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5,805 results for “Data model”
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: Characterizing neutral and adaptive genomic differentiation in a changing climate: the most northerly freshwater fish as a model
Arctic freshwater ecosystems have been profoundly affected by climate change. Given that the Arctic charr (Salvelinus alpinus) is often the only fish species inhabiting these ecosystems, it represents a valuable model for studying the impacts of climate change on species life history diversity and adaptability. Using a genotyping-by-sequencing approach, we identified 5976 neutral single nucleotide polymorphisms (SNPs) and found evidence for reduced gene flow between allopatric morphs from two high Arctic lakes, Linne´vatn (Anadromous, Normal, and Dwarf) and Ellasjøen (Littoral and Pelagic). Within each lake, the degree of genetic differentiation ranged from low (Pelagic vs. Littoral) to moderate (Anadromous and Normal vs. Dwarf). We identified 17 highly diagnostic, putative adaptive SNPs that differentiated the allopatric morphs. Although we found no evidence for adaptive differences between morphs within Ellasjøen, we found evidence for moderate (Anadromous vs. Normal) to high genetic differentiation (Anadromous and Normal vs. Dwarf) among morphs within Linne´vatn based on two adaptive loci. As these freshwater ecosystems become more productive, the frequency of sympatric morphs in Ellasjøen will likely shift based on foraging opportunities, whereas the propensity to migrate may decrease in Linne´vatn, increasing the frequency of the Normal morph. The Dwarf charr was the most genetically distinct group. Identifying the biological basis for small body size should elucidate the potential for increased growth and subsequent interbreeding with sympatric morphs. Overall, neutral and adaptive genomic differentiation between allopatric and some sympatric morphs suggests that the response of Arctic charr to climate change will be variable across freshwater ecosystems.
Data from: Using filter-based community assembly models to improve restoration outcomes
1. Ecological filter models derived from community assembly theory can inform restoration planning by highlighting management actions most likely to affect community composition. Despite growing interest in these models, many restoration studies solely manipulate a single filter—the biotic filter by altering interspecific competition in studies—while ignoring abiotic and dispersal filters that may also influence restoration success. 2. To examine how manipulating all three filters (biotic, abiotic, dispersal) affected restoration in an annual-type grassland, we seeded native forbs from the same functional group as a target invader to increase biotic resistance to invasion (biotic filter), cut standing biomass and either removed it or returned it to plots as litter to alter light conditions (abiotic filter), and added native forbs at different seeding rates to alter density of establishing native populations (dispersal filter). We measured restoration success by recording native species and invader cover in plots. 3. The addition of native species with phenological and morphological traits similar to the target invader reduced invasion and increased native populations, but only in litter-free plots when high-densities of native seed were added. 4. Seeding two species with functional traits similar to the invader was more effective at reaching restoration goals than seeding just one functionally similar species. As such, trait differences among restoration species, even species belonging to the same functional group, may increase biotic resistance to invasion in restored communities. 5. Litter removal altered native-invader interactions. When litter was kept, added natives did not reduce invader cover. However, when litter was removed, added natives led to declines in invader cover. 6. Increasing native seeding rates led to larger native populations and increased invasion resistance. 7. Synthesis and applications. In this study, simultaneously manipulating biotic, abiotic and dispersal filters was necessary to optimize restoration outcomes. In particular, the biotic filter only contributed to successful restoration outcomes under abiotic and dispersal conditions that were created through management actions specifically targeting these two additional filters. Restoration planning based on filter models should incorporate actions that target all three filters, rather than solely focusing on the biotic filter.
Data from: Model-based species delimitation: are coalescent species reproductively isolated?
