首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 156 毫秒
1.
中心化分析有助于识别复杂网络中的重要节点,已经被广泛应用于代谢网络研究中。当前,人们已经提出了多种中心化指标,然而如何合理地综合使用它们是一个严峻的挑战。本文使用主成分分析来整合多种中心化方法。首先简单介绍了主成分分析的基本概念及其原理等,随后构造了人类代谢网络的巨强连通成分,并使用10种中心化指标计算了该模型中各代谢物的中心化值作为样本进行主成分分析。最后,我们以第一主成分为例,论证了主成分分析可以合理地整合多种中心化方法用于代谢网络研究。  相似文献   

2.
复杂网络的中心化有助于发现复杂网络中的重要节点,因而具有重要的应用价值。将中心化的研究推广到了加权网络,首先在一个小的加权网络模型上刻画了几种重要的中心化指标,通过定量分析,指出了不同中心化指标的特点;并将三种节点重要性指标应用于BBV网络,分别对这三种中心化指标最大的节点进行目标免疫,通过模拟病毒传播趋势,得出节点的强度指标对这种网络的传播影响最大。  相似文献   

3.
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。  相似文献   

4.
针对基于耦合系数的无标度网络演化模型中的节点进行中心化研究,首先对常用的中心化指标进行了分析,接着对经典的无标度(BA)模型和演化的BA-S模型中各节点的几种指标进行了累积概率分布研究,最后对两种模型的中心化程度和效率进行了中心化测试对比研究,结果证明,演化的BA-S模型较BA模型具有更强的鲁棒性以及抗故障的能力。  相似文献   

5.
社团结构分析有助于识别代谢网络中的功能模块,有助于理解代谢网络的结构和功能关系,是代谢网络研究领域的一个重要研究课题。然而,当前的社团结构分析方法均依赖于对网络中的节点进行聚类分析,导致每个节点只能属于某一个社团。采用了一种对复杂网络中的链接进行聚类分析的方法,对高质量金黄色葡萄球菌代谢网络模型的巨强连通体进行了社团结构分析,得到了10个具有生物学意义的功能模块,结果表明链接聚类可用于识别新陈代谢网络中的功能社团。  相似文献   

6.
发现复杂网络中最具影响力的节点,有助于分析和控制网络中的信息传播,具有重要的理论意义和实用价值.传统的确定节点影响力的方法大多基于网络的邻接矩阵、拓扑结构等,普遍存在数据维度高和数据稀疏的问题,基于网络表征学习,本文提出了一种局部中心性指标来辨识网络中高影响节点(NLC),首先采用DeepWalk算法,把高维网络中的节...  相似文献   

7.
图(或复杂网络)是大规模代谢网络研究的重要工具。传统上,主要使用代谢物图研究代谢网络,特别是人类的代谢网络。本文则使用反应图来研究人类的代谢网络,即:如果反应x的某个代谢产物是反应Y的某个代谢底物,则将反应x链接到反应Y。首先,从公开发表的文献获取了人类的反应网络,它包含了1099个节点和5208个弧。然后,根据"蝴蝶结"的结构分解方法,提取了人类的反应网络巨强组成部分,它包含了682个节点和4119弧。此外,研究了人类代谢网络反应图巨强组成部分的全局结构特性,结果表明它是一个"小世界","无尺度"和"自相似"网络。最后,依据10种不同的中心化分析方法(度,偏心率,紧密度,发散性,质心值,最短路径介数,.Katz状态,交易,网页排名和HITS中心),我们将另一研究重心放在了人类代谢网络反应图巨强组成部分的反应中心性分析方面,并确定了前15个关键反应(R00351b,R00256a,R00220a,R00253a,R00352b,R01177b,R00181a,R00344a,R00355b,R00485b,R03778b,R03858b,R03991b,R04742b和.R04747b)。  相似文献   

8.
许晓东  李刚  杨燕 《计算机应用研究》2012,29(12):4618-4621
针对非结构去中心化的P2P网络可能作为DDoS引擎而产生大规模的网络攻击,提出了一种基于人工免疫(AIS)的方法来对非结构去中心化的P2P网络中的恶意节点进行免疫处理。通过在非结构去中心化的P2P网络中的节点上构建人工免疫系统,利用抗体和抗原之间天然的亲和关系,以及抗体不断进化的特点,实时计算由返回查询消息的节点提供的资源信息而进行请求得到的请求结果状态序列与检测器中的对应节点的请求状态序列特征之间的亲和力,并检测出恶意节点。在NS2仿真平台上通过修改GnuSim插件,对非结构去中心化的P2P网络中节点的人工免疫系统进行模拟仿真,实验仿真验证了该方法的可行性,且能够有效地降低非结构去中心化P2P网络中恶意节点产生的DDoS攻击程度。  相似文献   

