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13,064 results for “predictions”
Data from: Testosterone production ability predicts breeding success and tracks breeding stage in male finches
Testosterone (T) is an important mediator of reproductive behaviours and potential target for selection. However, there are few data relating natural variation in T to fitness estimates. Here, we used the GnRH challenge (an injection of gonadotropin-releasing hormone which stimulates maximal T release), to examine how individual differences in T relate to reproductive success and how T changes across date and breeding stage. We measured pre- and post-challenge T, in captive male Gouldian finches (Erythrura gouldiae), before and after introducing females, and across breeding stage. Post-challenge T before introducing females positively predicted breeding success. Post-challenge T levels were unrelated to date, but strongly related to stage; T production ability was strongly attenuated in incubating males. Prechallenge T levels related only to date. Our results suggest that T production ability is an important target for selection and that when males invest heavily in parental care they reduce their sensitivity to GnRH.
Data from: Do freshwater ecoregions and continental shelf width predict patterns of historical gene flow in the freshwater fish Poecilia butleri?
We examined historical patterns of gene flow in the freshwater fish Poecilia butleri in western Mexico. We tested the hypothesis that the boundaries between four freshwater ecological communities (ecoregions) might have limited the movement of P. butleri because changes in species compositions might restrict establishment between adjacent ecoregions, even in situations where a physical barrier is absent. Hence, we predicted that boundaries between ecoregions should correspond to phylogeographical breaks in P. butleri. We also tested the hypothesis that the width of the continental shelf affected historical gene flow in P. butleri because a broad continental shelf provides a greater opportunity for rivers to coalesce during historical episodes of low sea levels as opposed to a narrow continental shelf that should restrict the potential for gene flow among adjacent rivers. Hence, we predicted greater amounts of historical gene flow among neighbouring river basins in the region of western Mexico where the continental shelf is wider, whereas, in the region where the continental shelf is narrower, we expected to detect limited levels of historical gene flow. We analyzed mitochondrial DNA sequence data (cytochrome b) taken from 264 individuals of P. butleri collected from 34 locations distributed across four different ecoregions in western Mexico. To examine patterns of phylogenetic diversification and historical gene flow in P. butleri, we employed several analytical approaches, including traditional tree-based phylogenetic analyses (likelihood and parsimony), haplotype network reconstruction, analyses of molecular variance, and spatial analysis of molecular variance. We found genetic breaks coinciding with two out of three different ecoregion boundaries, suggesting limited historical gene flow. In addition to different species compositions between these adjacent ecoregions, geological features such as the Trans-Mexican Volcanic Belt and the mountainous topography in south-western Mexico, likely contributed to these observed genetic breaks. By contrast, no genetic break was evident between two other ecoregions, a result that partially rejects our first hypothesis. Several results were consistent with our second hypothesis. Changes in the width of the continental shelf in western Mexico are associated with the observed patterns of historical gene flow. Our results indicate that the interactions among multiple geological and biological factors affect the spatial patterns of genetic diversity of widespread freshwater species.
Data from: Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data
While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12×11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10,000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species' presence for both fine and coarse grain habitat suitability and distribution modelling.
Data from: What caused over a century of decline in general intelligence? Testing predictions from the genetic selection and neurotoxin hypotheses
Several converging lines of evidence indicate that general intelligence (g) has declined in Western populations. The causes of these declines are debated. Here, two hypotheses are tested: (1) selection acting against genetic variants that promote g causes the decline and (2) the presence of neurotoxic pollution in the environment causes the decline. A linear mixed model was devised to test (1) and (2), in which the secular decline in a "heritable g" (g.h) chronometric factor (comprised of convergent indicators of simple reaction time, working memory, utilization frequencies of high difficulty and also social-intelligence-indicating vocabulary items and per capita macro-innovation rates) was predicted using a neurotoxin chronometric factor (comprised of convergent secular trends among measures of lead, mercury and dioxin + furan pollution, in addition to alcohol consumption) and a polygenic score chronometric factor (comprised of polygenic score means for genetic variants predictive of g, sourced from US and Icelandic age-stratified cohorts). Bivariate correlations revealed that (other than time) only the polygenic score factor was significantly associated with declining g.h (r = .393, p < .05 vs. .033, ns for the neurotoxin factor). Using a hierarchical linear mixed model approach incorporating 25 year lags between the predictors and g.h, time period, operationalized categorically as fifths of a century, accounted for the majority of the variance in the decline in g.h (partial η^2 = .584, p < .05). Net of time period and neurotoxins, changing levels of polygenic scores also significantly predicted variance in the decline in g.h (partial η^2 = .253, p < .05); however, changing levels of neurotoxins did not significantly predict variance in g.h net of time (partial η^2 = .027 ns). Within-period analysis indicates that the independent significant positive effect of the polygenic score factor on g.h was restricted to the third fifth of a century period (β = .202, p < .05).
