,betweenness,and the clustering coefficient).network resilience,the ratio between global efficiency and centralization,was stable with colony size but increased in the presence of broods,presumably in response to the nutritional needs of larvae.Individual metrics highlighted the major role of foragers in food dissemination.In addition,a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics.networks appeared to be hierarchical rather than random or centralized exclusively around foragers.Finally,our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.

关键词： insects network evolution self-organization social evolution social network analyses

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Information-Defined networks:A Communication network Approach for network Studies

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China Communications 2021年第7期18卷 197-210页

作者： Wenjie Jia Tao Jiang School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhan 430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China

The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.

关键词： network data analysis label detection complex network communication network network evolution

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Predictive Characteristics of Co-authorship networks: Comparing the Unweighted, Weighted, and Bipartite Cases

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Journal of Data and Information Science 2016年第3期1卷 59-78页

作者： Raf Guns Centre for R&D Monitoring (ECOOM) University of Antwerp

Purpose： This study aims to answer the question to what extent different types of networks can be used to predict future co-authorship among authors.Design/methodology/approach： We compare three types ot networks： unwelgntea networks, in which a link represents a past collaboration; weighted networks, in which links are weighted by the number of joint publications; and bipartite author-publication networks. The analysis investigates their relation to positive stability, as well as their potential in predicting links in future versions of the co-authorship network. Several hypotheses are tested.Findings： Among other results, we find that weighted networks do not automatically lead to better predictions. Bipartite networks, however, outperform unweighted networks in almost all cases. Research limitations： Only two relatively small case studies are considered Practical implications： The study suggests that future link prediction studies on networks should consider using the bipartite network as a training network. Originality/value： This is the first systematic comparison of unweighted, weighted, and bipartite training networks in link prediction.

关键词： network evolution Link prediction Weighted networks Bipartite networks Two-mode networks

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Review of Innovation networks Research

Review of Innovation Networks Research

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作者： Shiping Guan Ranran Du School of Economics and Management Guangxi University of Science and Technology

Due to the wide application of information technology,the speed of technology update is getting faster and faster.Innovation network is very important to the development of industry.So,innovation network is the hot spot of innovation research now.Through the analysis of the existing literature,this paper introduces the meaning,structural characteristics,research and development status of innovation network and the research content of innovation network evolution path.And puting forward the prospect of future research trend.

关键词： innovation network network structure network evolution

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国际复杂工程项目合作网络演化研究

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管理科学 2021年第11期

作者：张宇翔赵国堂周国华何海艳郭捷楠

以2000-2020年中国工程企业参与的国际工程项目为样本，探索了国际复杂工程项目组织间合作演化机制，从动态网络视角分析了全生命周期下国际复杂工程项目组织网络关系。结果表明：企业在国际复杂工程项目合作中形成了稳定的合作网络关... 详细信息

以2000-2020年中国工程企业参与的国际工程项目为样本，探索了国际复杂工程项目组织间合作演化机制，从动态网络视角分析了全生命周期下国际复杂工程项目组织网络关系。结果表明：企业在国际复杂工程项目合作中形成了稳定的合作网络关系，合作网络规模逐渐扩大，但合作网络密度和企业可合作程度未显著增加；国际承包商和供应方占据合作网络中心位置，带动设计方和咨询方参与到合作网络中，形成全产业链“走出去”的国际复杂工程项目合作模式；企业通过参与合作网络获取核心资源、信息和能力，提升项目整体合作绩效、企业市场份额及国际市场竞争力。

关键词：国际工程项目合作网络网络演化　　international engineering project cooperative networks network evolution

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新创企业联盟网络的动态演化

企业管理研究

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企业管理研究 2014年第3期

作者：彭伟符正平

新创企业联盟网络动态演化的内在机理在理论上缺乏更细致的诠释，鉴于此，对广东省3家新创企业进行探索性案例研究，探讨新创企业在不同发展阶段联盟网络动态演化的特征及其驱动因素，旨在揭示新创企业联盟网络的动态演化机理。研究结... 详细信息

新创企业联盟网络动态演化的内在机理在理论上缺乏更细致的诠释，鉴于此，对广东省3家新创企业进行探索性案例研究，探讨新创企业在不同发展阶段联盟网络动态演化的特征及其驱动因素，旨在揭示新创企业联盟网络的动态演化机理。研究结果表明：新创企业在不同发展阶段其联盟网络的关系强度、网络位置、网络异质性都会发生动态演化，企业战略类型以及外部环境不确定性是影响新创企业联盟网络动态演化的关键性驱动因素。

关键词：新创企业联盟网络网络演化　　new venture alliance network network evolution

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