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1,721 results for “network data”
Data for Perception of own centrality in social networks by Kovarik, Ozaita, Sánchez and Brañas-Garza
<p>Data for the paper "Perception of own centrality in social networks", by Kovarik, Ozaita, Sánchez and Brañas-Garza, submitted for publication. Two .csv files: one with the anonymized, otherwise raw network data, and the second one with the results of analyzing the network reported in the paper</p>
DATA_measure and predict the travel time reliability on the urban rail transit network
<p>(1)The automatic fare collection data recorded the time of entering and exiting stations for each trip.<br>(2)The automatic fare collection data format is CSV, and the columns of the table are in Chinese. The columns are ticket card number, ticket card type, date, time of entering the station, entering station name, time of exiting the station, exiting station name, and day of the week.</p>
Linked collectors and determiners for: NatureServe Network Species Occurrence Data.
Natural history specimen data linked to collectors and determiners held within, "NatureServe Network Species Occurrence Data". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/7fd12114-9010-4c13-8f46-990fe04ca882">https://bionomia.net/dataset/7fd12114-9010-4c13-8f46-990fe04ca882</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/7fd12114-9010-4c13-8f46-990fe04ca882">https://gbif.org/dataset/7fd12114-9010-4c13-8f46-990fe04ca882</a>. Formatted as a Frictionless Data package.
Data from: Stimulation-based control of dynamic brain networks
The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.
Data from: Local extinctions of obligate frugivores and patch size reduction disrupt the structure of seed dispersal networks
A central problem in ecology is to understand how human impacts affect plant-animal interactions that lead to effective seed dispersal services for plant communities. Seed dispersal services are the outcome of plant-frugivore interactions that often form local networks of interacting species. Recent work has shown that some frugivorous bird species are more critical to network organization than others. Here, we explore how patch size and the potential local extinctions of obligate frugivorous birds affect the reorganization of seed dispersal networks. We examined the structure of 20 empirical seed dispersal networks documented across tropical avian assemblages occupying widely variable habitat patch sizes, a surrogate of the amount of remaining habitat. Networks within small forest patches consistently supported both lower plant and bird species richness. Forest patch size was positively associated with nestedness, indicating that reductions in patch size disrupted the nested organization of seed dispersal networks. Obligate frugivores, especially large-bodied species, were almost entirely absent from small forest patches. Analysis at the species level showed that obligate frugivores formed the core of interacting species, connecting species within a given seed dispersal network. Our combined results revealed that patch size reduction erodes frugivorous bird diversity, thereby affecting the integrity of seed dispersal networks. We highlight the importance of conserving large forest patches to maintain tropical forest functionality.
Data from: The network motif architecture of dominance hierarchies
The widespread existence of dominance hierarchies has been a central puzzle in social evolution, yet we lack a framework for synthesizing the vast empirical data on hierarchy structure in animal groups. We applied network motif analysis to compare the structures of dominance networks from data published over the past 80 years. Overall patterns of dominance relations, including some aspects of non-interactions, were strikingly similar across disparate group types. For example, nearly all groups exhibited high frequencies of transitive triads, whereas cycles were very rare. Moreover, pass-along triads were rare, and double-dominant triads were common in most groups. These patterns did not vary in any systematic way across taxa, study settings (captive or wild) or group size. Two factors significantly affected network motif structure: the proportion of dyads that were observed to interact and the interaction rates of the top-ranked individuals. Thus, study design (i.e. how many interactions were observed) and the behaviour of key individuals in the group could explain much of the variations we see in social hierarchies across animals. Our findings confirm the ubiquity of dominance hierarchies across all animal systems, and demonstrate that network analysis provides new avenues for comparative analyses of social hierarchies.
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.
Data from: Chemogenetic interrogation of a brain-wide fear memory network in mice
Behavior depends on coordinated activity across multiple brain regions. Within such networks, highly connected hub regions are assumed to disproportionately influence behavioral output, although this hypothesis has not been systematically evaluated. Previously, by mapping brain-wide expression of the activity-regulated gene c-fos, we identified a network of brain regions co-activated by fear memory. To test the hypothesis that hub regions are more important for network function, here, we simulated node deletion in silico in this behaviorally defined functional network. Removal of high degree nodes produced the greatest network disruption (e.g., reduction in global efficiency). To test these predictions in vivo, we examined the impact of post-training chemogenetic silencing of different network nodes on fear memory consolidation. In a series of independent experiments encompassing 25% of network nodes (i.e., 21/84 brain regions), we found that node degree accurately predicted observed deficits in memory consolidation, with silencing of highly connected hubs producing the largest impairments.