Data from: Accurate genomic prediction of Coffea canephora in multiple environments using whole-genome statistical models
Genomic selection have been proposed as the standard method to predict breeding values in animal and plant breeding. Although some crops have benefited from this methodology, studies in Coffea are still emerging. To date, there have been no studies of how well genomic prediction models work across populations and environments for different complex traits in coffee. Considering that predictive models are based on biological and statistical assumptions, it is expected that their performance vary depending on how well these assumptions align with the true genetic architecture of the phenotype. To investigate this, we used data from two recurrent selection populations of Coffea canephora, evaluated in two locations, and single nucleotide polymorphisms identified by Genotyping-by-Sequencing. In particular, we evaluated the performance of 13 statistical approaches to predict three important traits in the coffee — production of coffee beans, leaf rust incidence and yield of green beans. Analyses were performed for predictions within-environment, across locations and across populations to assess the reliability of genomic selection. Overall, differences in the prediction accuracy of the competing models were small, although the Bayesian methods showed a modest improvement over other methods, at the cost of more computation time. As expected, predictive accuracy for within-environment analysis, on average, were higher than predictions across locations and across populations. Our results support the potential of genomic selection to reshape traditional plant breeding schemes. In practice, we expect to increase the genetic gain per unit of time by reducing the length cycle of recurrent selection in coffee.
Data from: Corticosterone predicts foraging behavior and parental care in macaroni penguins
Corticosterone has received considerable attention as the principal hormonal mediator of allostasis or physiological stress in wild animals. More recently, it has also been implicated in the regulation of parental care in breeding birds, particularly with respect to individual variation in foraging behaviour and provisioning effort. There is also evidence that prolactin can work either inversely or additively with corticosterone to achieve this. Here we test the hypothesis that endogenous corticosterone plays a key physiological role in the control of foraging behaviour and parental care using a combination of exogenous corticosterone treatment, time-depth telemetry, and physiological sampling of female macaroni penguins (Eudyptes chrysolophus) during the brood-guard period of chick rearing, while simultaneously monitoring patterns of prolactin secretion. Plasma corticosterone levels were significantly higher in females given exogenous implants relative to those receiving sham implants. Increased corticosterone levels were associated with significantly higher levels of foraging and diving activity, and greater mass gain in implanted females. Elevated plasma corticosterone was also associated with an apparent fitness benefit in the form of increased chick mass. Plasma prolactin levels did not correlate with corticosterone levels at any time, nor was prolactin correlated with any measure of foraging behaviour or parental care. Our results provide support for the corticosterone-adaptation hypothesis, which predicts that higher corticosterone levels support increased foraging activity and parental effort.
Data from: Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat
Predicting a species' distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2−3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert-informed modeling approach could be applied to opportunistic presence-only data when sampling bias is a concern and expert knowledge is available.
