26,315 research outputs found

    Shapes of interacting RNA complexes

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    Shapes of interacting RNA complexes are studied using a filtration via their topological genus. A shape of an RNA complex is obtained by (iteratively) collapsing stacks and eliminating hairpin loops. This shape-projection preserves the topological core of the RNA complex and for fixed topological genus there are only finitely many such shapes.Our main result is a new bijection that relates the shapes of RNA complexes with shapes of RNA structures.This allows to compute the shape polynomial of RNA complexes via the shape polynomial of RNA structures. We furthermore present a linear time uniform sampling algorithm for shapes of RNA complexes of fixed topological genus.Comment: 38 pages 24 figure

    Evidence for HI replenishment in massive galaxies through gas accretion from the cosmic web

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    We examine the H i -to-stellar mass ratio (H i fraction) for galaxies near filament backbones within the nearby Universe (d < 181 Mpc). This work uses the 6 degree Field Galaxy Survey (6dFGS) and the Discrete Persistent Structures Extractor (DisPerSE) to define the filamentary structure of the local cosmic web. H i spectral stacking of H i Parkes All Sky Survey (HIPASS) observations yield the H i fraction for filament galaxies and a field control sample. The H i fraction is measured for different stellar masses and 5th nearest neighbour projected densities (ÎŁ5) to disentangle what influences cold gas in galaxies. For galaxies with stellar masses log(M⋆) ≀ 11 M⊙ in projected densities 0 ≀ ÎŁ5 < 3 galaxies Mpc−2, all H i fractions of galaxies near filaments are statistically indistinguishable from the control sample. Galaxies with stellar masses log(M⋆) ≄ 11 M⊙ have a systematically higher H i fraction near filaments than the control sample. The greatest difference is 0.75 dex, which is 5.5σ difference at mean projected densities of 1.45 galaxies Mpc−2. We suggest that this is evidence for massive galaxies accreting cold gas from the intra-filament medium which can replenish some H i gas. This supports cold mode accretion where filament galaxies with a large gravitational potential can draw gas from the large scale structure

    Geometric detection of hierarchical backbones in real networks

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    Hierarchies permeate the structure of real networks, whose nodes can be ranked according to different features. However, networks are far from treelike structures and the detection of hierarchical ordering remains a challenge, hindered by the small-world property and the presence of a large number of cycles, in particular clustering. Here, we use geometric representations of undirected networks to achieve an enriched interpretation of hierarchy that integrates features defining the popularity of nodes and similarity between them, such that the more similar a node is to a less popular neighbor the higher the hierarchical load of the relationship. The geometric approach allows us to measure the local contribution of nodes and links to the hierarchy within a unified framework. Additionally, we propose a link filtering method, the similarity filter, able to extract hierarchical backbones containing the links that represent statistically significant deviations with respect to the maximum entropy null model for geometric heterogeneous networks. We applied our geometric approach to the detection of similarity backbones of real networks in different domains and found that the backbones preserve local topological features at all scales. Interestingly, we also found that similarity backbones favor cooperation in evolutionary dynamics modeling social dilemmas

    Determining the Solution Space of Vertex-Cover by Interactions and Backbones

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    To solve the combinatorial optimization problems especially the minimal Vertex-cover problem with high efficiency, is a significant task in theoretical computer science and many other subjects. Aiming at detecting the solution space of Vertex-cover, a new structure named interaction between nodes is defined and discovered for random graph, which results in the emergence of the frustration and long-range correlation phenomenon. Based on the backbones and interactions with a node adding process, we propose an Interaction and Backbone Evolution Algorithm to achieve the reduced solution graph, which has a direct correspondence to the solution space of Vertex-cover. By this algorithm, the whole solution space can be obtained strictly when there is no leaf-removal core on the graph and the odd cycles of unfrozen nodes bring great obstacles to its efficiency. Besides, this algorithm possesses favorable exactness and has good performance on random instances even with high average degrees. The interaction with the algorithm provides a new viewpoint to solve Vertex-cover, which will have a wide range of applications to different types of graphs, better usage of which can lower the computational complexity for solving Vertex-cover
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