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1,721 results for “network data”
Data from: Phylogenetic comparative methods on phylogenetic networks with reticulations
The goal of Phylogenetic Comparative Methods (PCMs) is to study the distribution of quantitative traits among related species. The observed traits are often seen as the result of a Brownian Motion (BM) along the branches of a phylogenetic tree. Reticulation events such as hybridization, gene flow or horizontal gene transfer, can substantially affect a species' traits, but are not modeled by a tree. Phylogenetic networks have been designed to represent reticulate evolution. As they become available for downstream analyses, new models of trait evolution are needed, applicable to networks. One natural extension of the BM is to use a weighted average model for the trait of a hybrid, at a reticulation point. We develop here an efficient recursive algorithm to compute the phylogenetic variance matrix of a trait on a network, in only one preorder traversal of the network. We then extend the standard PCM tools to this new framework, including phylogenetic regression with covariates (or phylogenetic ANOVA), ancestral trait reconstruction, and Pagel's λ test of phylogenetic signal. The trait of a hybrid is sometimes outside of the range of its two parents, for instance because of hybrid vigor or hybrid depression. These two phenomena are rather commonly observed in present-day hybrids. Transgressive evolution can be modeled as a shift in the trait value following a reticulation point. We develop a general framework to handle such shifts, and take advantage of the phylogenetic regression view of the problem to design statistical tests for ancestral transgressive evolution in the evolutionary history of a group of species. We study the power of these tests in several scenarios, and show that recent events have indeed the strongest impact on the trait distribution of present-day taxa. We apply those methods to a dataset of Xiphophorus fishes, to confirm and complete previous analysis in this group. All the methods developed here are available in the Julia package PhyloNetworks.
Data from: Detecting and quantifying social transmission using network-based diffusion analysis
<p>1. Although social learning capabilities are taxonomically widespread, demonstrating that freely interacting animals (whether wild or captive) rely on social learning has proved remarkably challenging.</p> <p>2. Network-based diffusion analysis (NBDA) offers a means for detecting social learning using observational data on freely interacting groups. Its core assumption is that if a target behaviour is socially transmitted, then its spread should follow the connections in a social network that reflects social learning opportunities.</p> <p>3. Here, we provide a comprehensive guide for using NBDA. We first introduce its underlying mathematical framework and present the types of questions that NBDA can address. We then guide researchers through the process of: selecting an appropriate social network for their research question; determining which NBDA variant should be used; and incorporating other variables that may impact asocial and social learning. Finally, we discuss how to interpret an NBDA model's output and provide practical recommendations for model selection.</p> <p>4. Throughout, we highlight extensions to the basic NBDA framework, including incorporation of dynamic networks to capture changes in social relationships during a diffusion and using a multi-network NBDA to estimate information flow across multiple types of social relationship.</p> <p>5. Alongside this information, we provide worked examples and tutorials demonstrating how to perform analyses using the newly developed NBDA package written in the R programming language.</p>
Data collected by fruit body– and DNA-based survey methods yield consistent species-to-species association networks in wood-inhabiting fungal communities
<p>Inferring interspecific interactions indirectly from community data is of central interest in community ecology. Data on species communities can be surveyed using different methods, each of which may differ in the amount and type of species detected, and thus produce varying information on interaction networks. Since fruit bodies reflect only a fraction of the woodinhabiting fungal diversity, there is an ongoing debate in fungal ecology on whether fruit body– based surveys are a valid method for studying fungal community dynamics compared to surveys based on DNA metabarcoding. In this paper, we focus on species-to-species associations and ask whether the associations inferred from data collected by fruit-body surveys reflect the ones found from data collected by DNA-based surveys. We estimate and compare the association networks resulting from different survey methods using a joint species distribution model. We recorded both raw and residual associations that respectively do not and do correct for the influence of the abiotic predictors when estimating the species-to-species associations. The analyses of the DNA data yielded a larger number of species-to-species associations than the analyses of the fruit body–based data as expected. Yet, we estimated unique associations also from the fruit-body data. Our results show that the directions of estimated residual associations were consistent between the data types, whereas the raw associations were much less consistent, highlighting the need to account for the influence of relevant environmental covariates when estimating association networks. We conclude that even though DNA-based survey methods are more informative about the total number of interacting species, fruit-body surveys are also an adequate method for inferring association networks in wood-inhabiting fungi. Since the DNA and fruit-body data carry on complementary information on fungal communities, the most comprehensive insights are obtained by combining the two survey methods.</p>
Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations - data
<p>Data from the paper:<em> Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations.</em></p> <p>Preprint: https://www.biorxiv.org/content/10.1101/840256v1</p> <p>Marek A. Pedziwiatr<br> marek.pedziwi@gmail.com<br> September 2020</p> <p> </p>
Data of "A network-ready random-access qubits memory"
<p>Data published in "<em>A network-ready random-access qubits memory</em>"</p> <p><em>npj Quantum Information</em></p>
Data from: Ethanol abolishes vigilance-dependent astroglia network activation in mice by inhibiting norepinephrine release
<p>This collection of data sets was obtained during a study of the effect of acute ethanol intoxication on vigilance-dependent astroglia network activation in mice. The main findings have been that ethanol inhibits astroglia activation by inhibiting vigilance-dependent norepinephrine release. This leads to a failure of activation of alpha<sub>1A</sub>-adrenergic receptors on astroglia. Further, this study has revealed that ethanol inhibition of cerebellar Bergmann glia Ca<sup>2+</sup> activation does not account for ataxic motor behavior, but may rather contribute to cognitive deficits.</p>
Effort data from the FLT Mediterranean Network 2008-2018
<p>Effort data used for the analysis presented in the manuscript "Trends in summer presence of fin whales in the Western Mediterranean Sea Region: new insights from a long-term monitoring program" - submitted for publication on PeerJ. </p> <p>Shape file represent transect monitored under favourable weather condition (sea state <=4) using ferries as platform of opportunity.</p>
Data from: A meta-analysis of plant interaction networks reveals competitive hierarchies as well as facilitation and intransitivity
The extent to which competitive interactions and niche differentiation structure communities has been highly controversial. To quantify evidence for key features of plant community structure, I recharacterized published data from interaction experiments as networks of competitive and facilitative interactions. I measured the network structure of 31 woody and herbaceous communities, including the intensity, distribution, and diversity of interactions at the species-pair and community level to determine the generality of competition, winner-loser relationships, and unequal interaction allocation. I developed novel methodology using meta-analysis to incorporate interaction uncertainty into estimates of structural metrics among independent networks. Plant communities were competitive, but intraspecific interactions were sometimes more intense than interspecific interactions. On the whole, interactions were imbalanced and communities were transitive. However, facilitation, balanced interactions, and intransitivity were common in individual communities. Synthesizing network metrics using meta-analysis is an original approach with which to generalize community structure in a systematic way.
SAPPAN: Combined Network and Host Data
<p>The data were acquired from a small simulated environment consisting of one Windows host (host data collection) and a router that observes all network traffic passing to the host. Two attack scenarios were performed in these small simulated environments, and data relevant to these attacks were extracted and further processed. In the case, the attack scenario was based on the Drupal web application's vulnerability, which enabled downloading and running of a malicious code that provided a remote shell to the attacker. In the case, the scenario was based on the old version of the Samba file-sharing that was vulnerable to Eternalblue attack allowing to execute commands and provide a remote shell to the attacker. </p> <p>The dataset is divided into separate directories according to the attacks contained. In the case of the Drupal vulnerability scenario, datasets from a failed and successful attempt to exploit the vulnerability are included. Four datasets were created during individual phases of SMB file sharing vulnerability scenario. Each directory contains a normalized network traffic capture and corresponding host data in preformatted JSON.