Search results for "Network Analysi"

showing 10 items of 243 documents

Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners

2012

The availability of large volumes of protein-protein interaction data has allowed the study of biological networks to unveil the complex structure and organization in the cell. It has been recognized by biologists that proteins interacting with each other often participate in the same biological processes, and that protein modules may be often associated with specific biological functions. Thus the detection of protein complexes is an important research problem in systems biology. In this review, recent graph-based approaches to clustering protein interaction networks are described and classified with respect to common peculiarities. The goal is that of providing a useful guide and referenc…

Structure (mathematical logic)Computer scienceSystems biologyCellData ScienceNanotechnologyComputational biologyProtein protein interaction networkBioinformatics network analysismedicine.anatomical_structuremedicineGraph (abstract data type)Lecture Notes in Computer ScienceCluster analysisProtein modulesBiological network
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Social Networks as an Approach to Systematic review

2019

Whether we are in the process of designing a new empirical study or our interest lies in conducting a review study, a solid literature review is needed to acquire an accurate idea of the current state of affairs with regard to a phenomenon of interest. Even if we can find contributions to the literature by entering keywords in search engines, we need tools that can help us to structure all the contributions encountered in terms of their interrelations and impact. This article presents social network analysis as such a tool. Although social network analysis is commonly thought of as a method in a particular empirical study, where individuals and groups of participants are studied, we can vie…

Structure (mathematical logic)lcsh:R5-920Empirical researchComputer scienceProcess (engineering)Field (Bourdieu)State of affairsContext (language use)lcsh:Medicine (General)CitationSocial network analysisData scienceHealth Professions Education
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An Analysis of the Internal Organization of Facebook Groups

2019

With the rapid development and growth of online social networks (OSNs), researchers have been pushed forward to improve the knowledge of these complex networks by analyzing several aspects, such as the types of social media, the structural properties of the network, or the interaction patterns among users. In particular, a relevant effort has been devoted to the study and identification of cohesive groups of users in OSNs (also referred as communities) because they are the basic building block of each OSN. While several research works on groups in OSNs have mainly focused on identifying the types of groups and the contents created by their members, the analysis of internal organizations of …

Structure (mathematical logic)social networksExploitSettore INF/01 - InformaticaComputer science020206 networking & telecommunications02 engineering and technologyComplex networkData scienceGroup organization; network centrality; social networks; tie strengthHuman-Computer InteractionIdentification (information)tie strengthModeling and Simulation0202 electrical engineering electronic engineering information engineeringGroup organizationnetwork centrality020201 artificial intelligence & image processingSocial mediaUse casesocial networkSocial network analysisSocial Sciences (miscellaneous)Internal organization
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"Master-Slave" Biological Network Alignment

2010

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. He…

Theoretical computer scienceBasis (linear algebra)business.industryComputer scienceFingerprint (computing)Process (computing)Master/slaveENCODETask (computing)Bioinformatics network analysisArtificial intelligencebusinessBiological networkOrganism
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Network Centralities and Node Ranking

2017

An important problem in network analysis is understanding how much nodes are important in order to “propagate” the information across the input network. To this aim, many centrality measures have been proposed in the literature and our main goal here is that of providing an overview of the most important of them. In particular, we distinguish centrality measures based on walks computation from those based on shortest-paths computation. We also provide some examples in order to clarify how these measures can be calculated, with special attention to Degree Centrality, Closeness Centrality and Betweennes Centrality.

Theoretical computer scienceCentrality measureNetwork topologyShortest pathSettore INF/01 - InformaticaComputer scienceBiological networkComputationNode (networking)Network topologySubgraph extractionNode centralityRankingShortest path problemCentralityBiological networkNetwork analysisNode neighborhoodNode ranking
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Statistically validated networks in bipartite complex systems.

2011

Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the pr…

Theoretical computer scienceComputer sciencelcsh:MedicineNetwork theorySocial and Behavioral SciencesBioinformaticsQuantitative Biology - Quantitative MethodsSociologyProtein Interaction Mappinglcsh:ScienceQuantitative Methods (q-bio.QM)MultidisciplinarySystems BiologyApplied MathematicsPhysicsStatisticsComplex SystemsGenomicsLink (geometry)Social NetworksSpecialization (logic)Interdisciplinary PhysicsBipartite graphProbability distributionResearch ArticleNetwork analysisPhysics - Physics and SocietyComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Type (model theory)BiologyModels BiologicalNetwork theory Statistical PhysicsStatistical MechanicsSet (abstract data type)Statistical MethodsBiologyStructure (mathematical logic)Statistical Physicslcsh:RComputational BiologyModels TheoreticalComparative GenomicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Biological sciencesNetwork theorylcsh:QNull hypothesisMathematicsPLoS ONE
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Asymmetric Comparison and Querying of Biological Networks

2011

Comparing and querying the protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform these tasks operate symmetrically, i.e., they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how the corresponding organism is biologically well characterized. In this paper a new idea is developed, that is, to exploit differences in the characterization of organisms at hand in order to devise methods for comparing their PPI networks. We use the PPI network (called Master) of the best characterized organism as a …

Theoretical computer scienceFinite-state machineMatching (graph theory)Computer scienceApplied MathematicsFingerprint (computing)Process (computing)Computational BiologyViterbi algorithmModels BiologicalAutomatonBioinformatics network analysissymbols.namesakeSequence Analysis ProteinLinearizationProtein Interaction MappingGeneticssymbolsProtein Interaction Domains and MotifsSequence AlignmentAlgorithmsBiological networkBiotechnologyIEEE/ACM Transactions on Computational Biology and Bioinformatics
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Approximate Matching over Biological RDF Graphs

2012

In the last few years, the amount of biological interaction data discovered and stored in public databases (e.g., KEGG [2]) considerably increased. To this aim, RDF is a powerful representation for interactions (or pathways), since they can be modeled as directed graphs, often referred to as biological networks, where nodes represent cellular components and the (labeled or unlabeled) edges correspond to interactions among components. Often for a given organism some components are known to be linked by well studied interactions. Such groups of components are called modules and they can be represented by sub-graphs in the corresponding biological network model. At today, one of the most impor…

Theoretical computer scienceGraph databaseComputer scienceSearch engine indexingcomputer.file_formatcomputer.software_genreGraphBioinformatics network analysisApproximate matchingIsomorphismRDFKEGGHeuristicscomputerBiological networkNetwork analysis
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Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

2021

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…

Theoretical computer scienceSettore INF/01 - InformaticaComputational complexity theorySocial networkComputer sciencebusiness.industryNode (networking)Complex networksComplex networkSocial network analysisK-pathBetweenness centralityCentrality measuresCorrelation coefficientsCentralitybusinessSocial network analysisClustering coefficient
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Social network analysis: the use of graph distances to compare artificial and criminal networks

2021

Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of s…

Theoretical computer sciencesocial network analysisSpectral distanceSettore INF/01 - InformaticaComputer sciencegraph theorySocial network analysis (criminology)social network analysiGraph theoryspectral distancenetwork modelCriminal networksCriminal networkGraph (abstract data type)Criminal networks social network analysis graph theory spectral distance network modelNetwork model
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