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1,721 results for “network data”
Norwegian UV Network - minute data
<p><strong>Data are free for scientific, non-commercial purposes, but acknowledgement shall be given to DSA and NILU.</strong></p> <p>Doserates at 1 minute resolution, based on real-sky measurements from GUV-instruments located at 10 sites in Norway (no substitution of gap periods).</p> <p>Calibrations based on the FARIN2005-campaign and annual site visits with a travelling reference GUV instrument. <a href="http://onlinelibrary.wiley.com/doi/10.1029/2007JD009731/abstract">http://onlinelibrary.wiley.com/doi/10.1029/2007JD009731/abstract</a></p> <p>Groups of station-instruments have participated in 6 QASUME-campaigns (2003, 2005, 2009, 2010, 2014 and 2019).</p> <p>Interquartile range of UVI-measurements, relative to QASUME for the periode 2003-2019: +/-5 percent.</p> <p>Funding: Norwegian Environment Agency and Norwegian Ministry of Health and Care Services</p>
data set related to article Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers - Preliminary Data from a DWI Analysis
<p>This record contains raw data related to article Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers - Preliminary Data from a DWI Analysis</p>
Data from: Differential effects of fertilisers on pollination and parasitoid interaction networks
Grassland fertilisation drives non-random plant loss resulting in areas dominated by perennial grass species. How these changes cascade through linked trophic levels, however, is not well understood. We studied how grassland fertilisation propagates change through the plant assemblage into the plant-flower visitor, plant-leaf miner and leaf miner-parasitoid networks using a year's data collection from a long-term grassland fertiliser application experiment. Our experiment had three fertiliser treatments each applied to replicate plots 15 m2 in size: mineral fertiliser, farmyard manure, and mineral fertiliser and farmyard manure combined, along with a control of no fertiliser. The combined treatment had the most significant impact, and both plant species richness and floral abundance decreased with the addition of fertiliser. While insect species richness was unaffected by fertiliser treatment, fertilised plots had a significantly higher abundance of leaf miners and parasitoids and a significantly lower abundance of bumblebees. The plant-flower visitor and plant-herbivore networks showed higher values of vulnerability and lower modularity with fertiliser addition, while leaf miner-parasitoid networks showed a rise in generality. The different groups of insects were impacted by fertilisers to varying degrees: while the effect on abundance was the highest for leaf miners, the vulnerability and modularity of flower visitor networks was the most affected. The impact on the abundance of leaf miners was positive and three times higher than the impact on parasitoids, and the impact on bumblebee abundance was negative and double the magnitude of impact on flower abundance. Overall our results show that while insect species richness was unaffected by fertilisers, network structure changed significantly as the replacement of forbs by grasses resulted in changes in relative abundance across trophic levels, with the direction of change depending on the type of network. By studying multiple networks simultaneously, we were able to rank the relative impact of habitat change on the different groups of species within the community. This provided a more holistic picture of the impact of agricultural intensification and provides useful information when deciding on priorities for mitigation. 01-Oct-2020
Data for "Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network"
<p><strong>Data for the paper "Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network"</strong></p> <p>GitHub: <a href="https://github.com/gauchm/mts-lstm">https://github.com/gauchm/mts-lstm</a></p> <p>This dataset contains the hourly NLDAS forcings and USGS streamflow data.</p> <p>For training with our codebase, we recommend using the combined NetCDF file, but you can also use the csv files (but it will take much longer to load the data).</p> <p> </p> <p><em>Related Datasets: </em><a href="https://doi.org/10.5281/zenodo.4071885">https://doi.org/10.5281/zenodo.4071885</a> contains the models trained with the forcings and streamflow from this dataset.</p>
Data for: Infectious disease and sickness behaviour: tumour progression affects interaction patterns and social network structure in wild Tasmanian devils
<p>Infectious diseases, including transmissible cancers, can have a broad range of impacts on host behaviour, particularly in the latter stages of disease progression. However, the difficulty of early diagnoses makes the study of behavioural influences of disease in wild animals a challenging task. Tasmanian devils (<i>Sarcophilus harrisii</i>) are affected by a transmissible cancer, devil facial tumour disease (DFTD), in which tumours are externally visible as they progress. Using telemetry and mark-recapture data sets, we quantify the impacts of cancer progression on the behaviour of wild devils by assessing how interaction patterns within the social network of a population change with increasing tumour load. DFTD negatively influences devils' likelihood of interaction within their network, an effect which increases with increasing tumour load. Infected devils were more active within their network late in the mating season, a pattern with repercussions for DFTD transmission. Our study provides a rare opportunity to quantify and understand the behavioural feedbacks of disease in wildlife and how they may affect transmission and population dynamics in general.</p>