9.
许晓东  程建国  朱士瑞 《计算机应用》2011,31(12):3343-3345
僵尸网络结构的不断改进对网络安全造成了极大的威胁,如何深入研究其结构本身的固有性质对抵御该种攻击方式显得尤为重要。从复杂网络的角度模拟非结构化P2P僵尸网络,通过定义度量标准并应用网络中心化指标分析非结构化P2P僵尸网络面对节点失效时的鲁棒性。实验结果表明,非结构化P2P僵尸网络在面对随机节点失效时其鲁棒性较强,而面对高中心化节点失效时其鲁棒性将会迅速降低。  相似文献   

10.
近几年,复杂网络的研究正成为广泛关注的热点,代谢网络是复杂网络的一个例子。本文以产甲烷的常温古细菌Methanosarcina acetivorans(M.acetivorans)和嗜热古细菌Methanopyrus kandleri(M.kandleri)的代谢网络为对象,从拓扑参数以及模块化两方面进行比较研究。结果表明:M.acetivorans与M.kandleri的代谢网络均具有较高的模块化结构。同时发现它们模块化后的代谢网络中的Hub模块均属于氨基酸代谢和碳水化合物代谢,表明这些网络模块均具有一定的功能意义。最后将Hub模块与最紧密的k-核心网络相比较,发现它们节点完全相同,此结果表明代谢网络的最紧密k-核心网络部分也是不同网络比较的重要因素。  相似文献   

11.
Centrality is one of the most important fields of social network research. To date, some centrality measures based on topological features of nodes in social networks have been proposed in which the importance of nodes is investigated from a certain point of view. Such measures are one dimensional and thus not feasible for measuring sociological features of nodes. Given that the main basis of Social Network Analysis (SNA) is related to social issues and interactions, a novel procedure is hereby proposed for developing a new centrality measure, named Sociability Centrality, based on the TOPSIS method and Genetic Algorithm (GA). This new centrality is not only based on topological features of nodes, but also a representation of their psychological and sociological features that is calculable for large size networks (e.g. online social networks) and has high correlation with the nodes' social skill questionnaire scores. Finally, efficiency of the proposed procedure for developing sociability centrality was tested via implementation on the Abrar Dataset. Our results show that this centrality measure outperforms its existing counterparts in terms of representing the social skills of nodes in a social network.  相似文献   

12.
Centrality in social network is one of the major research topics in social network analysis. Even though there are more than half a dozen methods to find centrality of a node, each of these methods has some drawbacks in one aspect or the other. This paper analyses different centrality calculation methods and proposes a new swarm based method named Flocking Based Centrality for Social network (FBCS). This new computation technique makes use of parameters that are more realistic and practical in online social networks. The interactions between nodes play a significant role in determining the centrality of node. The new method has been calculated both empirically as well as experimentally. The new method is tested, verified and validated for different sets of random networks and benchmark datasets. The method has been correlated with other state of the art centrality measures. The new centrality measure is found to be realistic and suits well with online social networks. The proposed method can be used in applications such as finding the most prestigious node and for discovering the node which can influence maximum number of users in an online social network. FBCS centrality has higher Kendall’s tau correlation when compared with other state of the art centrality methods. The robustness of the FBCS centrality is found to be better than other centrality measures.  相似文献   

13.
Centrality metrics have proven to be of a major interest when analyzing the structure of networks. Given modern-day network sizes, fast algorithms for estimating these metrics are needed. This paper proposes a computation framework (named Filter-Compute-Extract) that returns an estimate of the top-k most important nodes in a given network. We show that considerable savings in computation time can be achieved by first filtering the input network based on correlations between cheap and more costly centrality metrics. Running the costly metric on the smaller resulting filtered network yields significant gains in computation time. We examine the complexity improvement due to this heuristic for classic centrality measures, as well as experimental results on well-studied public networks.  相似文献   

14.
丁德武  陆克中  须文波  吴璞  黄海生 《计算机工程》2010,36(13):162-163,166
比较几种常用的社团结构分析方法,讨论它们在代谢网络分析中的不足之处。模拟退火算法在代谢网络模块分析中具有一定优势,选用该算法分析苏云金杆菌代谢网络巨强连通体中的功能模块,并将所得的结果与KEGG数据库中的途径信息进行对比研究,发现大部分的模块都对应于1~2个KEGG途径。进一步的研究表明这些模块均具备重要的生物学功能意义。  相似文献   

15.
由于缺乏详尽的热力学参数,基于网络拓扑的代谢途径分析是现阶段最重要的途径分析方法。首先简单地介绍了基于网络的途径分析方法发展简史,随后着重说明了基于凸分析的两种代谢途径分析方法:基元模式和极端途径及它们之间的异同,并详细阐述了这两种方法的具体应用。最后,使用极端途径分析了苏云金杆菌的PHB代谢。结果表明,除了传统的途径,还存在一些新颖的途径可用于PHB合成。  相似文献   

