Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
295
datasets available to search
ShareScore release 0.9.0
Dataset results
295 results for “Structure prediction”
Data from: Bill morphology and neutral genetic structure both predict variation in acoustic signals within a bird population
Open the record for dataset details and reuse information.
Data from: Long-term mechanistic hindcasts predict the structure of experimentally-warmed intertidal communities
Open the record for dataset details and reuse information.
Recent climate change and historical population structure predict spatial patterns of admixture between two host-specialized pine sawfly species
Open the record for dataset details and reuse information.
Structural and socioeconomic features of cities predict migratory bird species richness
Open the record for dataset details and reuse information.
Both source and recipient range phylogenetic community structure can predict the outcome of avian introductions
Open the record for dataset details and reuse information.
Non-structural carbohydrates predict survival in saplings of temperate trees under carbon stress
Open the record for dataset details and reuse information.
Mitigating flicker noise in high-precision photometry. I - Characterization of the noise structure, impact on the inferred transit parameters, and predictions for CHEOPS observations
<p>This repository contains the publicly available artificial exoplanet transit light curves that has been generated in HMI observations.</p> <p>Descriptions of the data are encapsulated in the READme.dat file. For further details, please report to Sec. 3 of the paper (arXiV link: <a href="https://arxiv.org/abs/2003.07707">https://arxiv.org/abs/2003.07707</a>).</p> <p>If you find these synthetic data useful in your own research please cite the Sulis. et al., (2020) paper.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Learning Context-aware Structural Representations to Predict Antigen and Antibody Binding Interfaces
<p>These are data corresponding to the paper '<a href="https://doi.org/10.1093/bioinformatics/btaa263">Learning Context-aware Structural Representations to Predict Antigen and Antibody Binding Interfaces</a>', published in Bioinformatics 2020. The code to run the experiments can be found on github <a href="https://github.com/vamships/PECAN">here</a>.</p>
Invertebrate community structure predicts natural pest control resilience to insecticide exposure
<p>Biological pest control has become one of the central principles of ecological intensification in agriculture. However, invertebrate natural enemies within agricultural ecosystems are exposed to a myriad of different pesticides at both lethal and sub-lethal doses, that may limit their capacity to carry out pest control. An important question is how underlying diversity in invertebrate predator species, linked to their unique susceptibility to insecticides, can act to increase the resilience of natural pest control.</p> <p>We explore this issue by assessing the effects of sub-lethal insecticide exposure on the predation rates of 12 generalist predators feeding on the aphid <i>Sitobion avenae</i> (Aphididae). Predation rates within a 24 hr period were assessed (predation assessment) for each species after receiving one of the following treatments: 1) no prior deltamethrin exposure before the predation assessment (control); 2) deltamethrin exposure immediately before the predation assessment (resistance); and 3) deltamethrin exposure five days before the predation assessment (recovery). Extrapolating from these species-specific measures of resistance and recovery, we predicted the resilience of community level predation to insecticide exposure for predator communities associated with 256 arable fields in the UK.</p> <p>There was large variation in sub-lethal effects of the insecticide between even closely related species. This ranged from species showing no change in predation rates following sub-lethal insecticide exposure (high resistance), species showing only immediate depressed feeding rates after 24 hrs (high recovery), or those with depressed feeding rates after five days (low resistance and recovery).</p> <p>The community level analysis showed that resistance and recovery of natural pest control was predicted by both community phylogenetic diversity (positively) and weighted mean body mass (negatively). However, the removal of numerically dominant species from the analysis modified these effects.</p> <p><strong>Synthesis and applications. </strong>Our results highlight the role of community diversity in maintaining the resilience of natural pest control following insecticide use. Importantly, less diverse assemblages dominated by predator species that show low resilience to insecticide exposure, may show a greater depression in pest control than diverse assemblages under insecticide based farmland management. </p>
Adjacency matrices and nodal attributes for prestige and homophily predict network structure for social learning of medicinal plant knowledge
<p>Human subsistence societies have thrived in environmental extremes while maintaining biodiversity through social learning of ecological knowledge, such as techniques to prepare food and medicine from local resources. However, there is limited understanding of which processes shape social learning patterns and configuration in ecological knowledge networks, or how these processes apply to resource management and biological conservation. In this study, we test the hypothesis that the prestige (rarity or exclusivity) of knowledge shapes social learning networks. In addition, we test whether people tend to select who to learn from based on prestige (knowledge or reputation), and homophily (e.g., people of the same age or gender). We used interviews to assess five types of medicinal plant knowledge and how 303 people share this knowledge across four villages in Solomon Islands. We developed exponential random graph models (ERGMs) to test whether hypothesized patterns of knowledge sharing based on prestige and homophily are more common in the observed network than in randomly simulated networks of the same size. We found that prestige predicts five hypothesized network configurations and all three hypothesized learning patterns, while homophily predicts one of three hypothesized network configurations and five of the seven hypothesized learning patterns. These results compare the strength of different prestige and homophily effects on social learning and show how cultural practices such as intermarriage can affect certain aspects of prestige and homophily. By advancing our understanding of how prestige and homophily affect ecological knowledge networks, we identify which social learning patterns have the largest effects on biocultural conservation of ecological knowledge.</p>