Data from: An automated approach to identifying search terms for systematic reviews using keyword co-occurrence networks
1. Systematic review, meta-analysis, and other forms of evidence synthesis are critical to strengthen the evidence base concerning conservation issues and to answer ecological and evolutionary questions. Synthesis lags behind the pace of scientific publishing, however, due to time and resource costs which partial automation of evidence synthesis tasks could reduce. Additionally, current methods of retrieving evidence for synthesis are susceptible to bias towards studies with which researchers are familiar. In fields that lack standardized terminology encoded in an ontology, including ecology and evolution, research teams can unintentionally exclude articles from the review by omitting synonymous phrases in their search terms. 2. To combat these problems, we developed a quick, objective, reproducible method for generating search strategies that uses text mining and keyword co-occurrence networks to identify the most important terms for a review. The method reduces bias in search strategy development because it does not rely on a predetermined set of articles and can improve search recall by identifying synonymous terms that research teams might otherwise omit. 3. When tested against the search strategies used in published environmental systematic reviews, our method performs as well as the published searches and retrieves gold-standard hits that replicated versions of the original searches do not. Because the method is quasi-automated, the amount of time required to develop a search strategy, conduct searches, and assemble results is reduced from approximately 17-34 hours to under 2 hours. 4. To facilitate use of the method for environmental evidence synthesis, we implemented the method in the R package litsearchr, which also contains a suite of functions to improve efficiency of systematic reviews by automatically deduplicating and assembling results from separate databases.
Data from: Low modularity and specialization in a commensalistic epiphyte–phorophyte network in a tropical cloud forest
Species interactions can shape the structure of natural communities. Such sets of interactions have been described as complex ecological networks, an example of which is the commensal network formed by epiphyte–phorophyte interactions. Vascular epiphytes germinate and grow on phorophytes (support trees), assuming a horizontal distribution (among the phorophyte species) and a vertical distribution (from the base of the tree trunk to the crown of phorophytes, i.e., through ecological zones). Here we investigated the organization of these structural dimensions of the epiphyte–phorophyte network in a Brazilian tropical montane cloud forest. The analyzed network, comprising 66 epiphyte species and 22 phorophyte species, exhibited a nested structure with a low degree of specialization, a typical pattern for epiphyte–phorophyte networks in forests. The network was slightly modular, with 65% of the species common to three modules, and had vertical structure corresponding to the vertical organization of the phorophytes. The size (diameter at breast height) of phorophyte individuals influenced the network structure, possibly due to the increase in habitat area, the time available for colonization by epiphytes, and a greater number of microenvironments. We found that the distribution of the epiphyte species differed between the phorophyte ecological zones, with greater richness in the lower portions and greater abundance in the upper portions of the phorophytes. The results provide relevant guidance for future research on the characteristics and the vertical and horizontal organization of vascular epiphyte and phorophyte networks.
Data from: Scalability of asynchronous networks is limited by one-to-one mapping between effective connectivity and correlations
Network models are routinely downscaled compared to nature in terms of numbers of nodes or edges because of a lack of computational resources, often without explicit mention of the limitations this entails. While reliable methods have long existed to adjust parameters such that the first-order statistics of network dynamics are conserved, here we show that limitations already arise if also second-order statistics are to be maintained. The temporal structure of pairwise averaged correlations in the activity of recurrent networks is determined by the effective population-level connectivity. We first show that in general the converse is also true and explicitly mention degenerate cases when this one-to-one relationship does not hold. The one-to-one correspondence between effective connectivity and the temporal structure of pairwise averaged correlations implies that network scalings should preserve the effective connectivity if pairwise averaged correlations are to be held constant. Changes in effective connectivity can even push a network from a linearly stable to an unstable, oscillatory regime and vice versa. On this basis, we derive conditions for the preservation of both mean population-averaged activities and pairwise averaged correlations under a change in numbers of neurons or synapses in the asynchronous regime typical of cortical networks. We find that mean activities and correlation structure can be maintained by an appropriate scaling of the synaptic weights, but only over a range of numbers of synapses that is limited by the variance of external inputs to the network. Our results therefore show that the reducibility of asynchronous networks is fundamentally limited.
Data from: Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network
Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks.
Data from: Whole-body photoreceptor networks are independent of 'lenses' in brittle stars
Photoreception and vision are fundamental aspects of animal sensory biology and ecology, but important gaps remain in our understanding of these processes in many species. The colour-changing brittle star Ophiocoma wendtii is iconic in vision research, speculatively possessing a unique whole-body visual system that incorporates information from nerve bundles underlying thousands of crystalline 'microlenses'. The hypothesis that these form a sophisticated compound eye-like system regulated by chromatophore movement has been extensively reiterated, with consequent investigations into biomimetic optics and similar 'visual' structures in living and fossil taxa. However, no photoreceptors or visual behaviours have ever been identified. We present the first evidence of photoreceptor networks in three Ophiocoma species, both with and without microlenses and colour-changing behaviour. High-resolution microscopy, immunohistochemistry and synchrotron tomography demonstrate that putative photoreceptors cover the animals' oral, lateral, and aboral surfaces, but are absent at the hypothesised focal points of the microlenses. The structural optics of these crystal 'lenses' are an exaptation and do not fulfil any apparent visual role. This contradicts previous studies, yet the photoreceptor network in Ophiocoma appears even more widespread than previously anticipated, both taxonomically and anatomically.