16.
Ensemble of classifiers can improve classification accuracy by combining several models. The fusion method plays an important role in the ensemble performance. Usually, a criterion for weighting the decision of each ensemble member is adopted. Frequently, this can be done using some heuristic based on accuracy or confidence. Then, the used fusion rule must consider the established criterion for providing a most reliable ensemble output through a kind of competition among the ensemble members. This article presents a new ensemble fusion method, named centrality score-based fusion, which uses the centrality concept in the context of social network analysis (SNA) as a criterion for the ensemble decision. Centrality measures have been applied in the SNA to measure the importance of each person inside of a social network, taking into account the relationship of each person with all others. Thus, the idea is to derive the classifier weight considering the overall classifier prominence inside the ensemble network, which reflects the relationships among pairs of classifiers. We hypothesized that the prominent position of a classifier based on its pairwise relationship with the other ensemble members could be its weight in the fusion process. A robust experimental protocol has confirmed that centrality measures represent a promising strategy to weight the classifiers of an ensemble, showing that the proposed fusion method performed well against the literature.  相似文献   

17.
Real technological, social and biological networks evolve over time. Predicting their future topology has applications to epidemiology, targeted marketing, network reliability and routing in ad hoc and peer-to-peer networks. The key problem for such applications is usually to identify the nodes that will be in more important positions in the future. Previous researchers had used ad hoc prediction functions. In this paper, we evaluate ways of predicting a node’s future importance under three important metrics, namely degree, closeness centrality, and betweenness centrality, using empirical data on human contact networks collected using mobile devices. We find that node importance is highly predictable due to both periodic and legacy effects of human social behaviour, and we design reasonable prediction functions. However human behaviour is not the same in all circumstances: the centrality of students at Cambridge is best correlated both daily and hourly, no doubt due to hourly lecture schedules, while academics at conferences exhibit rather flat closeness centrality, no doubt because conference attendees are generally trying to speak to new people at each break. This highlights the utility of having a number of different metrics for centrality in dynamic networks, so as to identify typical patterns and predict behaviour. We show that the best-performing prediction functions are 25% more accurate on average than simply using the previous centrality value. These prediction functions can be efficiently computed in linear time, and are thus practical for processing dynamic networks in real-time.  相似文献   

18.
针对车载自组织网络(VANET)拓扑结构的动态性特征,基于车辆换道功能的智能驾驶移动模型,应用VanetMobiSim仿真软件详细研究车载自组织网络拓扑结构的动态中心性。构建VANET时序网络模型,建立基于衰落因子和信息存储转发指数的动态中心性评价方法,该方法不仅能够描述当前网络拓扑与历史网络拓扑之间的联系,而且能够刻画VANET中信息的存储转发机制;最后,通过仿真实验分析了VANET动态中心性。结果表明虽然VANET拓扑结构的动态中心性随着衰落因子和信息存储转发指数的变化而变化,但重要节点整体的排名基本保持相对稳定的状态。该结论有助于更好地确定信息传播的中继节点,实现信息的成功投递,而且为VANET拓扑结构的抗毁性提供指导。  相似文献   

19.
In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance of a node in a network, its sensitivity represents the importance of the relationship between this and all other nodes in the network. We have derived an analytical solution that extracts the sensitivity as the derivative of centrality with respect to degree for two centrality metrics based on feedback and random walks. We show that these sensitivities are good indicators of the distribution of centrality in the network, and how changes are expected to be propagated if we introduce changes to the network. These metrics also help us simplify a complex network in a way that retains the main structural properties and that results in trustworthy, readable diagrams. Sensitivity is also a key concept for uncertainty analysis of social networks, and we show how our approach may help analysts gain insight on the robustness of key network metrics. Through a number of examples, we illustrate the need for measuring sensitivity, and the impact it has on the visualization of and interaction with social and other scale-free networks.  相似文献   

20.
Goals are desired states that an individual tries to attain. The process of achieving a goal can be represented as interlinked means-end chains of user goals that have been traditionally visualized as hierarchies. Evidence in recent literature suggests that a network structure would be more appropriate and provide insight into a user's process of seeking a goal. We investigated user goal means-end chains for the eBay online auction system, and produced its structure as a goal network. To analyze this network and assess the importance of various goals, social network analysis measures were used (specifically, degree and flow-betweenness centrality). In addition, goal networks for users with low and high IS value were created and differences in goal importance in the two groups were considered. Results revealed that the most important user goals are closely related to key features of the auction system; users with high IS value want to use eBay to buy, sell, and bid for products, while users with low IS value seem to avoid using eBay because of uncertain price bidding. As such, the results of our study suggest that differences in IS value may be due to differences in IS usage. IS designers, marketers, and providers of online auction system can use our findings to design and promote better systems for their users.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号