BDRC Educational Affiliation Network Data
<p>This set of files contains the edge list, the node list and the list of node attributes used for building the network of educational affiliation in the <em>Biographical Dictionary of Republican China</em> (BDRC). The network contains two categories of nodes: the individuals and the educational institutions they attended. The node attributes file contains two sheet: one for individuals, one for institutions.</p>
Data for assessment of damage to residential dwellings using artificial neural networks
<p>The data provided and the associated MATLAB code were used to build an Artificial Neural Network Model to capture damage to residential home subjected to tornado events in the State of Missouri. The ANN model utilizes relevant tornado, societal demographic, and structural data to determine a building's resulting damage state from an extreme wind event. </p>
Data for "CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks"
<p>Trained models and reconstructed density maps for:</p> <ul> <li>EMPIAR-10028: "Cryo-EM structure of a <em>Plasmodium falciparum</em> 80S ribosome bound to the anti-protozoan drug emetine" from Wong et al. (2014)</li> <li>EMPIAR-10049: "Molecular Mechanism of V(D)J Recombination from Synaptic RAG1-RAG2 Complex Structures" from Ru et al. (2015)</li> <li>EMPIAR-10076: "Modular assembly of the large bacterial ribosome" from Davis et al. (2016)</li> <li>EMPIAR-10180: "Structure of a pre-catalytic spliceosome" from Plaschka et al. (2017)</li> </ul> <p>Synthetic datasets with simulated heterogeneity and their ground truth density maps, poses, and labels:</p> <ul> <li>Uniform: 50k particle images (128x128, 6A/pix) uniformly sampled from 50 models along a 1-dimensional reaction coordinate</li> <li>Cooperative: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model with overlapping components </li> <li>Noncontiguous: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model without overlapping components</li> <li>Ribosomes: 50k particle images (128x128, 3A/pix) containing a mixture of 30S, 50S, 70S ribosomes simulating compositional heterogeneity</li> </ul>
Data from: How to make methodological decisions when inferring social networks.
<p>Social network analyses allow studying the processes underlying the associations between individuals and the consequences of those associations. Constructing and analysing social networks can be challenging, especially when designing new studies as researchers are confronted with decisions about how to collect data and construct networks, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods, and risk generating false results arising from multiple hypotheses testing. Here, we suggest an approach for making decisions when starting social network research in a new study system that avoids the pitfall of multiple hypotheses testing. We argue that best edge definition for a network is a decision that can be made using <i>a priori</i> knowledge about the species, and that is independent from the hypotheses that the network will ultimately be used to evaluate. We illustrate this approach with a study conducted on a colonial cooperatively breeding bird, the sociable weaver. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then evaluated which combination of data collection and association definition maximised (i) the assortment of individuals into previously known 'breeding groups' (birds that contribute towards the same nest and maintain cohesion when foraging), and (ii) socially differentiated relationships (more strong and weak relationships than expected by chance). This evaluation of different methods based on <i>a priori</i> knowledge of the study species can be implemented in a diverse array of study systems and makes the case for using existing, biologically meaningful knowledge about a system to help navigate the myriad of methodological decisions about data collection and network inference.</p>
Data and Code for Inequality is rising where social network segregation interacts with urban topology
<p>This folder contains data and code to reproduce results of the paper "Inequality is rising where social network segregation interacts with urban topology". arXiv version: https://arxiv.org/abs/1909.11414.</p>
FIGURE 4. Combined haplotype networks from CytB data for Laminatubus paulbrooksi n in Laminatubus (Serpulidae, Annelida) from eastern Pacific hydrothermal vents and methane seeps, with description of two new species
FIGURE 4. Combined haplotype networks from CytB data for Laminatubus paulbrooksi n. sp. (top) from Pacific Costa Rica margin and Gulf of California (Mexico) localities and L. joycebrooksae n. sp. (bottom) from Costa Rica. There was little variability among the L. joycebrooksae n. sp. sequences and a distinct break to L. paulbrooksi n. sp. This corresponds to a minimum 6.4% uncorrected distance. Laminatubus paulbrooksi n. sp. showed marked intraspecific variability with distinct breaks among the three main sites; Costa Rica (9°N), Pescadero (23°N) and Guaymas Basin (27°N). * indicates the holotypes for L. paulbrooksi n. sp. and L. joycebrooksae n. sp. respectively.
