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364 results for “Network interaction”
Knowledge Graph Neural Network with Spatial-Aware Capsule for Drug-Drug Interaction Prediction
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Data from: Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles
The specialization of ecological networks provides important insights into possible consequences of biodiversity loss for ecosystem functioning. However, mostly mutualistic and antagonistic interactions of living organisms have been studied, whereas detritivore networks and their successional changes are largely unexplored. We studied the interactions of saproxylic (deadwood-dependent) beetles with their dead host trees. In a large-scale experiment, 764 logs of 13 tree species were exposed to analyse network structure of three trophic groups of saproxylic beetles over 3 successional years. We found remarkably high specialization of deadwood-feeding xylophages and lower specialization of fungivorous and predatory species. During deadwood succession, community composition, network specialization and network robustness changed differently for the functional groups. To reveal potential drivers of network specialization, we linked species' functional traits to their network roles, and tested for trait matching between plant (i.e. chemical compounds) and beetle (i.e. body size) traits. We found that both plant and animal traits are major drivers of species specialization, and that trait matching can be more important in explaining interactions than neutral processes reflecting species abundance distributions. High network specialization in the early successional stage and decreasing network robustness during succession indicate vulnerability of detritivore networks to reduced tree species diversity and beetle extinctions, with unknown consequences for wood decomposition and nutrient cycling.
Pollen transport networks reveal highly diverse and temporally stable plant-pollinator interactions in an Appalachian floral community
<p>Floral visitation alone has been typically used to characterize plant-pollinator interaction networks even though it ignores differences in the quality of floral visits (e.g. transport of pollen) and thus may overestimate the number and functional importance of pollinating interactions. However, how network structural properties differ between floral visitation and pollen transport networks is not well understood. Furthermore, the strength and frequency of plant-pollinator interactions may vary across fine temporal scales (within a single season) further limiting our predictive understanding of the drivers and consequences of plant-pollinator network structure. Thus, evaluating the structure of pollen transport networks and how they change within a flowering season may help increase our predictive understanding of the ecological consequences of plant-pollinator network structure. Here we compare plant-pollinator network structure using floral visitation and pollen transport data and evaluate within-season variation in pollen transport network structure in a diverse plant-pollinator community. Our results show that pollen transport networks provide a more accurate representation of the diversity of plant-pollinator interactions in a community but that floral visitation and pollen transport networks do not differ in overall network structure. Pollen transport network structure was relatively stable throughout the flowering season despite changes in plan and pollinator species composition. Overall, our study highlights the need to improve our understanding of the drivers of plant-pollinator network structure in order to more fully understand the process that govern the assembly of these interactions in nature.</p>
Figure datafiles for Network of hotspot interactions cluster tau amyloid folds
<p>Datafiles used to produce the figures for</p> <p>Network of hotspot interactions cluster tau amyloid folds</p>
Edge disturbance shapes liana diversity and abundance but not liana-tree interaction network patterns in moist semi-deciduous forests, Ghana
<p>Edge disturbance can drive liana community changes and alter liana-tree interaction networks, with ramifications for forest functioning. Understanding edge effects on liana community structure and liana-tree interactions is therefore essential for forest management and conservation. We evaluated the response of liana community structure and the patterns of liana-tree interaction structure to forest edge in two moist semi-deciduous forests in Ghana (Asenanyo and Suhuma Forest Reserves: AFR and SFR, respectively). Liana community structure and liana-tree interactions were assessed in 24 50 × 50 m randomly located plots in three forest sites in each forest: edge, interior and deep-interior established at 0-50 m, 200 m and 400 m from edge. Edge effects positively and negatively influenced liana diversity in forest edges of AFR and SFR, respectively. There was a positive influence of edge disturbance on liana abundance in both forests. We observed anti-nested structure in all the liana-tree networks in AFR, while no nestedness was observed in the networks in SFR. The networks in both forests were less connected, and thus more modular and specialised than their null models. Many liana and tree species were specialised, with specialisation tending to be symmetrical. The plant species played different roles in relation to modularity. Most of the species acted as peripherals (specialists), with only a few species having structural importance to the networks. The latter species group consisted of connectors (generalists) and hubs (highly connected generalists). Some of the species showed consistency in their roles across the sites, while the roles of other species changed. Generally, liana species co-occurred randomly on tree species in all the forest sites, except edge site in AFR where lianas showed positive co-occurrence. Our findings deepen our understanding of the response of liana communities and liana-tree interactions to forest edge disturbance, which are useful for managing forest edge.</p>
Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer
<p>This serves as the supplementary data repo for the paper, <em><a href="https://doi.org/10.1101/2023.09.04.556262">Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer</a>. </em></p> <p>The file structure is as follows:</p> <ul> <li>Splitpea rewired PPI networks for individual patient samples (files ending in `patient-rewired-networks.zip`). The networks are stored as dat files, which are tab delimited with one row per edge. Gene ids are reported as entrez id, the edge weights determine the directionality of the interaction (positive weights are potential gains, negative weights are edges likely lost). Chaos edges can have a positive or negative weight but will be indicated by a boolean value in the `chaos` column.</li> <li>The consensus networks (files ending in `consensus_networks`) are separated into two networks one for positive edges and one for negative edges present in at least 80% of tumor samples. These files are tab delimited files with one row per edge in the corresponding undirected weighted network. The following columns are included: <ul> <li>node1, node2: genes incident on the edge as entrez gene IDs</li> <li>mean_weight: average weight of edge across networks (where edge is present) used to build the consensus</li> <li>total_weight: sum of weights across networks (where edge is present) used to build the consensus</li> <li>num_graphs: # of networks where edge was present</li> <li>prop_graphs: # of networks where edge was present / total # of networks used to build the consensus</li> </ul> </li> <li>IRIS.zip: Splicing matrix spliced exon files from IRIS (Pan et al. <a href="https://doi.org/10.1073/pnas.2221116120">https://doi.org/10.1073/pnas.2221116120</a>). These are the initial inputs for the Splitpea run described in the paper.</li> <li>BRCA-psi.zip: precalculated PSI values for breast cancer samples as described in the paper</li> <li>PAAD-psi.zip: precalculated PSI values for pancreatic cancer samples as described in the paper</li> <li>*-centralities.zip: precalculated centralities for each patient network</li> <li>*-pickle.zip: network representations as pickle files</li> </ul>
Data from: Black Queen evolution and trophic interactions determine plasmid survival after the disruption of conjugation network
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Data from: Trophic level, successional age and trait matching determine specialization of deadwood-based interaction networks of saproxylic beetles
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Data from: Network structure and local adaptation in coevolving bacteria-phage interactions
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Data from: Reorganization of interaction networks modulates the persistence of species in late successional stages
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Data from: Multiple interaction networks: towards more realistic descriptions of the web of life
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Data from: Topology of tree-mycorrhizal fungus interaction networks in xeric and mesic Douglas-fir forests
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Data from: Social interactions elicit rapid shifts in functional connectivity in the social decision-making network of zebrafish
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Clearcutting and selective logging have inconsistent effects on liana diversity and abundance but not on liana–tree interaction networks
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Edge disturbance shapes liana diversity and abundance but not liana-tree interaction network patterns in moist semi-deciduous forests, Ghana
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Pollen transport networks reveal highly diverse and temporally stable plant-pollinator interactions in an Appalachian floral community
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Data from: Indirect interactions influence contact network structure and diffusion dynamics
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Data from: Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
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Molecular ecological network analyses: An effective conservation tool for the assessment of biodiversity, trophic interactions, and community structure
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Data from: Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.