Data from: Predictable food supplies induce plastic shifts in avian scaled body mass
Urbanization constitutes one of the most profound forms of land-use change and strongly affects global biodiversity and ecosystem functioning. Expansion of urban areas typically leads to species loss but may also induce more subtle changes in species dynamics through selection or plasticity. Using a dual correlative (field) and experimental (aviary) approach, we here show that free-ranging urban house sparrows in southern France were smaller and lighter than their rural counterparts after allometric scaling, whereas 2 independent indices of nutritional (feather growth rates) and developmental (feather asymmetry) stress did not vary with urbanization. When subjecting these individuals to urban or rural diets in a highly predictable, controlled setting, rural but not urban sparrows decreased their body mass, independent of diet type, to the extent that initial scaled mass differences between urban and rural birds disappeared by the end of the captive period. By integrating field- and aviary measurements of body size and mass with indices of nutritional and developmental stress, we conclude that the lower scaled body masses of urban birds likely reflect a plastic response to predictable food supplies, possibly mediated through predation. Urban environments therefore do not necessarily constitute nutritionally stressful environments for species that typically cohabit with humans, such as house sparrows.
Data from: Social-ecological landscape patterns predict woody encroachment from native tree plantings in a temperate grassland
Afforestation is often viewed as the purposeful planting of trees in historically non-forested grasslands, but an unintended consequence is woody encroachment, which should be considered part of the afforestation process. In North America's temperate grassland biome, Eastern redcedar (Juniperus virginiana L.) is a native species used in tree plantings that aggressively invades in the absence of controlling processes. Cedar is a well-studied woody encroacher, but little is known about the degree to which cedar windbreaks, which are advocated for in agroforestry programs, are contributing to woody encroachment, what factors are associated with cedar spread from windbreaks, nor where encroachment from windbreaks is occurring in contemporary social–ecological landscapes. We used remotely sensed imagery to identify the presence and pattern of woody encroachment from windbreaks in the Nebraska Sandhills. We used multimodel inference to compare three classes of models representing three hypotheses about factors that could influence cedar spread: (a) windbreak models based on windbreak structure and design elements; (b) abiotic models focused on local environmental conditions; and (c) landscape models characterizing coupled human-natural features within the broader matrix. Woody encroachment was evident for 22% of sampled windbreaks in the Nebraska Sandhills. Of our candidate models, our inclusive landscape model carried 92% of the model weight. This model indicated that encroachment from windbreaks was more likely near roadways and less likely near farmsteads, other cedar plantings, and waterbodies, highlighting strong social ties to the distribution of woody encroachment from tree plantings across contemporary landscapes. Cedar control efforts are insufficient for nearly one-quarter of windbreaks in the Nebraska Sandhills. Our model findings indicate where additional investments into cedar control can be prioritized to prevent cedar spread from windbreaks. This approach can serve as a model in other temperate regions to identify where woody encroachment resulting from temperate agroforestry programs is emerging.
Data from: A quantitative test of the predicted relationship between countershading and lighting environment.
Countershading, a vertical luminance gradient from a dark back to a light belly, is perhaps the most common coloration phenotype in the animal kingdom. Why? We investigated whether countershading functions as self-shadow concealment (SSC) in ruminants. We calculated "optimal" countershading for SSC by measuring illumination falling onto a model ruminant as a function of time of day and lighting environment. Calibrated images of 114 species of ruminant were compared to the countershading model, and phylogenetic analyses were used to find the best predictors of coats' countershading characteristics. In many species, countershading was close to the model's prediction of "optimal" countershading for SSC. Stronger countershading was associated with increased use of open lighting environments, living closer to the equator, and small body size. Abrupt transitions from dark to light tones were more common in open lighting environments but unassociated with group size or antipredator behavior. Though the SSC hypothesis prediction for stronger countershading in diurnal species was not supported and noncountershaded or reverse-countershaded species were unexpectedly common, this basic pattern of associations is explained only by the SSC hypothesis. Despite extreme variation in lighting conditions, many terrestrial animals still find protection from predation by compensating for their own shadows.