Data from: Finding the best management policy to eradicate invasive species from spatial ecological networks with simultaneous actions
1. Spatial management of invasive species is more likely to be successful when multiple locations are treated simultaneously. However, selecting the best locations to act is difficult due to the many options available at any time. 2. We design a near-optimal policy for applying multiple actions simultaneously for faster invasive species control within a network. Our method uses a recent optimisation tool, the Graph-based Markov decision process (GMDP). Since the policy can be difficult to interpret, we extracted a simpler policy using classification trees. We applied our approach to the eradication of invasive mosquitofish (Gambusia holbrooki) from the habitat of the red-finned blue-eye (Scaturiginichthys vermeilipinnis), a critically endangered fish with a global population that is restricted to seven artesian springs in Queensland, Australia. 3. The policy returned by the GMDP was to manage springs occupied by mosquitofish and their connected neighbours, unless the neighbours were occupied by red-finned blue-eyes. 4. Simultaneous management resulted in rapid declines in simulated mosquitofish occupancy even if eradication effectiveness was low; however the cost of simultaneous eradication was high and sustained eradication effort was necessary to maintain low mosquitofish occupancy. 5. Synthesis and applications. Our paper finds a near-optimal, multi-action control policy to remove an invasive species from a multi-species spatial network. We introduce the Graph-based Markov decision process (GMDP) and apply it to a real case study – eradication of invasive mosquitofish from the habitat of the red-finned blue-eye. We find that the GMDP can generate policies for networks with extremely large state spaces, however it works best when nodes have fewer than five neighbours. We conclude that simultaneous eradications are effective for rapid control of invasive species; however, managers should consider the cost and time required for an effective eradication program.
Data from: Fire influences the structure of plant-bee networks
1. Fire represents a frequent disturbance in many ecosystems, which can affect plant-pollinator assemblages and hence the services they provide. Furthermore, fire events could affect the architecture of plant-pollinator interaction networks, modifying the structure and function of communities. 2. Some pollinators, such as wood-nesting bees, may be particularly affected by fire events due to damage to nesting material and its long regeneration time. However, it remains unclear whether fire influences the structure of bee plant interactions. 3. Here, we used quantitative plant-wood nesting bee interaction networks sampled across four different post-fire age categories (from freshly-burnt to unburnt sites) in an arid ecosystem to test whether the abundance of wood-nesting bees, the breadth of resource use and the plant-bee community structure change along a post-fire age gradient. 4. We demonstrate that freshly-burnt sites present higher abundances of generalist than specialist wood-nesting bees and this translates into lower network modularity than that of sites with greater post-fire ages. Bees do not seem to change their feeding behaviour across the post-fire age gradient despite changes in floral resource availability. 5. Despite the effects of fire on plant-bee interaction network structure, these mutualistic networks seem to be able to recover a few years after the fire event. This result suggests that these interactions might be highly resilient to this type of disturbance.
Data from: Plastic transcriptomes stabilize immunity to pathogen diversity: the jasmonic acid and salicylic acid networks within the Arabidopsis/Botrytis pathosystem
To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis-B. cinerea pathosystem to test how the host's defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA- and SA-signaling mutants, coi1-1 and npr1-1, individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene co-expression networks and two vectors of defense variation triggered by genetic variation in B. cinerea. This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen.
