Inferring Meaningful Communities from Topology-Constrained Correlation Networks

Community structure detection is an important tool in graph analysis. This can be done, among other ways, by solving for the partition set which optimizes the modularity scores . Here it is shown that topological constraints in correlation graphs induce over-fragmentation of community structures. A refinement step to this optimization based on Linear Discriminant Analysis (LDA) and a statistical test for significance is proposed. In structured simulation constrained by topology, this novel approach performs better than the optimization of modularity alone. This method was also tested with two empirical datasets: the Roll-Call voting in the 110th US Senate constrained by geographic adjacency, and a biological dataset of 135 protein structures constrained by inter-residue contacts. The former dataset showed sub-structures in the communities that revealed a regional bias in the votes which transcend party affiliations. This is an interesting pattern given that the 110th Legislature was assumed to be a highly polarized government. The -amylase catalytic domain dataset (biological dataset) was analyzed with and without topological constraints (inter-residue contacts). The results without topological constraints showed differences with the topology constrained one, but the LDA filtering did not change the outcome of the latter. This suggests that the LDA filtering is a robust way to solve the possible over-fragmentation when present, and that this method will not affect the results where there is no evidence of over-fragmentation.     

Emergence of Multiplex Communities in Collaboration Networks

Community structures in collaboration networks reflect the natural tendency of individuals to organize their work in groups in order to better achieve common goals. In most of the cases, individuals exploit their connections to introduce themselves to new areas of interests, giving rise to multifaceted collaborations which span different fields. In this paper, we analyse collaborations in science and among movie actors as multiplex networks, where the layers represent respectively research topics and movie genres, and we show that communities indeed coexist and overlap at the different layers of such systems. We then propose a model to grow multiplex networks based on two mechanisms of intra and inter-layer triadic closure which mimic the real processes by which collaborations evolve. We show that our model is able to explain the multiplex community structure observed empirically, and we infer the strength of the two underlying social mechanisms from real-world systems. Being also able to correctly reproduce the values of intra-layer and inter-layer assortativity correlations, the model contributes to a better understanding of the principles driving the evolution of social networks.     

Netgram: Visualizing Communities in Evolving Networks

Real-world complex networks are dynamic in nature and change over time. The change is usually observed in the interactions within the network over time. Complex networks exhibit community like structures. A key feature of the dynamics of complex networks is the evolution of communities over time. Several methods have been proposed to detect and track the evolution of these groups over time. However, there is no generic tool which visualizes all the aspects of group evolution in dynamic networks including birth, death, splitting, merging, expansion, shrinkage and continuation of groups. In this paper, we propose Netgram: a tool for visualizing evolution of communities in time-evolving graphs. Netgram maintains evolution of communities over 2 consecutive time-stamps in tables which are used to create a query database using the sql outer-join operation. It uses a line-based visualization technique which adheres to certain design principles and aesthetic guidelines. Netgram uses a greedy solution to order the initial community information provided by the evolutionary clustering technique such that we have fewer line cross-overs in the visualization. This makes it easier to track the progress of individual communities in time evolving graphs. Netgram is a generic toolkit which can be used with any evolutionary community detection algorithm as illustrated in our experiments. We use Netgram for visualization of topic evolution in the NIPS conference over a period of 11 years and observe the emergence and merging of several disciplines in the field of information processing systems.     

Cells Actively Stiffen Fibrin Networks by Generating Contractile Stress

During wound healing and angiogenesis, fibrin serves as a provisional extracellular matrix. We use a model system of fibroblasts embedded in fibrin gels to study how cell-mediated contraction may influence the macroscopic mechanical properties of their extracellular matrix during such processes. We demonstrate by macroscopic shear rheology that the cells increase the elastic modulus of the fibrin gels. Microscopy observations show that this stiffening sets in when the cells spread and apply traction forces on the fibrin fibers. We further show that the stiffening response mimics the effect of an external stress applied by mechanical shear. We propose that stiffening is a consequence of active myosin-driven cell contraction, which provokes a nonlinear elastic response of the fibrin matrix. Cell-induced stiffening is limited to a factor 3 even though fibrin gels can in principle stiffen much more before breaking. We discuss this observation in light of recent models of fibrin gel elasticity, and conclude that the fibroblasts pull out floppy modes, such as thermal bending undulations, from the fibrin network, but do not axially stretch the fibers. Our findings are relevant for understanding the role of matrix contraction by cells during wound healing and cancer development, and may provide design parameters for materials to guide morphogenesis in tissue engineering.     

Energy Spectral Behaviors of Communication Networks of Open-Source Communities

Large-scale online collaborative production activities in open-source communities must be accompanied by large-scale communication activities. Nowadays, the production activities of open-source communities, especially their communication activities, have been more and more concerned. Take CodePlex C # community for example, this paper constructs the complex network models of 12 periods of communication structures of the community based on real data; then discusses the basic concepts of quantum mapping of complex networks, and points out that the purpose of the mapping is to study the structures of complex networks according to the idea of quantum mechanism in studying the structures of large molecules; finally, according to this idea, analyzes and compares the fractal features of the spectra in different quantum mappings of the networks, and concludes that there are multiple self-similarity and criticality in the communication structures of the community. In addition, this paper discusses the insights and application conditions of different quantum mappings in revealing the characteristics of the structures. The proposed quantum mapping method can also be applied to the structural studies of other large-scale organizations.     

