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325 results for “network structure”
In-scanner head motion and structural covariance networks
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Code and data for: Network-based protein structural classification
<p>Code and data related to the research article titled, "Network-based protein structural classification".</p> <p>More information about the code and the data is available at https://nd.edu/~cone/NETPCLASS/</p>
Supplementary data for article 'Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images'
<p>3D DICOM volumes (CT scans) of feline femora, PNGs generated from them as DRRs using MeVisLab, and STLs generated from the DICOM volumes with MIMICS or MeshLab. Software to work with these files can be found at http://doi.org/10.5281/zenodo.3829423</p>
Dynamic shifts in social network structure and composition within a breeding hybrid population
1. Mating behavior and the timing of reproduction can inhibit genetic exchange between closely related species; however, these reproductive barriers are challenging to measure within natural populations. Social network analysis provides promising tools for studying the social context of hybridization, and the exchange of genetic variation, more generally. 2. We test how social networks within a hybrid population of California (Callipepla californica) and Gambel's quail (Callipepla gambelii) change over discrete periods of a breeding season. We assess patterns of phenotypic and genotypic assortment, and ask whether altered associations between individuals (association rewiring), or changes to the composition of the population (individual turnover) drive network dynamics. We use genetic data to test whether social associations and relatedness between individuals correlate with patterns of parentage within the hybrid population. 3. To achieve these aims, we combine RFID association data, phenotypic data, and genomic measures with social network analyses. We adopt methods from the ecological network literature to quantify shifts in network structure and to partition changes into those due to individual turnover and association rewiring. We integrate genomic data into networks as node-level attributes (ancestry) and edges (relatedness, parentage) to test links between social and parentage networks. 4. We show that rewiring of associations between individuals that persist across network periods, rather than individual turnover, drives the majority of the changes in network structure throughout the breeding season, and that the traits involved in phenotypic/genotypic assortment were highly dynamic over time. Social networks were randomly assorted based upon genetic ancestry, suggesting weak behavioral reproductive isolation within this hybrid population. Finally, we show that the strength of associations within the social network, but not levels of genetic relatedness, predict patterns of parentage. 5. Social networks play an important role in population processes such as the transmission of disease and information, yet there has been less focus on how networks influence the exchange of genetic variation. By integrating analyses of social structure, phenotypic assortment, and reproductive outcomes within a hybrid zone, we demonstrate the utility of social networks for analyzing links between social context and gene flow within wild populations. 08-Jul-2020
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: 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: Does biological intimacy shape ecological network structure? A test using a brood pollination mutualism on continental and oceanic islands
Biological intimacy—the degree of physical proximity or integration of partner taxa during their life cycles—is thought to promote the evolution of reciprocal specialization and modularity in the networks formed by co‐occurring mutualistic species, but this hypothesis has rarely been tested. Here, we test this "biological intimacy hypothesis" by comparing the network architecture of brood pollination mutualisms, in which specialized insects are simultaneously parasites (as larvae) and pollinators (as adults) of their host plants to that of other mutualisms which vary in their biological intimacy (including ant‐myrmecophyte, ant‐extrafloral nectary, plant‐pollinator and plant‐seed disperser assemblages). We use a novel dataset sampled from leafflower trees (Phyllanthaceae: Phyllanthus s. l. [Glochidion]) and their pollinating leafflower moths (Lepidoptera: Epicephala) on three oceanic islands (French Polynesia) and compare it to equivalent published data from congeners on continental islands (Japan). We infer taxonomic diversity of leafflower moths using multilocus molecular phylogenetic analysis and examine several network structural properties: modularity (compartmentalization), reciprocality (symmetry) of specialization and algebraic connectivity. We find that most leafflower‐moth networks are reciprocally specialized and modular, as hypothesized. However, we also find that two oceanic island networks differ in their modularity and reciprocal specialization from the others, as a result of a supergeneralist moth taxon which interacts with nine of 10 available hosts. Our results generally support the biological intimacy hypothesis, finding that leafflower‐moth networks (usually) share a reciprocally specialized and modular structure with other intimate mutualisms such as ant‐myrmecophyte symbioses, but unlike nonintimate mutualisms such as seed dispersal and nonintimate pollination. Additionally, we show that generalists—common in nonintimate mutualisms—can also evolve in intimate mutualisms, and that their effect is similar in both types of assemblages: once generalists emerge they reshape the network organization by connecting otherwise isolated modules.