Data from: Partner's age, not social environment, predicts extrapair paternity in wild great tits (Parus major)
An individual's fitness is not only influenced by its own phenotype, but by the phenotypes of interacting conspecifics. This is likely to be particularly true when considering fitness gains and losses caused by extrapair matings, as they depend directly on the social environment. While previous work has explored effects of dyadic interactions, limited understanding exists regarding how group-level characteristics of the social environment affect extrapair paternity (EPP) and cuckoldry. We use a wild population of great tits (Parus major) to examine how, in addition to the phenotypes of focal parents, two neighborhood-level traits – age and personality composition – predict EPP and cuckoldry. We used the well-studied trait "exploration behavior" as a measure of the reactive-proactive personality axis. Because breeding pairs inhabit a continuous "social landscape", we first established an ecologically relevant definition of a breeding "neighborhood" through genotyping parents and nestlings in a 51-ha patch of woodland and assessing the spatial predictors of EPP events. Using the observed decline in likelihood of EPP with increasing spatial separation between nests, we determined the relevant neighborhood boundaries, and thus the group phenotypic composition of an individual's neighborhood, by calculating the point at which the likelihood of EPP became negligible. We found no evidence that "social environment" effects (i.e. neighborhood age or personality composition) influenced EPP or cuckoldry. We did, however, find that a female's own age influenced the EPP of her social mate, with males paired to older females gaining more EPP, even when controlling for the social environment. These findings suggest that partner characteristics, rather than group phenotypic composition, influence mating activity patterns at the individual level.
Data from: The evolution of vertebrate eye size across an environmental gradient: phenotype does not predict genotype in a Trinidadian killifish
Vertebrates exhibit substantial variation in eye size. Eye size correlates positively with visual capacity and behaviors that enhance fitness, such as predator avoidance. This foreshadows a connection between predation and eye size evolution. Yet, the conditions that favor evolutionary shifts in eye size, besides the well-known role for light availability, are unclear. We tested the influence of predation on the evolution of eye size in Trinidadian killifish, Rivulus hartii. Rivulus are located across a series of communities where they coexist with visually oriented piscivores ('high predation' sites), and no predators ('Rivulus-only' sites). Wild-caught Rivulus from high predation sites generally exhibited a smaller relative eye size than communities that lack predators. Yet, such differences were inconsistent across rivers. Second-generation common garden reared fish revealed repeatable decreases in eye size in Rivulus from high predation sites. We performed additional experiments that tested the importance of light and resources on eye size evolution. Sites that differ in light or resource availability did not differ in eye size. Our results argue that differences in predator-induced mortality underlie genetically-based shifts in vertebrate eye size. We discuss the drivers of eye size evolution in light of the nonparallel trends between the phenotypic and common garden results.
Data from: Aldosterone reduction rate after saline infusion may be a novel clinical prediction of determining subtypes of primary aldosteronism
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective</b>Accurate assessment of the localization of aldosterone-producing adenomas (APAs) is essential for the treatment of primary aldosteronism (PA). Although adrenal venous sampling (AVS) is the standard method of reference for subtype diagnosis in PA, controversy exists concerning the criteria for interpretation. This study aimed to determine better indicators that can reliably predict subtypes of PA. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Method</b>Retrospective analysis in single-cohort including 209 patients with PA who were subjected to AVS. 82 patients whose plasma aldosterone concentrations (PAC) were normalized after surgery were histopathologically or genetically diagnosed with APA. The accuracy of image findings was compared to AVS results. Receiver operating characteristic (ROC) curve analysis between the operated and no apparent laterality groups was performed using AVS parameters and loading test for diagnosis of PA. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Result </b>The agreement between image findings and AVS results was 56.3%. ROC curve analysis revealed that lateralization index (LI) after ACTH stimulation cutoff value was 2.40, with 98.8% sensitivity and 97.1% specificity. The contralateral suppression index (CSI) cutoff value was 1.19, with 98.0% sensitivity and 93.9% specificity. All patients over the LI and CSI cutoff values exhibited unilateral subtypes. Among the loading test, <span><span>the best classification accuracy was achieved using the </span></span>PAC reduction rate after saline infusion<span><span>test (SIT) >33.8%, which yielded 87.2% sensitivity or PAC after SIT <87.9 pg/mL 86.2% specificity for predicting bilateral PA. </span></span></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Conclusion</b>The combined criterion of the PAC reduction rate and PAC after SIT may determine a subset of patients with APA who should be performed AVS for validation. </span></span></span></span></span></span></span></span></span></span></span></p> <p><br> </p>