The datasets used in "RNA secondary structure prediction using deep learning with thermodynamic integration"
<p>The datasets used in "RNA secondary structure prediction using deep learning with thermodynamic integration"</p>
Data from: Community structure of a Neotropical bat fauna as revealed by stable isotope analysis: Not all species fit neatly into predicted guilds
Neotropical bat communities are among the most diverse mammal communities in the world, and a better understanding of these assemblages may permit inferences about how so many species coexist. While broad trophic guilds (e.g., frugivore, insectivore) of bats are recognized, details of diet and similarities among species remain largely unknown. We used stable isotope ratios of carbon (δ13C) and nitrogen (δ15N) to characterize the community structure of a diverse Neotropical bat fauna from Belize to test predictions of niche theory and the competitive exclusion principle. We predicted that (1) interspecific variation in isotopic overlap would be greater within guilds than between guilds, and (2) no two sympatric populations would have isotopic niches that overlap completely, unless there is variation along some other axis (e.g., temporal, spatial). We additionally tested body size as an explanatory metric of potential overlap, and predicted that larger-bodied animals would have greater niche breadths. Results suggest that while guild-level characterizations of communities is at least somewhat informative, there are multiple examples of intra- and inter-guild species pairs with significantly overlapping isotopic niches, suggesting that, counter to predictions, they may compete for resources. Understanding the trophic structure of animal communities is fundamental to conservation and management of endangered species and ecosystems and important for evolutionary studies, and stable isotope analyses can provide key insights as well as informing hypotheses of the diet of species that are not well known.
Data from: Species traits and abundances predict metrics of plant–pollinator network structure, but not pairwise interactions
Plant–pollinator mutualistic networks represent the ecological context of foraging (for pollinators) and reproduction (for plants and some pollinators). Plant–pollinator visitation networks exhibit highly conserved structural properties across diverse habitats and species assemblages. The most successful hypotheses to explain these network properties are the neutrality and biological constraints hypotheses, which posit that species interaction frequencies can be explained by species relative abundances, and trait mismatches between potential mutualists respectively. However, previous network analyses emphasize the prediction of metrics of qualitative network structure, which may not represent stringent tests of these hypotheses. Using a newly documented temporally explicit alpine plant–pollinator visitation network, we show that metrics of both qualitative and quantitative network structure are easy to predict, even by models that predict the identity or frequency of species interactions poorly. A variety of phenological and morphological constraints as well as neutral interactions successfully predicted all network metrics tested, without accurately predicting species observed interactions. Species phenology alone was the best predictor of observed interaction frequencies. However, all models were poor predictors of species pairwise interaction frequencies, suggesting that other aspects of species biology not generally considered in network studies, such as reproduction for dipterans, play an important role in shaping plant–pollinator visitation network structure at this site. Future progress in explaining the structure and dynamics of mutualistic networks will require new approaches that emphasize accurate prediction of species pairwise interactions rather than network metrics, and better reflect the biology underlying species interactions.
Data from: Accounting for interspecific competition and age structure in demographic analyses of density dependence improves predictions of fluctuations in population size
Understanding species coexistence has long been a major goal of ecology. Coexistence theory for two competing species posits that intraspecific density dependence should be stronger than interspecific density dependence. Great tits and blue tits are two bird species that compete for food resources and nesting cavities. Based on long-term monitoring of these two competing species at sites across Europe, combining observational and manipulative approaches, we show that the strength of density regulation is similar for both species, and that individuals have contrasting abilities to compete depending on their age. For great tits, density regulation is driven mainly by intraspecific competition. In contrast, for blue tits, interspecific competition contributes as much as intraspecific competition, consistent with asymmetric competition between the two species. In addition, including age-specific effects of intra- and interspecific competition in density-dependence models improves predictions of fluctuations in population size by up to three times.
Data from: A trait-based approach to predict population genetic structure in bees
Understanding population genetic structure is key to developing predictions about species susceptibility to environmental change, such as habitat fragmentation and climate change. It has been theorized that life-history traits may constrain some species in their dispersal and lead to greater signatures of population genetic structure. In this study, we use a quantitative comparative approach to assess if patterns of population genetic structure in bees are driven by three key species-level life-history traits: body size, sociality, and diet breadth. Specifically, we reviewed the current literature on bee population genetic structure, as measured by the differentiation indices Nei's GST, Hedrick's G`ST, and Jost's D. We then used phylogenetic generalised linear models to estimate the correlation between the evolution of these traits and patterns of genetic differentiation. Our analyses revealed a negative and significant effect of body size on genetic structure, regardless of differentiation index utilized. For Hedrick's G`ST and Jost's D, we also found a significant impact of sociality, where social species exhibited lower levels of differentiation than solitary species. We did not find an effect of diet specialization on population genetic structure. Overall, our results suggest that physical dispersal or other functions related to body size are among the most critical for mediating population structure for bees. We further highlight the importance of standardizing population genetic measures to more easily compare studies and to identify the most susceptible species to landscape and climatic changes.