Data from: Network structure and the optimisation of proximity-based association criteria
<ol> <li>Animal social network analysis (SNA) often uses proximity data obtained from automated tracking of individuals. Identifying associations based on proximity requires deciding on quantitative criteria such as the maximum distance or the longest time interval between visits of different individuals to still consider them associated. These quantitative criteria are not easily chosen based on <i>a priori</i> biological arguments alone.</li> <li>Here we propose a procedure for optimising proximity-based association criteria in SNA, whereby different spatial and temporal criteria are screened to determine which combination detects more network structure. If we assume that biologically-relevant associations among individuals are non-random, and that proximity data are mostly influenced by those associations, then it is logical to select criteria that minimise random associations and show the underlying network structure more clearly.</li> <li>We first used simulations to evaluate which of four simple descriptors of network structure remain unbiased (i.e., do not change directionally) when reducing the number of observations, since unbiased descriptors are necessary for comparing the structure of networks using different association criteria. Then, using two of those descriptors (coefficient of variation of the strength of associations, and network entropy), and empirical proximity data from automated tracking of common waxbills (<i>Estrilda astrild</i>) in a mesocosm environment, we found that the structure-based optimisation procedure selected the most biologically-relevant combination of spatial and temporal proximity criteria, in the sense that those criteria were also the best at distinguishing between previously known social sub-groups of individuals.</li> <li>These results indicate that, provided that the assumptions for structure-based optimisation are met, this procedure can find the most biologically-relevant association criteria. Thus, under the condition that proximity data are shaped by non-random social associations, and if using adequate descriptors of network structure, structure-based optimisation may be a useful tool for SNA, particularly when <i>a priori</i> biological arguments are insufficient to inform the choice of proximity-based association criteria.</li> </ol>
Data from: Genetics-based interactions of foundation species affect community diversity, stability, and network structure
We examined the hypothesis that genetics-based interactions between strongly interacting foundation species, the tree Populus angustifolia and the aphid Pemphigus betae, affect arthropod community diversity, stability and species interaction networks of which little is known. In a 2-year experimental manipulation of the tree and its aphid herbivore four major findings emerged: (i) the interactions of these two species determined the composition of an arthropod community of 139 species; (ii) both tree genotype and aphid presence significantly predicted community diversity; (iii) the presence of aphids on genetically susceptible trees increased the stability of arthropod communities across years; and (iv) the experimental removal of aphids affected community network structure (network degree, modularity and tree genotype contribution to modularity). These findings demonstrate that the interactions of foundation species are genetically based, which in turn significantly contributes to community diversity, stability and species interaction networks. These experiments provide an important step in understanding the evolution of Darwin's 'entangled bank', a metaphor that characterizes the complexity and interconnectedness of communities in the wild.