Data from: SIDER: an R package for predicting trophic discrimination factors of consumers based on their ecology and phylogenetic relatedness
Stable isotope mixing models (SIMMs) are an important tool used to study species' trophic ecology. These models are dependent on, and sensitive to, the choice of trophic discrimination factors (TDF) representing the offset in stable isotope delta values between a consumer and their food source when they are at equilibrium. Ideally, controlled feeding trials should be conducted to determine the appropriate TDF for each consumer, tissue type, food source, and isotope combination used in a study. In reality however, this is often not feasible nor practical. In the absence of species-specific information, many researchers either default to an average TDF value for the major taxonomic group of their consumer, or they choose the nearest phylogenetic neighbour for which a TDF is available. Here, we present the SIDER package for R, which uses a phylogenetic regression model based on a compiled dataset to impute (estimate) a TDF of a consumer. We apply information on the tissue type and feeding ecology of the consumer, all of which are known to affect TDFs, using Bayesian inference. Presently, our approach can estimate TDFs for two commonly used isotopes (nitrogen and carbon), for species of mammals and birds with or without previous TDF information. The estimated posterior probability provides both a mean and variance, reflecting the uncertainty of the estimate, and can be subsequently used in the current suite of SIMM software. SIDER allows users to place a greater degree of confidence on their choice of TDF and its associated uncertainty, thereby leading to more robust predictions about trophic relationships in cases where study-specific data from feeding trials is unavailable. The underlying database can be updated readily to incorporate more stable isotope tracers, replicates and taxonomic groups to further increase the confidence in dietary estimates from stable isotope mixing models, as this information becomes available.
Data from: Finer-scale habitat predicts nest survival in grassland birds more than management and landscape: a multi-scale perspective
1. Birds may respond to habitat at multiple scales, ranging from microhabitat structure to landscape composition. North American grassland bird distributions predominantly reside on private lands, and populations have been consistently declining. Many of these lands are enrolled in U.S. federal conservation programmes, and properly guided management policies could alleviate declines. However, more evaluative research is needed on the effects of management policies juxtaposed with other multi-scale habitat features. Furthermore, research focused on nest survival is arguably more valuable because habitat associations with avian densities can sometimes be deceptive. 2. We investigated nest survival of a grassland facultative (red-winged blackbird, Agelaius phoeniceus) an obligate species (dickcissel, Spiza americana), and two nesting communities (ground and above-ground nesters) relative to management and multi-scale habitat (nest-site characteristics, in-field microhabitat, patch metrics, and landscape context). Our study was conducted on private lands in Illinois (2011-2014) and directly linked to policy-based management (disking, herbicidal spraying, spray/interseeding) and landowner decisions. 3. Multi-scale models explained more variation in nest survival compared to single scales or management in three of four analyses (blackbirds, dickcissels, and above-ground nesters). Finer-scale habitat variables, such as nest-site characteristics, were more often in top and among the competitive models relative to landscape factors. 4. Compared with other management types, disking (i.e. tractor-pulled disc harrows removed approximately 50% of vegetation) displayed distinct effects and positively influenced nest survival in above-ground nesters. Also, greater proportions of a field managed cumulatively and yearly, regardless of type, generally improved nest survival for dickcissels and above-ground nesters. All groups except above-ground nesters had generally higher nest survival in native grass fields. 5. Synthesis and applications. Habitat practitioners can improve nest survival for certain grassland birds by directly affecting infield-microhabitat vegetation and structure. However, characteristics associated with specific nest locations often drive nest survival. We suggest habitat managers and agency staff promote native grass practices and management, such as disking, to enhance nest survival of grassland bird populations. Management will likely be most effective in favourable unfragmented grassland landscapes with less surrounding forested areas, which also promote other important responses (e.g. colonization and persistence) of target species.