</p> <p> </p> <p><strong>Drupal Vulnerability Scenario</strong></p> <p>The attack scenario is based on an old Drupal server (v 8.5.0) with known vulnerability CVE-2018-7600 (also called Drupalgeddon). This vulnerability is exploited by an attacker to remotely run code and gain access to the vulnerable server via a remote shell. This connection is realized by the Meterpreter trojan of type python/meterpreter/reverse_tcp. The binary is created by Metasploit generator msfvenom and obfuscated using the attacker's custom obfuscation technique to bypass windows antivirus. The created binary file is delivered to the victim host using remote code execution in Drupal, based on which the "finger" command is executed to download the payload from the payload delivery server and C2 server. This trojan is then launched by an attacker using additional commands injected through the Drupal vulnerability. Once launched, it automatically establishes a connection with the attacker (remote shell) through the payload delivery and C2 server. As a result, the attacker gains full access to the system and can execute any commands (in the scenario, only the "whoami" command is executed).</p> <p>Two datasets were generated during the scenario and its preparation. The first was obtained during the preparatory work when the server's defense mechanisms blocked an attacker's attempt to download the file (a command "MpCmdRun.exe" is used instead of the "finger" command). The second dataset contains a complete attack performed after modifying the executed commands to overcome the mentioned defense mechanisms.</p> <p><strong>Samba File Sharing Vulnerability Scenario</strong></p> <p>The attack scenario is based on an unpatched Windows 7 host with known vulnerability CVE-2017-0144 (also called EternalBlue). The scenario is divided into four parts covering the individual phases of the attack and failed exploitation attempts. In the first part, the attacker performs a scan of open ports on the client device and verifies if the SMB file sharing service is vulnerable to the EternalBlue attack. In the next phase, the attacker unsuccessfully tries to exploit the vulnerability using a standard Metasploit module. This procedure does not result in a remote connection. In the third phase, a specialized exploit is used to attack the service using previously known credentials. In the fourth phase, the attacker tried another script to make the scenario more complex, enabling the attack to be performed without credentials.</p> <p>For each mentioned phase, a separate dataset was generated, capturing all events in the form of packet traces and corresponding host data.</p> <p> </p> <p><strong>Dataset Features</strong></p> <p>In the case of packet capture, the dataset contains standard PCAP files containing all captured packets, including the complete application layer.</p> <p>The raw host data were reduced to contain only the following attributes:</p> <ul> <li><em>event_id</em> - unique Identifier of the event, assigned by a preprocessor</li> <li><em>event_type</em> - a type of the event</li> <li><em>time_created</em> - time when the sensor recorded the event</li> <li><em>event_data</em> - event type-specific payload</li> </ul>
Europe Road Network extracted from OpenStreetMap data
<p>The data extracts of Europe region downloaded on 04/07/2020 was used to create this dataset. From this the <strong>highways</strong> tagged as <strong>motorway, trunk, primary, secondary, tertiary, unclassified</strong> and <strong>residential </strong>are selected and the information was saved as line strings. CRS: WGS84 (EPSG:4326)<br> Files available are in parquet and csv format. Please feel free to convert the files in to desired file formats.</p>
Chinese Rotarians' Affiliation Network Data
<p>This set of files contains the edge list and the node list used for building the network of affiliation of the Chinese members of the Rotary Club of Shanghai. The network contains two categories of nodes: the persons (Chinese Rotarians) and the institutions in which they held positions in their lifetime. The edge list specifies the nature of the position, the date (year) when and the place (city) where it was held, and the strength of the connection for each pair (weight). The additional file (Rotary_ZH_position_clean) contains the original data extracted from contemporary <em>Who's Who. </em></p>
DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks
<p>Dataset and code used in V Wåhlstrand-Skärström, et al, "DeepFRAP: Fast fluorescence recovery after photobleaching data analysis using deep neural networks", published in Journal of Microscopy. In this work, we develop a new approach for FRAP analysis based on deep neural networks. From a numerical FRAP model developed in previous work, we generate a very large set of realistic, simulated recovery curve data. The data is used for training deep neural network regression models for prediction of e.g. the diffusion coefficient. We compare the performance of the neural network estimation framework to conventional least squares estimation on simulated and <br> experimental data. Herein, the simulated FRAP data used for the training, validation, and test data sets, the experimental data, and the Matlab and Python/Tensorflow code are supplied.</p>
Data: Focal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy
<p>We make available all the brain network data, and metadata of 83 patients and 29 healthy controls included in our study.</p> <p>Nishant Sinha, Natalie Peternell, Gabrielle M. Schroeder, Jane de Tisi, Sjoerd B. Vos, Gavin P. Winston, John S. Duncan, Yujiang Wang, and Peter N. Taylor "<em>Focal to bilateral tonic-clonic seizures are associated with widespread network abnormality in temporal lobe epilepsy.</em>" Epilepsia 2021 <em>doi:10.1111/epi.16819</em>.</p> <p>Methodological details on MRI acquisition and data processing are provided in our manuscript. We request users to kindly cite our article and data appropriately.</p>
Data used in 'The joint role of coevolutionary selection and network structure in shaping trait complementarity in mutualisms' manuscript
<p>The files in this repository correspond to the raw and processed data described in the 'The joint role of coevolutionary selection and network structure in shaping trait complementarity in mutualisms' manuscript.</p> <p>Once expanded, the zip files contains two directories and one documentation file, named data_documentation. Please refer to this file for a thorough description of the organization and contents of raw and processed data files.</p>
Data from: Facilitation and biodiversity jointly drive mutualistic networks
<p>1. Facilitation by nurse plants increases understorey diversity and supports ecological communities. In turn, biodiversity shapes ecological networks and enhances ecosystem functioning. However, whether and how facilitation and increased biodiversity jointly influence community structure and ecosystem functioning remains unclear.</p> <p>2. We performed a field experiment disentangling the relative contribution of nurse plants and increasing understorey plant diversity in driving pollination interactions. Both the presence of nurse shrubs as well as increased understorey plant diversity increased pollinator diversity and visitation rates. While nurse and understorey diversity effects on pollinator visitation rates did not interact, the effects of increasing understorey plant diversity on pollinator diversity were stronger in the absence than in the presence of shrubs, meaning that nurse shrubs attenuated the effects of high understorey diversity and buffered the effects of low understorey diversity.</p> <p>3. We also found positive complementarity effects among understorey species as well as complementarity between nurse plants and understorey species at high diversity. Results also indicate negative selection effects, suggesting that species with generally few pollinators benefit the most in the polyculture, while a species (possibly the nurse plant) with generally lots of pollinators does not. The corresponding changes in pollination networks with the experimental treatments were due to both changes in the frequency of visits and turnover in pollinator community composition.</p> <p>4. <i>Synthesis</i> Plant–plant facilitative systems, where a nurse plant increases understorey plant diversity, are common in stressful environments. Here, we show that these facilitative systems positively influence mutualistic interactions with pollinators via both direct nurse effects and indirect positive effects of increasing plant diversity. Conserving and supporting nurse plant systems is crucial not only for maintaining plant diversity but also for supporting ecosystem functions and services.</p>
Data from: Brain functional networks associated with social bonding in monogamous voles
<p>Previous studies have related pair bonding in Microtus ochrogaster, the prairie vole, with plastic changes in several brain regions. However, the interactions between these socially-relevant regions have yet to be described. In this study, we used resting state magnetic resonance imaging to explore bonding behaviors and functional connectivity of brain regions previously associated with pair bonding. Thirty-two male and female prairie voles were scanned at baseline, 24h and 2 weeks after the onset of cohabitation. By using network based statistics, we identified that the functional connectivity of a cortico-striatal network predicted the onset of affiliative behavior, while another predicted the amount of social interaction during a partner preference test. Furthermore, a network with significant changes in time was revealed, also showing associations with the level of partner preference. Overall, our findings revealed the association between network-level functional connectivity changes and social bonding.</p>
Training data for "From small to large-scale genome comparison", a tutorial for the Galaxy Training Network
<p>This dataset comprises two sequence pairs in FASTA format, one including two mycoplasmas (<em>Hyopneumoniae</em> 232 and 7422) and the other including the first chromosome of two plant genomes (<em>Aegilops tauschii</em> and <em>Triticum aestivum</em>).</p>
Data from: High specialization and limited structural change in plant‐herbivore networks along a successional chronosequence in tropical montane forest