Representative structures for Trypsin-Benzamidine conformation-space network
<p>These structures were used for the analysis presented in the paper "Multiple Ligand Unbinding Pathways and Ligand-Induced Destabilization Revealed by WExplore" published in Biophysical Journal, 112, February 28, 2017. There is a tar ball (allframes.tgz) containing 4000 structures in PDB format, as well as a PDF file of the network with labels for each of the 4000 states (network_labels.pdf). Unpack the tar ball with: "tar xzf allframes.tgz".</p> <p> </p>
SIF datasets (50 m) and demos of network structure designs on the study of the STP-SIF issue
<p>The SIF datasets (i.e., SIF2019 and SIF2020) accompany the paper "Regional-Scale Cotton Yield Forecast via Data-Driven Spatio-Temporal Prediction (STP) of Solar-Induced Chlorophyll Fluorescence (SIF)" that was published in <a href="https://www.sciencedirect.com/science/article/abs/pii/S0034425723004121">Remote Sensing of Environment</a> on October 20, 2023. They have a spatial resolution of about 50 m and a monthly temporal resolution. Each of them has seven bands, corresponding to April to October. Please refer to our previous work, "Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network", which was published in <a href="https://www.sciencedirect.com/science/article/pii/S0168169922005737">Computers and Electronics in Agriculture</a> on August 14, 2022, for the development and detailed description.</p><p>The geographic reference (ESPG: 4326 (WGS_1984)) is the same for the two dataset, conforming to that in the geotiff file.</p><p><strong>Citation</strong>:</p><p>[1] Kang, X., Huang, C., Zhang, L., Wang, H., Zhang, Z., Lv, X., 2023. Regional-scale cotton yield forecast via data-driven spatio-temporal prediction (STP) of solar-induced chlorophyll fluorescence (SIF). Remote Sensing of Environment 299, 113861. doi:10.1016/j.rse.2023.113861</p><p>[2] Kang, X., Huang, C., Zhang, L., Zhang, Z., Lv, X., 2022. Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network. Computers and Electronics in Agriculture 201, 107260. doi:10.1016/j.compag.2022.107260</p><p>[3] Kang, X., Huang, C., Chen, J.M., Lv, X., Wang, J., Zhong, T., Wang, H., Fan, X., Ma, Y., Yi, X., Zhang, Z., Zhang, L., Tong, Q., 2023. The 10-m cotton maps in Xinjiang, China during 2018-2021. Sci Data 10, 688. doi:10.1038/s41597-023-02584-3</p><p>[4] Lang, P., Zhang, L., Huang, C., Chen, J., Kang, X., Zhang, Z., Tong, Q., 2023. Integrating environmental and satellite data to estimate county-level cotton yield in Xinjiang Province. Frontiers in Plant Science 13, 1048479. doi:10.3389/fpls.2022.1048479</p>
Social network structure is robust to parasite induced changes in contact behavior of domestic sheep
<p>Understanding how parasitism may affect social behavior and social networks is key to understanding the impact of infection on a population. Infection can disrupt social networks by altering the behavior of both infected individuals (e.g. by reducing activity) and the behavior of uninfected individuals (e.g. avoiding sick individuals), both of which can <span>have an impact on social group dynamics and parasite transmission</span>. Here we test experimentally how parasitism affects social contact behavior and social network structure using a common parasite infection of sheep. Three treatment groups, each with 4 replicate social groups were established (i) Parasitised; all lambs were infected with a parasitic nematode, (ii) Non-parasitised; all lambs remained uninfected (iii) Mixed; part of each group were infected, and part of the group remained uninfected. Contact behaviours of each individual were recorded using proximity loggers during four phases of infection (pre-parasite, pre-patent, patent-parasite, post-parasite). We found infected individuals in the parasitised and mixed groups reduced contact frequency following infection. Infected individuals in mixed groups however reduced contact frequency to a greater extent than infected animals in the fully parasitised group. D<span>espite the reduction in contacts between infected animals in the mixed group, the social network structure was unaffected, as non-infected individuals maintained pre-parasite levels of social interactions with their infected conspecifics. </span><span>These results demonstrate </span>how infection can impact the social behavior of all animals within a group, and how the expression of behavioral change may depend on the parasitic status of all group members and the response of uninfected conspecifics.</p>
Data from: Social networks reveal sex- and age-patterned social structure in Butler's Gartersnakes