Data from: Using relatedness networks to infer contemporary dispersal: application to the endangered mammal Galemys pyrenaicus
Information about the degree of contemporary dispersal is important when trying to understand how populations interchange individuals and identify the specific barriers that prevent these movements. In the case of endangered species, this can represent crucial information when designing appropriate strategies that favor natural genetic exchange between populations. Here we analyze the parentage relationships between individuals from different localities and use these data to infer dispersal occurred in recent generations. We applied this approach to the Pyrenean desman (Galemys pyrenaicus), a semiaquatic and endangered species endemic to the Iberian Peninsula. We studied this species in four primary rivers in the Iberian Range, where two ancient mitochondrial lineages are separated by a strict contact zone but whose populations are more homogeneous at the genome level, suggesting the existence of complex dispersal patterns. Using next generation sequencing, we obtained 912 SNPs from each sample and estimated relatedness values between them. While relatedness networks were very dense within each river, we found surprisingly few relationships between individuals from different rivers despite their close proximity in some cases, indicating that dispersal between rivers is extremely low compared to dispersal within a single river. In agreement with this, the degree of inbreeding was exceedingly high in most individuals. These data show that relatedness information can be crucial to understand the contemporary dispersal patterns and conservation status of specific populations of endangered species.
Data from: Comprehensive experimental fitness landscape and evolutionary network for small RNA
The origin of life is believed to have progressed through an RNA world, in which RNA acted as both genetic material and functional molecules. The structure of the evolutionary fitness landscape of RNA would determine natural selection for the first functional sequences. Fitness landscapes are the subject of much speculation, but their structure is essentially unknown. Here we describe a comprehensive map of a fitness landscape, exploring nearly all of sequence space, for short RNAs surviving selection in vitro. With the exception of a small evolutionary network, we find that fitness peaks are largely isolated from one another, highlighting the importance of historical contingency and indicating that natural selection would be constrained to local exploration in the RNA world.
Data from: Collective forces of tumor spheroids in three-dimensional biopolymer networks
<p>We describe a method for quantifying the contractile forces that tumor spheroids collectively exert on highly nonlinear three-dimensional collagen networks. While three-dimensional traction force microscopy for single cells in a nonlinear matrix is computationally complex due to the variable cell shape, here we exploit the spherical symmetry of tumor spheroids to derive a scale-invariant relationship between spheroid contractility and the surrounding matrix deformations. This relationship allows us to directly translate the magnitude of matrix deformations to the total contractility of arbitrarily sized spheroids. We show that our method is accurate up to strains of 50% and remains valid even for irregularly shaped tissue samples when considering only the deformations in the far field. Finally, we demonstrate that collective forces of tumor spheroids reflect the contractility of individual cells for up to 1h after seeding, while collective forces on longer timescales are guided by mechanical feedback from the extracellular matrix.</p>
Data from: Quantitative analysis of connectivity in populations of a semi-aquatic mammal using kinship categories and network assortativity
Analyzing the impact of anthropogenic and natural river barriers on the dispersal of aquatic and semi-aquatic species may be critical for their conservation, but no adequate genetic methods have been developed for quantifying the effect of specific barriers on current connectivity. Knowledge of kinship relationships between individuals and reconstructions of pedigrees obtained using genomic data can be extremely useful, not only for studying the social organization of animals, but also inferring how the last few generations of offspring have dispersed. In this study, we used kinship data to analyze connectivity patterns in a small semi-aquatic mammal, the Pyrenean desman, in an area comprising two river systems with close headwaters and dams of various sizes. Using a large SNP dataset from 70 specimens, we obtained kinship categories and reconstructed pedigrees. To quantify the barrier effect of specific obstacles, we constructed kinship networks and devised a method based on the assortativity coefficient, which measures the proportion between observed and expected kinship relationships across a barrier. The estimation of this parameter enabled us to infer that the most important barrier in the area was the watershed divide between the rivers, followed by a dam on one of the rivers. Other barriers did not significantly reduce the expected number of kinship relationships across them. This strategy and the information obtained with it may be crucial in determining the most important connectivity problems in an area and help develop conservation plans aimed at improving genetic exchange between populations of threatened species.
