Vertex importance extension of betweenness centrality algorithm

Variety of real-life structures can be simplified by a graph. Such simplification emphasizes the structure represented by vertices connected via edges. A common method for the analysis of the vertices importance in a network is betweenness centrality. The centrality is computed using the information about the shortest paths that exist in a graph. This approach puts the importance on the edges that connect the vertices. However, not all vertices are equal. Some of them might be more important than others or have more significant influence on the behavior of the network. Therefore, we introduce the modification of the betweenness centrality algorithm that takes into account the vertex importance. This approach allows the further refinement of the betweenness centrality score to fulfill the needs of the network better. We show this idea on an example of the real traffic network. We test the performance of the algorithm on the traffic network data from the city of Bratislava, Slovakia to prove that the inclusion of the modification does not hinder the original algorithm much. We also provide a visualization of the traffic network of the city of Ostrava, the Czech Republic to show the effect of the vertex importance adjustment. The algorithm was parallelized by MPI (http://www.mpi-forum.org/) and was tested on the supercomputer Salomon (https://docs.it4i.cz/) at IT4Innovations National Supercomputing Center, the Czech Republic.808726

A community based algorithm for deriving users' profiles from egocentrics networks: experiment on Facebook and DBLP

International audienceNowadays, social networks are more and more widely used as a solution for enriching users’ profiles in systems such as recommender systems or personalized systems. For an unknown user’s interest, the user’s social network can be a meaningful data source for deriving that interest. However, in the literature very few techniques are designed to meet this solution. Existing techniques usually focus on people individually selected in the user’s social network and strongly depend on each author’s objective. To improve these techniques, we propose using a community-based algorithm that is applied to a part of the user’s social network (egocentric network) and that derives a user social profile that can be reused for any purpose (e.g., personalization, recommendation). We compute weighted user’s interests from these communities by considering their semantics (interests related to communities) and their structural measures (e.g., centrality measures) in the egocentric network graph. A first experiment conducted in Facebook demonstrates the usefulness of this technique compared to individual-based techniques and the influence of structural measures (related to communities) on the quality of derived profiles. A second experiment on DBLP and the author’s social network Mendeley confirms the results obtained on Facebook and shows the influence of the density of egocentrics network on the quality of results

Cycle-centrality in complex networks

Networks are versatile representations of the interactions between entities in complex systems. Cycles on such networks represent feedback processes which play a central role in system dynamics. In this work, we introduce a measure of the importance of any individual cycle, as the fraction of the total information flow of the network passing through the cycle. This measure is computationally cheap, numerically well-conditioned, induces a centrality measure on arbitrary subgraphs and reduces to the eigenvector centrality on vertices. We demonstrate that this measure accurately reflects the impact of events on strategic ensembles of economic sectors, notably in the US economy. As a second example, we show that in the protein-interaction network of the plant Arabidopsis thaliana, a model based on cycle-centrality better accounts for pathogen activity than the state-of-art one. This translates into pathogen-targeted-proteins being concentrated in a small number of triads with high cycle-centrality. Algorithms for computing the centrality of cycles and subgraphs are available for download

Uncovering the overlapping community structure of complex networks in nature and society

Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections among the units they are made of. A key question is how to interpret the global organization of such networks as the coexistence of their structural subunits (communities) associated with more highly interconnected parts. Identifying these a priori unknown building blocks (such as functionally related proteins, industrial sectors and groups of people) is crucial to the understanding of the structural and functional properties of networks. The existing deterministic methods used for large networks find separated communities, whereas most of the actual networks are made of highly overlapping cohesive groups of nodes. Here we introduce an approach to analysing the main statistical features of the interwoven sets of overlapping communities that makes a step towards uncovering the modular structure of complex systems. After defining a set of new characteristic quantities for the statistics of communities, we apply an efficient technique for exploring overlapping communities on a large scale. We find that overlaps are significant, and the distributions we introduce reveal universal features of networks. Our studies of collaboration, word-association and protein interaction graphs show that the web of communities has non-trivial correlations and specific scaling properties.Comment: The free academic research software, CFinder, used for the publication is available at the website of the publication: http://angel.elte.hu/clusterin

A centrality measure for cycles and subgraphs II

In a recent work we introduced a measure of importance for groups of vertices in a complex network. This centrality for groups is always between 0 and 1 and induces the eigenvector centrality over vertices. Furthermore, its value over any group is the fraction of all network flows intercepted by this group. Here we provide the rigorous mathematical constructions underpinning these results via a semi-commutative extension of a number theoretic sieve. We then established further relations between the eigenvector centrality and the centrality proposed here, showing that the latter is a proper extension of the former to groups of nodes. We finish by comparing the centrality proposed here with the notion of group-centrality introduced by Everett and Borgatti on two real-world networks: the Wolfe’s dataset and the protein-protein interaction network of the yeast Saccharomyces cerevisiae. In this latter case, we demonstrate that the centrality is able to distinguish protein complexe