A large and growing fraction of systematists define species as independently evolving lineages that may be recognized by analyzing the population genetic history of alleles sampled from individuals belonging to those species. This has motivated the development of increasingly sophisticated statistical models rooted in the multispecies coalescent process. Specifically, these models allow for simultaneous estimation of the number of species present in a sample of individuals and the phylogenetic history of those species using only DNA sequence data from independent loci. These methods hold extraordinary promise for increasing the efficiency of species discovery, but require extensive validation to ensure that they are accurate and precise. Whether the species identified by these methods correspond to the species that would be recognized by alternative species recognition criteria (such as measurements of reproductive isolation) is currently an open question, and a subject of vigorous debate. Here we perform an empirical test of these methods by making use of a classic model system in the history of speciation research, flies of the genus Drosophila. Specifically, we use the uniquely comprehensive data on reproductive isolation that is available for this system, along with DNA sequence data, to ask whether Drosophila species inferred under the multispecies coalescent model correspond to those recognized by many decades of speciation research. We found that coalescent based and reproductive isolation based methods of inferring species boundaries are concordant for 77% of the species pairs. We explore and discuss potential explanations for these discrepancies. We also found that the amount of prezygotic isolation between two species is a strong predictor of the posterior probability of species boundaries based on DNA sequence data, regardless of whether the species pairs are sympatrically or allopatrically distributed.
Data from: What explains rare and conspicuous colours in a snail? A test of time-series data against models of drift, migration or selection
It is intriguing that conspicuous colour morphs of a prey species may be maintained at low frequencies alongside cryptic morphs. Negative frequency-dependent selection by predators using search images ('apostatic selection') is often suggested without rejecting alternative explanations. Using a maximum likelihood approach we fitted predictions from models of genetic drift, migration, constant selection, heterozygote advantage or negative frequency-dependent selection to time-series data of colour frequencies in isolated populations of a marine snail (Littorina saxatilis), re-established with perturbed colour morph frequencies and followed for >20 generations. Snails of conspicuous colours (white, red, banded) are naturally rare in the study area (usually <10%) but frequencies were manipulated to levels of ~50% (one colour per population) in 8 populations at the start of the experiment in 1992. In 2013, frequencies had declined to ~15–45%. Drift alone could not explain these changes. Migration could not be rejected in any population, but required rates much higher than those recorded. Directional selection was rejected in three populations in favour of balancing selection. Heterozygote advantage and negative frequency-dependent selection could not be distinguished statistically, although overall the results favoured the latter. Populations varied idiosyncratically as mild or variable colour selection (3–11%) interacted with demographic stochasticity, and the overall conclusion was that multiple mechanisms may contribute to maintaining the polymorphisms.
Data from: Combining human acceptance and habitat suitability in a unified socio-ecological suitability model: a case study of the wolf in Switzerland
Habitat suitability models (HSMs) are commonly used in conservation practise to assess the potential of an area to be occupied and colonised. A major limitation of these models, however, is the omission of spatially explicit understanding of human acceptance towards the focal species. As wildlife is more and more subject to human-dominated landscapes, ignoring the sociological component will result in misrepresentation of the observed processes and inappropriate management. We distributed 10 000 questionnaires across Switzerland and identified key socio-demographical factors correlated with human acceptance of the wolf. We then created a spatially explicit acceptance model based on geo-referenced socio-demographical, social and geographical information. Finally, we combined our acceptance model with a HSM to obtain a unified socio-ecological suitability model, which included human and ecological components. We showed that the key factors associated with human acceptance were perception of how harmful the wolf is, interest in wolf-related issues, need for livestock protection, and fear of the wolf. Perceived harmfulness was in turn correlated with direct and indirect experience with the wolf, and level of education. Our acceptance map predicted decreasing acceptance with increasing altitude of residency and proximity to locations of confirmed wolf presence. This resulted in the overall opposition to the wolf for the Alpine region, albeit substantial regional differences. We found little spatial overlap (6% of Switzerland) between areas where the wolf was accepted and areas of suitable habitat. These areas of socio-ecological suitability were concentrated in the Jura Mountains and in the eastern and southern Alps, and were absent in the western and central Alps. Particularly in the Jura region, which is yet to be colonised, management of human acceptance will be a crucial conservation target. Synthesis and applications. We developed an integrative, socio-ecological approach that allowed us to accurately reproduce recent wolf recolonisation. We anticipate our framework to be a powerful tool to reliably evaluate overall suitable habitats and predict short to medium-term range expansion for species whose distribution is also dependent on human attitudes. Because our approach is sensitive to both the ecological and human component, it is ideally suited to identify key regions where proactive and targeted socio-ecological management plans are needed.
