1,721,028 research outputs found
Inflammatory bowel disease biomarkers revealed by the human gut microbiome network
No full textInflammatory bowel diseases (IBDs) are complex medical conditions in which the gut microbiota is attacked by the immune system of genetically predisposed subjects when exposed to yet unclear environmental factors. The complexity of this class of diseases makes them suitable to be represented and studied with network science. In this paper, the metagenomic data of control, Crohn’s disease, and ulcerative colitis subjects’ gut microbiota were investigated by representing this data as correlation networks and co-expression networks. We obtained correlation networks by calculating Pearson’s correlation between gene expression across subjects. A percolation-based procedure was used to threshold and binarize the adjacency matrices. In contrast, co-expression networks involved the construction of the bipartite subjects-genes networks and the monopartite genes-genes projection after binarization of the biadjacency matrix. Centrality measures and community detection were used on the so-built networks to mine data complexity and highlight possible biomarkers of the diseases. The main results were about the modules of Bacteroides, which were connected in the control subjects’ correlation network, Faecalibacterium prausnitzii, where co-enzyme A became central in IBD correlation networks and Escherichia coli, whose module has different patterns of integration within the whole network in the different diagnoses
Evidence of scale-free clusters of vegetation in tropical rainforests
Full text linkTropical rainforests exhibit a rich repertoire of spatial patterns emerging from the intricate relationship between the microscopic interaction between species. In particular, the distribution of vegetation clusters can shed much light on the underlying process regulating the ecosystem. Analyzing the distribution of vegetation clusters at different resolution scales, we show the first robust evidence of scale-invariant clusters of vegetation, suggesting the coexistence of multiple intertwined scales in the collective dynamics of tropical rainforests. We use field data and computational simulations to confirm our hypothesis, proposing a predictor that could be particularly interesting to monitor the ecological resilience of the world\u27s \u27green lungs\u27.6 pages, 5 figures and Supplementary Informatio
Laplacian renormalization group: an introduction to heterogeneous coarse-graining
Full text linkThe renormalization group (RG) constitutes a fundamental framework in modern theoretical physics. It allows the study of many systems showing states with large-scale correlations and their classification into a relatively small set of universality classes. The RG is the most powerful tool for investigating organizational scales within dynamic systems. However, the application of RG techniques to complex networks has presented significant challenges, primarily due to the intricate interplay of correlations on multiple scales. Existing approaches have relied on hypotheses involving hidden geometries and based on embedding complex networks into hidden metric spaces. Here, we present a practical overview of the recently introduced Laplacian RG (LRG) for heterogeneous networks. First, we present a brief overview that justifies the use of the Laplacian as a natural extension of well-known field theories to analyze spatial disorder. We then draw an analogy to traditional real-space RG procedures, explaining how the LRG generalizes the concept of 'Kadanoff supernodes' as block nodes that span multiple scales. These supernodes help mitigate the effects of cross-scale correlations due to small-world properties. Additionally, we rigorously define the LRG procedure in momentum space in the spirit of the Wilson RG. Finally, we show different analyses for the evolution of network properties along the LRG flow following structural changes when the network is properly reduced
Laplacian Renormalization Group for heterogeneous networks
Full text linkThe renormalization group is the cornerstone of the modern theory of
universality and phase transitions, a powerful tool to scrutinize symmetries
and organizational scales in dynamical systems. However, its network
counterpart is particularly challenging due to correlations between intertwined
scales. To date, the explorations are based on hidden geometries hypotheses.
Here, we propose a Laplacian RG diffusion-based picture in complex networks,
defining both the Kadanoff supernodes' concept, the momentum space procedure,
\emph{\'a la Wilson}, and applying this RG scheme to real networks in a natural
and parsimonious way.Comment: 7 pages, 4 figures, and Supplementary Informatio
Multi-scale Laplacian community detection in heterogeneous networks
Full text linkHeterogeneous and complex networks represent intertwined interactions between real-world elements or agents. Determining the multiscale mesoscopic organization of clusters and intertwined structures is still a fundamental and open problem of complex network theory. By taking advantage of the recent Laplacian renormalization group (LRG), we scrutinize information diffusion pathways throughout networks to shed further light on this issue. Based on internode communicability, our definition provides a clear-cut framework for resolving the multiscale mesh of structures in complex networks, disentangling their intrinsic arboreal architecture. As it does not consider any topological null-model assumption, the LRG naturally permits the introduction of scale-dependent optimal partitions. Moreover, we demonstrate the existence of a particular class of nodes, called metastable nodes, that switch regions to which they belong at different scales, likely playing a pivotal role in cross-regional communication and, therefore, in managing macroscopic effects of the whole network
Characterizing spatial point processes by percolation transitions
Full text linkA set of discrete individual points located in an embedding continuum space
can be seen as percolating or non-percolating, depending on the radius of the
discs/spheres associated with each of them. This problem is relevant in
theoretical ecology to analyze, e.g., the spatial percolation of a tree species
in a tropical forest or a savanna. Here, we revisit the problem of aggregating
random points in continuum systems (from to dimensional Euclidean
spaces) to analyze the nature of the corresponding percolation transition in
spatial point processes. This problem finds a natural description in terms of
the canonical ensemble but not in the usual grand-canonical one, customarily
employed to describe percolation transitions. This leads us to analyze the
question of ensemble equivalence and study whether the resulting canonical
continuum percolation transition shares its universal properties with standard
percolation transitions, analyzing diverse homogeneous and heterogeneous
spatial point processes. We, therefore, provide a powerful tool to characterize
and classify a vast class of natural point patterns, revealing their
fundamental properties based on percolation phase transitions.Comment: 22 pages, 13 figure
Laplacian paths in complex networks: information core emerges from entropic transitions
Full text linkComplex networks usually exhibit a rich architecture organized over multiple
intertwined scales. Information pathways are expected to pervade these scales
reflecting structural insights that are not manifest from analyses of the
network topology. Moreover, small-world effects correlate with the different
network hierarchies complicating the identification of coexisting mesoscopic
structures and functional cores. We present a communicability analysis of
effective information pathways throughout complex networks based on information
diffusion to shed further light on these issues. We employ a variety of
brand-new theoretical techniques allowing for: (i) bring the theoretical
framework to quantify the probability of information diffusion among nodes,
(ii) identify critical scales and structures of complex networks regardless of
their intrinsic properties, and (iii) demonstrate their dynamical relevance in
synchronization phenomena. By combining these ideas, we evidence how the
information flow on complex networks unravels different resolution scales.
Using computational techniques, we focus on entropic transitions, uncovering a
generic mesoscale object, the information core, and controlling information
processing in complex networks. Altogether, this study sheds much light on
allowing new theoretical techniques paving the way to introduce future
renormalization group approaches based on diffusion distances.Comment: 12 pages, 6 figures. To be published in Phys. Rev. Re
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