<p>Sex- and age-based social structures have been well-documented in animals with visible aggregations. However, very little is known about the social structures of snakes. This is most likely because snakes are often considered non-social animals and are particularly difficult to observe in the wild. Here, we show that wild Butler's Gartersnakes have an age and sex assorted social structure similar to more commonly studied social animals. To demonstrate this, we use data from a 12-year capture-mark-recapture study to identify social interactions using social network analyses. We find that the social structures of Butler's Gartersnakes comprise sex- and age-assorted intra-species communities with older females often central and age segregation partially due to patterns of study site use. In addition, we find that females tended to increase in sociability as they aged while the opposite occurred in males. We also present evidence that social interaction may provide fitness benefits, where snakes that were part of a social network were more likely to have improved body condition. We demonstrate that conventional capture data can reveal valuable information on social structures in cryptic species. This is particularly valuable as research has consistently demonstrated that understanding social structure is important for conservation efforts. Additionally, research on the social patterns of animals without obvious social groups provides valuable insight into the evolution of group living.</p>
Data from: Urbanisation and agricultural intensification modulate plant-pollinator network structure and robustness
<p>Land use change is a major pressure on pollinator abundance, diversity, and plant-pollinator interactions. Far less is known about how land use alters the structure of plant-pollinator networks and their robustness to plant-pollinator coextinctions.</p> <p>We analyzed the structure of plant-pollinator networks sampled in 12 landscapes along an urbanisation and agricultural intensity gradient, from early spring to late summer 2021, and used a stochastic coextinction model to correlate plant-pollinator coextinction risk with network structure (species and network-level metrics) and landscape context.</p> <p>Networks in intensively managed (i.e. agricultural and urban) landscapes had a lower risk of initiating a coextinction cascade, while networks in less-intensively managed landscapes may be less robust. Network structure modulated the frequency and severity of coextinctions and species loss, while the strength of species interactions increased robustness.</p> <p>Urban networks were more species-rich and symmetrical due to the high diversity of ornamental plants, while intensively managed agricultural landscapes had smaller, more tightly connected, and nested networks.</p> <p>Network structure modulated the frequency of extinctions, which was decreased by greater linkage density, interaction asymmetry, and interaction dependence in the networks, while once an extinction occurred, nestedness and linkage density propagated the degree of the coextinction cascade and species loss. At the species level, species strength was inversely correlated with extinction risk, implying that generalist species with a high number of interactions with specialists had the lowest extinction risk.</p>
Data from: Heat stress conditions affect the social network structure of free‐ranging sheep
<p>Extreme weather conditions, like heatwave events, are becoming more frequent with climate change. Animals often modify their behaviour to cope with environmental changes and extremes. During heat stress conditions, individuals change their spatial behaviour and increase the use of shaded areas to assist with thermoregulation. Here, we suggest that for social species, these behavioural changes and ambient conditions have the potential to influence an individual's position in its social network, and the social network structure as a whole. We investigated whether heat stress conditions (quantified through the temperature humidity index) and the resulting use of shaded areas, influence the social network structure and an individual's connectivity in it. We studied this in free‐ranging sheep in the arid zone of Australia, GPS‐tracking all 48 individuals in a flock. When heat stress conditions worsened, individuals spent more time in the shade and the network was more connected (higher density) and less structured (lower modularity). Furthermore, we then identified the behavioural change that drove the altered network structure and showed that an individual's shade use behaviour affected its social connectivity. Interestingly, individuals with intermediate shade use were most strongly connected (degree, strength, betweenness), indicating their importance for the connectivity of the social network during heat stress conditions. Heat stress conditions, which are predicted to increase in severity and frequency due to climate change, influence resource use within the ecological environment. Importantly, our study shows that these heat stress conditions also affect the animal's social environment through the changed social network structure. Ultimately, this could have further flow on effects for social foraging and individual health since social structure drives information and disease transmission.</p>