Data from: The utility of normalized difference vegetation index for predicting African buffalo forage quality
Many studies of mammalian herbivores have employed remotely sensed vegetation greenness, in the form of Normalized Difference Vegetation Index (NDVI) as a proxy for forage quality. The assumption that reflected greenness represents forage quality often goes untested, and limited data exist on the relationships between remotely sensed and traditional forage nutrient indicators. We provide the first study connecting NDVI and forage nutrient indicators within a free-ranging African herbivore ecosystem. We examined the relationships between fecal nutrient levels (nitrogen and phosphorus), forage nutrient levels, body condition, and NDVI for African buffalo (Syncerus caffer) in a South African savanna ecosystem over a 2-year period (2001 and 2002). We used an information-theoretic approach to rank models of fecal nitrogen (Nf) and phosphorus (Pf) as functions of geology, season, and NDVI in each year separately. For each year, the highest ranked models for Nf accounted for 61% and 65% of the observed variance, and these models included geology, season, and NDVI. The top-ranked model for Pf in 2001, although capturing 54% of the variability, did not include NDVI. In 2002, we could not identify a top ranking model for phosphorus (i.e., all models were within 2 AICc of each other). Body condition was most highly correlated (equation image; P ≤ 0.001) with NDVI at a 1 month time lag and with Nf at a 3 months time lag (equation image; P ≤ 0.001), but was not significantly correlated with Pf. Our findings suggest that NDVI can be used to index nitrogen content of forage and is correlated with improved body condition in African buffalo. Thus, NDVI provides a useful means to assess forage quality where crude protein is a limiting resource. We found that NDVI accounted for more than a seasonal effect, and in a system where standing biomass may be high but of low quality, understanding available nutrients is useful for management.
BNN_DNAPL_MassDischa_Prediction
<p>The data used in paper "Modeling upscaled mass discharge from complex DNAPL source zones using a Bayesian Neural Network: prediction accuracy, uncertainty quantification and source zone feature importance"</p>
HOMOLOBIND predictions
<p>This dataset contains results of the HOMOLOBIND program ( http://fredpdavis.com/homolobind ) for proteome-wide prediction of protein and ligand binding sites, described in:</p> <p>Proteome-wide prediction of overlapping protein and ligand binding sites using structure.<br /> Davis FP, <em>Molecular BioSystems</em>, 2011<br /> http://dx.doi.org/10.1039/C0MB00200C</p> <p> </p> <p>The files contain predicted binding sites for several complete proteomes from the Nov 1, 2009 release of SUPERFAMILY:</p> <ul> <li>Homo sapiens: hs.homolobind.out.gz</li> <li>Mus musculus: mm.homolobind.out.gz</li> <li>Drosophila melanogaster: dm.homolobind.out.gz</li> <li>Caenorhabditis elegans: ce.homolobind.out.gz</li> <li>Saccharomyces cerevisiae: sc.homolobind.out.gz</li> <li>Escherichia coli: ec.homolobind.out.gz</li> <li>NCBI viral sequence set: vl.homolobind.out.gz</li> </ul> <p> </p>
Dynamic re-calibration of perceived size in fovea and periphery through predictable size changes
<p>Dataset relative to the following publication:</p> <p>Valsecchi, M. & Gegenfurtner, K.R (2016). Dynamic re-calibration of perceived size in fovea and periphery through predictable size changes. Current Biology, 26, 59-63.</p> <p>Each folder contains the data relative to one experiment and the script that was used to generate them. </p> <p>Each data folder contains a description of the data format which should be sufficient to replicate the analyses as performed in the paper. </p> <p>Additional info can be deducted fromt he experimental scripts.</p>
An Architecture-aware Approach to Hierarchical Online Failure Prediction
<p>Supplementary material for the paper:</p> <p>"An Architecture-aware Approach to Hierarchical Online Failure Prediction".</p> <p>Included in the supplementary material are:</p> <ul> <li>Architectural Dependency Model (ADM): the ADM used in the evaluation (exported to yml format).</li> <li>Failure Propagation Model (FPM): the structure of the FPM and the corresponding conditional probability tables.</li> <li>Proof-of-concept implementation of Hora, including instruction of how to build, run, and analyze the results. Note: Hora currently works only on Linux due to a limitation in R bridge for Windows.</li> <li>Evaluation results of two failure scenarios; memory leak, system overload and the overall result.</li> </ul> <p>Additionally, the following datasets used in the experiment are also provided:</p> <ul> <li>35-SystemOverload.zip</li> <li>36-MemoryLeak.zip</li> </ul>
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.