Data from: Integrating phylogenomic and morphological data to assess candidate species-delimitation models in brown and red-bellied snakes (Storeria)
Systematics at the species level is still marked by theoretical and empirical tensions amongst the desires to identify geographical lineages, delimit species, and estimate their relationships. These goals are often confounded because each relies, at least to some extent, on the others being known. However, recently developed methods can simultaneously address all three. Furthermore, next-generation genomic sequencing allows us to generate large-scale molecular data sets to examine variation within species at a fine scale. Finally, a renaissance in morphological species validation allows us to integrate historical species definitions with coalescent models for species delimitation. Here, we investigate the applicability of these methods in an empirical case, in the Nearctic snake genus Storeria. Integrating trait data into species delimitation reduces the number of species delimited from molecular data alone. Whereas molecular data support eight distinct species-level lineages, including morphological data reduces this to four. The taxa Storeria dekayi, Storeria occipitomaculata, Storeria storerioides, and Storeria victa are considered distinct, monotypic species, with no subspecies recognized. We highlight the need for careful assessment of species delimitation, combining both computational genetic methods as well as traditional character-based descriptions. It is now possible to identify phylogeographical lineages, delimit species using molecular and morphological data, and estimate their relationships in a single coherent set of analyses. Moving forward, this will allow for more rapid and objective assessments of cryptic diversity at the species level.
Data from: Molecular Inversion Probes for targeted resequencing in non-model organisms
Applications that require resequencing of hundreds or thousands of predefined genomic regions in numerous samples are common in studies of non-model organisms. However few approaches at the scale intermediate between multiplex PCR and sequence capture methods are available. Here we explored the utility of Molecular Inversion Probes (MIPs) for the medium-scale targeted resequencing in a non-model system. Markers targeting 112 bp of exonic sequence were designed from transcriptome of Lissotriton newts. We assessed performance of 248 MIP markers in a sample of 85 individuals. Among the 234 (94.4%) successfully amplified markers 80% had median coverage within one order of magnitude, indicating relatively uniform performance; coverage uniformity across individuals was also high. In the analysis of polymorphism and segregation within family, 77% of 248 tested MIPs were confirmed as single copy Mendelian markers. Genotyping concordance assessed using replicate samples exceeded 99%. MIP markers for targeted resequencing have a number of advantages: high specificity, high multiplexing level, low sample requirement, straightforward laboratory protocol, no need for preparation of genomic libraries and no ascertainment bias. We conclude that MIP markers provide an effective solution for resequencing targets of tens or hundreds of kb in any organism and in a large number of samples.