Forecasting of the Geomagnetic Activity for the Next 3 Days Utilizing Neural Networks Based on Parameters Related to Large-scale Structures of the Solar Corona
<p>These are supplementary data for the paper "Forecasting of the Geomagnetic Activity for the Next 3 Days Utilizing Neural Networks Based on Parameters Related to Large-scale Structures of the Solar Corona". They are:</p> <ul> <li>Python code to forecast Kp index</li> <li><span>Code to construct a nerual network model</span></li> </ul>
The individual-based network structure of palm-seed dispersers is explained by a rainforest gradient
<p>How species interactions change in space and time is a major question in ecology. In tropical forests, plant individuals share mutualistic partners (pollinators or seed dispersers), yet we have little understanding of the factors affecting these individual interaction patterns. We used a seed dispersal individual-based network describing interactions between individuals of a palm species with bird species to investigate how intrinsic and extrinsic characteristics of individual plants influence the network structure. In our work we evaluated if average canopy height, number of fruits, distance to forest gap, and habitat type influence the role of palm individuals in the network. From 102 palms, 62 individuals had their seeds dispersed at least once: 17 individual palms in the restinga, 15 in the lowland and 30 in the pre-montane habitat. Twelve bird species were recorded dispersing <em>Euterpe edulis</em> seeds in our study area.</p>
Changes in the structure of seed dispersal networks when including interaction outcomes from both plant and animal perspectives
<p>Interaction frequency is the most common currency in quantitative ecological networks, although interaction quality can also affect benefits provided by mutualisms. Here, we evaluate if interaction quality can modify network topology, species' role and whether such changes affect community vulnerability to species loss. We use a well-examined study system (bird-lizard and fleshy-fruited plants in the 'thermophilous' woodland of the Canary Islands) to compare network and species-level metrics from a network based on fruit consumption rates (Interaction Frequency, IF), against networks reflecting functional outcomes: a Seed Dispersal Effectiveness network (SDE) quantifying recruitment, and a Fruit Resource Provisioning network (FRP), accounting for the nutrient supply of fruits. Nestedness decreased in the FRP and the SDE networks, due to the lack of association between fruit consumption rates and (1) nutrient content, and (2) recruitment at the seed deposition sites, respectively. The FRP network showed lower niche overlap due to resource use complementarity among frugivores. Interaction evenness was lower in the SDE network, in response to a higher dominance of lizards in the recruitment of heliophilous species. Such changes, however, did not result in enhanced vulnerability against extinctions. At the plant species level, strength changed in the FRP network in frequently consumed or highly nutritious species. The number of effective partners decreased for species whose seeds were deposited in unsuitable places for recruitment. In frugivores, strength was consistent across networks (SDE vs IF), showing that consumption rates outweighed differences in dispersal quality. In the case of lizards, the increased importance of nutrient-rich species resulted in a higher number of effective partners.</p> <p>Our work shows that although frequency strongly impacts interaction effects, accounting for quality improves our inferences about interaction assembly and species role. Thus, future studies including interaction outcomes from both partners' perspectives will provide valuable insights about the net effects of mutualistic interactions.</p>
Network structural origin of instabilities in large complex systems
<p>Raw data used to generate figures in the following publication:</p> <p>Title: "Network structural origin of instabilities in large complex systems"<br> Authors: Chao Duan, Takashi Nishikawa, Deniz Eroglu, Adilson E. Motter<br> Journal: <a href="https://doi.org/10.1126/sciadv.abm8310">Science Advances 8, eabm8310 (2022)</a></p> <p>The CSV files are named by the corresponding figure numbers and the quantities (e.g., "Fig1A_data.csv" for data for Fig. 1A and "FigS1A_data_adj_mat.csv" for the adjacency matrix data for Fig. S1A).<br> </p>
Habitat loss shapes the structure and species roles in mutualistic seed dispersal networks
<p>This dataset has the variables used in the paper "Habitat loss shapes the structure and species roles in tropical seed dispersal networks" as well as the script to perform the analysis.</p>
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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.