Data from: The impact of gene expression variation on robustness and evolvability of a developmental gene regulatory network
Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear), allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.
Data from: Plant interactions shape pollination networks via nonadditive effects
Plants grow in communities where they interact with other plants and with other living organisms such as pollinators. On the one hand, studies of plant–plant interactions rarely consider how plants interact with other trophic levels such as pollinators. On the other, studies of plant–animal interactions rarely deal with interactions within trophic levels such as plant–plant competition and facilitation. Thus, to what degree plant interactions affect biodiversity and ecological networks across trophic levels is poorly understood. We manipulated plant communities driven by foundation species facilitation and sampled plant–pollinator networks at fine spatial scale in a field experiment in Sierra Nevada, Spain. We found that plant–plant facilitation shaped pollinator diversity and structured pollination networks. Nonadditive effects of plant interactions on pollinator diversity and interaction diversity were synergistic in one foundation species networks while they were additive in another foundation species. Nonadditive effects of plant interactions were due to rewiring of pollination interactions. In addition, plant facilitation had negative effects on the structure of pollination networks likely due to increase in plant competition for pollination. Our results empirically demonstrate how different network types are coupled, revealing pervasive consequences of interaction chains in diverse communities.
Data from: Phylogenetic signal in module composition and species connectivity in compartmentalized host-parasite networks
Across different taxa, networks of mutualistic or antagonistic interactions show consistent architecture. Most networks are modular, with modules being distinct species subsets connected mainly with each other and having few connections to other modules. We investigate the phylogenetic relatedness of species within modules and whether a phylogenetic signal is detectable in the within- and among module connectivity of species using 27 mammal-flea networks from the Palaearctic. In the 24 networks that were modular, closely-related hosts co-occurred in the same module more often than expected by chance; in contrast, this was rarely the case for parasites. The within- and among-module connectivity of the same host or parasite species varied geographically. However, among-module but not within-module connectivity of host and parasites was somewhat phylogenetically constrained. These findings suggest that the establishment of host-parasite networks results from the interplay between phylogenetic influences acting mostly on hosts and local factors acting on parasites, to create an asymmetrically constrained pattern of geographic variation in modular structure. Modularity in host-parasite networks seems to result from the shared evolutionary history of hosts and by trait convergence among unrelated parasites. This suggests profound differences between hosts and parasites in the establishment and functioning of bipartite antagonistic networks.
Data from: PopART: full-feature software for haplotype network construction
1. Haplotype networks are an intuitive method for visualising relationships between individual genotypes at the population level. 2. Here, we present popart, an integrated software package that provides a comprehensive implementation of haplotype network methods, phylogeographic visualisation tools and standard statistical tests, together with publication-ready figure production. 3. popart also provides a platform for the implementation and distribution of new network-based methods – we describe one such new method, integer neighbour-joining. 4. The software is open source and freely available for all major operating systems.
Data from: Key players and hierarchical organization of prairie dog social networks
The use of social network theory in evaluating animal social groups has gained traction in recent years. Despite the utility of social network analysis in describing attributes of social groups, it remains unclear how comparable this approach is to traditional behavioral observational studies. Using data on Gunnison's prairie dog (Cynomys gunnisoni) social interactions we describe social networks from three populations. We then compare those social networks to groups identified by traditional behavioral approaches and explore whether individuals group together based on similarities. The social network social groups identified by social network analysis were consistent with those identified by more traditional behavioral approaches. However, fine-grained social sub-structuring was revealed only with social network analysis. We found variation in the patterns of interactions among prairie dog social groups that was largely independent of the behavioral attributes or genetics of the individuals within those groups. We detected that some social groups include disproportionately well-connected individuals acting as hubs or bridges. This study contributes to a growing body of evidence that social networks analysis is a robust and efficient tool for examining social dynamics.
Data from: Node-based measures of connectivity in genetic networks
At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.