Data from: Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander
Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot.
Data from: Does population structure predict the rate of speciation? A comparative test across Australia's most diverse vertebrate radiation
Population divergence is the first step in allopatric speciation, as has long been recognized in both theoretical models of speciation and empirical explorations of natural systems. All else being equal, lineages with substantial population differentiation should form new species more quickly than lineages that maintain range-wide genetic cohesion through high levels of gene flow. However, there have been few direct tests of the extent to which population differentiation predicts speciation rates as measured on phylogenetic trees. Here, we explicitly test the links between organismal traits, population-level processes, and phylogenetic speciation rates across a diverse clade of Australian lizards that shows remarkable variation in speciation rate. Using genome-wide ddRAD data from 892 individuals, we generated a comparative dataset on isolation-by-distance and population differentiation across 104 putative species-level lineages (OTUs). We find that species show substantial variation in the extent of population differentiation, and this variation is predicted by organismal traits that are thought to be proxies for dispersal and deme size. However, variation in population structure does not predict variation in speciation rate. Our results suggest that population differentiation is not the rate-limiting step in species formation and that other ecological and historical factors are primary determinants of speciation rates at macroevolutionary scales.
Early life learning ability predicts adult social structure, with potential implications for fitness outcomes in the wild
1. Social environments influence important ecological processes and can determine how selection acts on traits. Cognitive abilities can shape these social environments and in turn, affect individuals' fitness. 2. To understand how cognitive abilities evolve, we need to understand the complex interplay between an individual's cognitive abilities, the social environment that they inhabit and the fitness consequences of these relationships. 3. We measured the associative learning ability of pheasant chicks, Phasianus colchicus, then released them into the wild where we quantified their social position by observing their associations at feeding stations and monitored the number of days survived. 4. We observed disassortative mixing by learning performance at the population level, and poor learners had more associates than good learners. Learning was beneficial for survival when focal individuals had fewer than four associates, but survival probability across learning abilities equalized for individuals with more than four associates. 5. While the mechanisms underlying these relationships remain to be determined, the patterns of association exhibited by pheasants at feeders can be predicted by individual variation in cognitive performances and we suspect these patterns are related to differences in information use. Critically, these resulting patterns of association have fitness consequences for individuals that cannot be explained directly by their cognitive ability, but which could mediate selection on cognition.
Data from: Drivers of the spatial scale that best predict primate responses to landscape structure
Understanding the effect of landscape structure on biodiversity is critically needed to improve management strategies. To accurately evaluate such effect, landscape metrics need to be assessed at the correct scale, i.e. considering the spatial extent at which species‐landscape relationship is strongest (scale of effect, SE). Although SE is highly variable, its drivers are poorly known, but of key relevance to understand the way species use the landscape. In this study, we evaluate whether and how species traits, biological responses, landscape variables and the regional context of the study drive SE in Mexican primates. We estimated the relative abundance and immature‐to‐female ratio (a proxy of reproductive success) of howler monkeys (Alouatta palliata and A. pigra) and spider monkeys (Ateles geoffroyi) in 48 forest patches from four rainforest regions (12 patches per region) with different land‐use intensity. We then assessed the composition (forest cover, matrix functionality) and configuration (forest patch density, connectors' density, forest edge density) of local landscapes considering 13 scales (100 to 1300‐m radius) to identify the spatial extent at which each landscape variable best predict each response variable in each species and region. We found that SE did not differ significantly among the drivers evaluated. However, it tended to be lower for connectors' density than for forest patch density and forest edge density, probably because connectors' density is associated with local‐scale processes such as supplementary dynamics. Surprisingly, SE also tended to be higher in the more disturbed region than in the rest of the regions, probably because primates in the more disturbed region used larger areas of the landscape. Our findings therefore suggest that SE depends more strongly on landscape variables and regional context than on species traits and biological responses, and hence, especial caution should be taken when attempting to generalize SE to different explanatory variables and regions.
Data from: Ocean circulation model predicts high genetic structure in a long-lived pelagic developer
Understanding the movement of genes and individuals across marine seascapes is a long-standing challenge in marine ecology, and can inform our understanding of local adaptation, the persistence and movement of populations, and the spatial scale of effective management. Patterns of gene flow in the ocean are often inferred based on population genetic analyses coupled with knowledge of species' dispersive life histories. However, genetic structure is the result of time-integrated processes, and may not capture present-day connectivity between populations. Here we use a high-resolution oceanographic circulation model to predict larval dispersal along the complex coastline of western Canada that includes the transition between two well-studied zoogeographic provinces. We simulate dispersal in a benthic sea star with a 6-10 week pelagic larval phase, and test predictions of this model against previously observed genetic structure including a strong phylogeographic break within the zoogeographical transition zone. We also test predictions with new genetic sampling in a site within the phylogeographic break. We find that the coupled genetic and circulation model predicts the high degree of genetic structure observed in this species, despite its long pelagic duration. High genetic structure on this complex coastline can thus be explained through ocean circulation patterns which tend to retain passive larvae within 20 - 50 km of their parents, suggesting a necessity for close-knit design of Marine Protected Area networks.
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.