Identifying Communities and Key Vertices by Reconstructing Networks from Samples

Sampling techniques such as Respondent-Driven Sampling (RDS) are widely used in epidemiology to sample “hidden” populations, such that properties of the network can be deduced from the sample. We consider how similar techniques can be designed that allow the discovery of the structure, especially the community structure, of networks. Our method involves collecting samples of a network by random walks and reconstructing the network by probabilistically coalescing vertices, using vertex attributes to determine the probabilities. Even though our method can only approximately reconstruct a part of the original network, it can recover its community structure relatively well. Moreover, it can find the key vertices which, when immunized, can effectively reduce the spread of an infection through the original network.     

Information Networks in Amenity Transition Communities: A Comparative Case Study

Amenity transition, a major socio demographic trend in areas rich in natural resources, is characterized by economic and population growth as a result of retirement in-migration, increased rates of second home ownership, and increases in the number of industries that do not need to be proximate to a specific geographic location. Amenity transition is also characterized by increased intra-community conflict between long-term residents and in-migrants. This research analyzes whether the population growth accompanying amenity transition is associated with variations in the structure and characteristics of intra-community informational networks, as sociological theory would suggest. Methodologically, this is accomplished through a comparative analysis of the structure and characteristics of informational networks in three communities undergoing amenity transition. The analyses suggest population density is not related to either the structure of informational networks or the concentration of trust/distrust within them. When considered in conjunction with previous empirical work, these findings suggest the conflicts associated with amenity transition are more likely to arise because of conflicting value systems and ideologies as opposed to social structural changes in the communities themselves.     

Stability of Multispecies Bacterial Communities: Signaling Networks May Stabilize Microbiomes

Multispecies bacterial communities can be remarkably stable and resilient even though they consist of cells and species that compete for environmental resources. In silico models suggest that common signals released into the environment may help selected bacterial species cluster at common locations and that sharing of public goods (i.e. molecules produced and released for mutual benefit) can stabilize this coexistence. In contrast, unilateral eavesdropping on signals produced by a potentially invading species may protect a community by keeping invaders away from limited resources. Shared bacterial signals, such as those found in quorum sensing systems, may thus play a key role in fine tuning competition and cooperation within multi-bacterial communities. We suggest that in addition to metabolic complementarity, signaling dynamics may be important in further understanding complex bacterial communities such as the human, animal as well as plant microbiomes.     

Mapping Yoruba Networks: Power and Agency in the Making of Transnational Communities

Mapping Yoruba Networks: Power and Agency in the Making of Transnational Communities . Kamari Maxine Clarke. Durham, NC: Duke University Press, 2004. 345 pp.     

Generating disulfides with the Quiescin-sulfhydryl oxidases

The Quiescin-sulfhydryl oxidase (QSOX) family of flavoenzymes catalyzes the direct and facile insertion of disulfide bonds into unfolded reduced proteins with concomitant reduction of oxygen to hydrogen peroxide. This review discusses the chemical mechanism of these enzymes and the involvement of thioredoxin and flavin-binding domains in catalysis. The variability of CxxC motifs in the QSOX family is highlighted and attention is drawn to the steric factors that may promote efficient thiol/disulfide exchange during oxidative protein folding. The varied cellular location of these multi-domain sulfhydryl oxidases is reviewed and potential intracellular and extracellular roles are summarized. Finally, this review identifies important unresolved questions concerning this ancient family of sulfhydryl oxidases.     

Evaluating Communities of Practice and Knowledge Networks: A Systematic Scoping Review of Evaluation Frameworks

Communities of Practice (CoPs) are increasingly considered a part of ecohealth and other sectors such as health care, education, and business. However, there is little agreement on approaches to evaluate the influence and effectiveness of CoPs. The purpose of this review was to understand what frameworks and methods have been proposed or used to evaluate CoPs and/or knowledge networks. The review searched electronic databases in interdisciplinary, health, education, and business fields, and further collected references and forward citations from relevant articles. Nineteen articles with 16 frameworks were included in the synthesis. The purposes of the evaluation frameworks varied; while some focused on assessing the performance of CoPs, several frameworks sought to learn about CoPs and their critical success factors. Nine of the frameworks had been applied or tested in some way, most frequently to guide a case study. With limited applications of the frameworks, strong claims about generalizability could not be made. The review results can inform the development of tailored frameworks. However, there is a need for more detailed and targeted CoP evaluation frameworks, as many imperative CoP evaluation needs would be unmet by the available frameworks.     

Hospital Admission and Absence from Work Attributed to Asthma

Study of a 10% sample of hospital admissions for asthma in England and Wales shows that in each age and sex group deaths have increased by at least a half between 1959 and 1964, while for males aged 15–44 years they have doubled. The number of deaths in hospital has risen in a similar way, and hence the hospital fatality rate has not changed over this period. Since study of certified absences from work has shown no comparable increase, it is suggested that the increase has occurred in the number of attacks of severe asthma requiring admission to hospital.