Data from: RNAi screening reveals a large signaling network controlling the Golgi apparatus in human cells
The Golgi apparatus has many important physiological functions, including sorting of secretory cargo and biosynthesis of complex glycans. These functions depend on the intricate and compartmentalized organization of the Golgi apparatus. To investigate the mechanisms that regulate Golgi architecture, we developed a quantitative morphological assay using three different Golgi compartment markers and quantitative image analysis, and performed a kinome- and phosphatome-wide RNAi screen in HeLa cells. Depletion of 159 signaling genes, nearly 20% of genes assayed, induced strong and varied perturbations in Golgi morphology. Using bioinformatics data, a large regulatory network could be constructed. Specific subnetworks are involved in phosphoinositides regulation, acto-myosin dynamics and mitogen activated protein kinase signaling. Most gene depletion also affected Golgi functions, in particular glycan biosynthesis, suggesting that signaling cascades can control glycosylation directly at the Golgi level. Our results provide a genetic overview of the signaling pathways that control the Golgi apparatus in human cells.
Data from: Comparative developmental transcriptomics reveals rewiring of a highly conserved gene regulatory network during a major life history switch in the sea urchin genus Heliocidaris
The ecologically significant shift in developmental strategy from planktotrophic (feeding) to lecithotrophic (nonfeeding) development in the sea urchin genus Heliocidaris is one of the most comprehensively studied life history transitions in any animal. Although the evolution of lecithotrophy involved substantial changes to larval development and morphology, it is not known to what extent changes in gene expression underlie the developmental differences between species, nor do we understand how these changes evolved within the context of the well-defined gene regulatory network (GRN) underlying sea urchin development. To address these questions, we used RNA-seq to measure expression dynamics across development in three species: the lecithotroph Heliocidaris erythrogramma, the closely related planktotroph H. tuberculata, and an outgroup planktotroph Lytechinus variegatus. Using well-established statistical methods, we developed a novel framework for identifying, quantifying, and polarizing evolutionary changes in gene expression profiles across the transcriptome and within the GRN. We found that major changes in gene expression profiles were more numerous during the evolution of lecithotrophy than during the persistence of planktotrophy, and that genes with derived expression profiles in the lecithotroph displayed specific characteristics as a group that are consistent with the dramatically altered developmental program in this species. Compared to the transcriptome, changes in gene expression profiles within the GRN were even more pronounced in the lecithotroph. We found evidence for conservation and likely divergence of particular GRN regulatory interactions in the lecithotroph, as well as significant changes in the expression of genes with known roles in larval skeletogenesis. We further use coexpression analysis to identify genes of unknown function that may contribute to both conserved and derived developmental traits between species. Collectively, our results indicate that distinct evolutionary processes operate on gene expression during periods of life history conservation and periods of life history divergence, and that this contrast is even more pronounced within the GRN than across the transcriptome as a whole.
Data from: Using local ecological knowledge to build mutualistic networks in hyper-diverse and logistically challenging ecosystems
<p>1. Collecting interaction data to build frugivory or seed dispersal networks is logistically challenging in ecosystems that have very high plant and animal diversity and/or where fieldwork is difficult or dangerous. Consequently, the majority of available networks are from ecosystems with low species diversity or they represent a sub-set of the community. </p> <p>2. Here, we propose an approach using local ecological knowledge (LEK) of indigenous communities to build interaction databases and weighted networks that would otherwise be difficult to achieve with direct observations. Indigenous communities live and work in many hyper-diverse ecosystems and the people within these communities often have detailed knowledge of ecological processes. </p> <p>3. Working in a Sundaland biodiversity hotspot – Royal Belum State Park, Peninsular Malaysia – we used field data, visually-oriented interviews with indigenous people (Orang Asli, in the Jahai and Temiar ethnic subgroups), and published records to collate interactions, and their frequency of occurrence of animal fruit consumption and seed dispersal. </p> <p>4. We documented 2060 fruit consumption and 1330 seed dispersal interactions among 164 plant species and 34 animal taxa, the latter representing groups of closely related species or individual species. The majority of the interactions (97%) were identified by the LEK interviews, with the additional methods (field data and published records) used to support and marginally expand the interview data. The metrics for the networks we built reflect those of networks structured by biological mechanisms, supporting the validity of our novel method. </p> <p>5. Local ecological knowledge is highly relevant for building detailed databases for mutualistic interactions in hyper-diverse and/or challenging ecosystems. Such ecosystems are among the most vulnerable on earth, harbouring ecological interactions that are often poorly documented at a community-level. We show how LEK can broaden our knowledge of such sensitive ecosystems, but our approach is useful for any ecosystem where people retain rich local ecological knowledge.</p>
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.