Secondary succession is well‐understood, to the point of being predictable for plant communities, but the successional changes in plant‐herbivore interactions remains poorly explored. This is particularly true for tropical forests, despite the increasing importance of early successional stages in tropical landscapes. Deriving expectations from successional theory, we examine properties of plant‐herbivore interaction networks while accounting for host phylogenetic structure along a succession chronosequence in montane rainforest in Papua New Guinea. We present one of the most comprehensive successional investigations of interaction networks, equating to >40 person years of field sampling, and one of the few focused on montane tropical forests. We use a series of nine 0.2ha forest plots across young secondary, mature secondary and primary montane forest, sampled almost completely for woody plants and larval leaf chewers (Lepidoptera), using forest felling. These networks comprised of 12,357 plant‐herbivore interactions and were analysed using quantitative network metrics, a phylogenetically controlled host‐use index and a qualitative network beta diversity measure. Network structural changes were low and specialisation metrics surprisingly similar throughout succession, despite high network beta diversity. Herbivore abundance was greatest in the earliest stages, and hosts here had more species‐rich herbivore assemblages, presumably reflecting higher palatability due to lower defensive investment. All herbivore communities were highly specialised, using a phylogenetically narrow set of hosts, while host phylogenetic diversity itself decreased throughout the chronosequence. Relatively high phylogenetic diversity, and thus high diversity of plant defenses, in early succession forest may result in herbivores feeding on fewer hosts than expected. Successional theory, derived primarily from temperate systems, is limited in predicting tropical host‐herbivore interactions. All succession stages harbour diverse and unique interaction networks, which together with largely similar network structures and consistent host use patterns, suggests general rules of assembly may apply to these systems.
Data from: A multilayer network in an herbaceous tropical community reveals multiple roles of floral visitors
<p>Flower visitation does not necessarily mean pollination. In this sense, floral visitors can either act as mutualists (pollinators) or antagonists (floral robbers/thieves), indicating that these interactions are part of a continuum and that a visitor species can present multiple behaviours. We included both mutualistic and antagonistic interactions between plants and floral visitors in a multilayer network to explore the consequences (at the community level) of the dual roles played by flower visitors. The multilayer network of interactions was formed by herbaceous plants (12 species) and insects that visited their flowers (21 species) in an area of Atlantic Forest in Brazil from Jul 2015 to May 2016. The two layers presented similar structures, with high overlap between them. Similar to what was expected, the antagonistic layer was more modular and specialized than the mutualistic layer. Some visitor species exhibited highly central, dual roles, acting as both antagonists and mutualists. Most behaved consistently as mutualists in all their visits, especially bees, which formed a predominantly mutualistic group. Butterflies represented a mixed group in relation to their visits and flies made more antagonistic visits. This research represents an important step towards understanding the role of mutualisms and antagonisms in the structure of interaction networks between herbaceous plants and floral visitors in tropical environments.</p>
Data from: Fission–fusion processes weaken dominance networks of female Asian elephants in a productive habitat
Dominance hierarchies are expected to form in response to socioecological pressures and competitive regimes. We assess dominance relationships among free-ranging female Asian elephants (Elephas maximus) and compare them with those of African savannah elephants (Loxodonta africana), which are known to exhibit age-based dominance hierarchies. Both species are generalist herbivores, however, the Asian population occupies a more productive and climatically stable environment relative to that of the African savannah population. We expected this would lower competition relative to the African taxon, relaxing the need for hierarchy. We tested whether 1) observed dominance interactions among individuals were transitive, 2) outcomes were structured either by age or by social unit according to 4 independent ranking methods, and 3) hierarchy steepness among classes was significant using David's score. Elephas maximus displayed less than a third the number of dominance interactions as observed in L. africana, with statistically insignificant transitivity among individuals. There was weak but significant order as well as steepness among age-classes but no clear order among social units. Loxodonta africana showed significant transitivity among individuals, with significant order and steepness among age-classes and social units. Elephas maximus had a greater proportion of age-reversed dominance outcomes than L. africana. When dominance hierarchies are weak and nonlinear, signals of dominance may have other functions, such as maintaining social exclusivity. We propose that resource dynamics reinforce differences via influence on fission–fusion processes, which we term "ecological release." We discuss implications of these findings for conservation and management when animals are spatially constrained.
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.