Adult-onset Leigh syndrome linked to the novel stop codon mutation m.6579G>A in MT-CO1

Adult-onset Leigh syndrome is a rare but important manifestation of mitochondrial disease. We report a 17 year old female who presented with subacute encephalopathy, brainstem and extrapyramidal signs, raised CSF lactate, and symmetrical hyperintensities in the basal ganglia on T2-weighted cerebral MRI. The presence of cytochrome c oxidase deficient fibres in muscle tissue prompted sequencing of the entire mitochondrial genome which revealed the novel stop codon mutation m.6579G>A; p.Gly226X in MT-CO1. Here we present the case and review the clinicopathological and molecular spectrum of previously reported MT-CO1 truncating mutations

Disruption of PML Nuclear Bodies Is Mediated by ORF61 SUMO-Interacting Motifs and Required for Varicella-Zoster Virus Pathogenesis in Skin

Promyelocytic leukemia protein (PML) has antiviral functions and many viruses encode gene products that disrupt PML nuclear bodies (PML NBs). However, evidence of the relevance of PML NB modification for viral pathogenesis is limited and little is known about viral gene functions required for PML NB disruption in infected cells in vivo. Varicella-zoster virus (VZV) is a human alphaherpesvirus that causes cutaneous lesions during primary and recurrent infection. Here we show that VZV disrupts PML NBs in infected cells in human skin xenografts in SCID mice and that the disruption is achieved by open reading frame 61 (ORF61) protein via its SUMO-interacting motifs (SIMs). Three conserved SIMs mediated ORF61 binding to SUMO1 and were required for ORF61 association with and disruption of PML NBs. Mutation of the ORF61 SIMs in the VZV genome showed that these motifs were necessary for PML NB dispersal in VZV-infected cells in vitro. In vivo, PML NBs were highly abundant, especially in basal layer cells of uninfected skin, whereas their frequency was significantly decreased in VZV-infected cells. In contrast, mutation of the ORF61 SIMs reduced ORF61 association with PML NBs, most PML NBs remained intact and importantly, viral replication in skin was severely impaired. The ORF61 SIM mutant virus failed to cause the typical VZV lesions that penetrate across the basement membrane into the dermis and viral spread in the epidermis was limited. These experiments indicate that VZV pathogenesis in skin depends upon the ORF61-mediated disruption of PML NBs and that the ORF61 SUMO-binding function is necessary for this effect. More broadly, our study elucidates the importance of PML NBs for the innate control of a viral pathogen during infection of differentiated cells within their tissue microenvironment in vivo and the requirement for a viral protein with SUMO-binding capacity to counteract this intrinsic barrier

Sleep-wake sensitive mechanisms of adenosine release in the basal forebrain of rodents : an in vitro study

Adenosine acting in the basal forebrain is a key mediator of sleep homeostasis. Extracellular adenosine concentrations increase during wakefulness, especially during prolonged wakefulness and lead to increased sleep pressure and subsequent rebound sleep. The release of endogenous adenosine during the sleep-wake cycle has mainly been studied in vivo with microdialysis techniques. The biochemical changes that accompany sleep-wake status may be preserved in vitro. We have therefore used adenosine-sensitive biosensors in slices of the basal forebrain (BFB) to study both depolarization-evoked adenosine release and the steady state adenosine tone in rats, mice and hamsters. Adenosine release was evoked by high K+, AMPA, NMDA and mGlu receptor agonists, but not by other transmitters associated with wakefulness such as orexin, histamine or neurotensin. Evoked and basal adenosine release in the BFB in vitro exhibited three key features: the magnitude of each varied systematically with the diurnal time at which the animal was sacrificed; sleep deprivation prior to sacrifice greatly increased both evoked adenosine release and the basal tone; and the enhancement of evoked adenosine release and basal tone resulting from sleep deprivation was reversed by the inducible nitric oxide synthase (iNOS) inhibitor, 1400 W. These data indicate that characteristics of adenosine release recorded in the BFB in vitro reflect those that have been linked in vivo to the homeostatic control of sleep. Our results provide methodologically independent support for a key role for induction of iNOS as a trigger for enhanced adenosine release following sleep deprivation and suggest that this induction may constitute a biochemical memory of this state

Gold colloidal nanoparticle electrodeposition on a silicon surface in a uniform electric field

The electrodeposition of gold colloidal nanoparticles on a silicon wafer in a uniform electric field is investigated using scanning electron microscopy and homemade electrochemical cells. Dense and uniform distributions of particles are obtained with no aggregation. The evolution of surface particle density is analyzed in relation to several parameters: applied voltage, electric field, exchanged charge. Electrical, chemical, and electrohydrodynamical parameters are taken into account in describing the electromigration process