Data from: Examining temporal sample scale and model choice with spatial capture-recapture models in the common leopard Panthera pardus
Many large carnivores occupy a wide geographic distribution, and face threats from habitat loss and fragmentation, poaching, prey depletion, and human wildlife-conflicts. Conservation requires robust techniques for estimating population densities and trends, but the elusive nature and low densities of many large carnivores make them difficult to detect. Spatial capture-recapture (SCR) models provide a means for handling imperfect detectability, while linking population estimates to individual movement patterns to provide more accurate estimates than standard approaches. Within this framework, we investigate the effect of different sample interval lengths on density estimates, using simulations and a common leopard (Panthera pardus) model system. We apply Bayesian SCR methods to 89 simulated datasets and camera-trapping data from 22 leopards captured 82 times during winter 2010–2011 in Royal Manas National Park, Bhutan. We show that sample interval length from daily, weekly, monthly or quarterly periods did not appreciably affect median abundance or density, but did influence precision. We observed the largest gains in precision when moving from quarterly to shorter intervals. We therefore recommend daily sampling intervals for monitoring rare or elusive species where practicable, but note that monthly or quarterly sample periods can have similar informative value. We further develop a novel application of Bayes factors to select models where multiple ecological factors are integrated into density estimation. Our simulations demonstrate that these methods can help identify the "true" explanatory mechanisms underlying the data. Using this method, we found strong evidence for sex-specific movement distributions in leopards, suggesting that sexual patterns of space-use influence density. This model estimated a density of 10.0 leopards/100 km2 (95% credibility interval: 6.25–15.93), comparable to contemporary estimates in Asia. These SCR methods provide a guide to monitor and observe the effect of management interventions on leopards and other species of conservation interest.
Data from: Conservation versus livelihoods: spatial management of non-timber forest product harvests in a two-dimensional model
Areas of high biodiversity often coincide with communities living in extreme poverty. As a livelihood support, these communities often harvest wild products from the environment. But harvest activities can have negative impacts on fragile and globally important ecosystems. This paper examines trade-offs in ecological protection and community welfare from the harvest of wild products. With a novel model and empirical evidence, I show that management of harvest activity does not always resolve these trade-offs. In a model of continuous harvests in a two-dimensional landscape, managed harvest activity improves welfare, but is uniformly bad for other ecosystem services that are sensitive to the presence (as opposed to the intensity) of human activity. Empirical results from a unique dataset of mushroom harvesters in Yunnan, China suggest more experienced, poorer, and more vulnerable individuals tend to rely on more distant harvests. Thus, policies that limit the extent of forest travel, such as protected areas, may protect fragile ecosystems but can have a disproportionately negative effect on those most vulnerable.
Data from: A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods
Genomic selection (GS) potentially offers an unparalleled advantage over traditional pedigree-based selection (TS) methods by reducing the time commitment required to carry out a single cycle of tree improvement. This quality is particularly appealing to tree breeders, where lengthy improvement cycles are the norm. We explored the prospect of implementing GS for interior spruce (Picea engelmannii × glauca) utilizing a genotyped population of 769 trees belonging to 25 open-pollinated families. A series of repeated tree height measurements through ages 3–40 years permitted the testing of GS methods temporally. The genotyping-by-sequencing (GBS) platform was used for single nucleotide polymorphism (SNP) discovery in conjunction with three unordered imputation methods applied to a data set with 60% missing information. Further, three diverse GS models were evaluated based on predictive accuracy (PA), and their marker effects. Moderate levels of PA (0.31–0.55) were observed and were of sufficient capacity to deliver improved selection response over TS. Additionally, PA varied substantially through time accordingly with spatial competition among trees. As expected, temporal PA was well correlated with age-age genetic correlation (r=0.99), and decreased substantially with increasing difference in age between the training and validation populations (0.04–0.47). Moreover, our imputation comparisons indicate that k-nearest neighbor and singular value decomposition yielded a greater number of SNPs and gave higher predictive accuracies than imputing with the mean. Furthermore, the ridge regression (rrBLUP) and BayesCπ (BCπ) models both yielded equal, and better PA than the generalized ridge regression heteroscedastic effect model for the traits evaluated.
Data from: Using citizen science monitoring data in species distribution models to inform isotopic assignment of migratory connectivity in wetland birds
Stable isotopes have been used to estimate migratory connectivity in many species. Estimates are often greatly improved when coupled with species distribution models (SDMs), which temper estimates in relation to occurrence. SDMs can be constructed using from point locality data from a variety of sources including extensive monitoring data typically collected by citizen scientists. However, one potential issue with SDM is that these data oven have sampling bias. To avoid this potential bias, an approach using SDMs based on marsh bird monitoring program data collected by citizen scientists and other participants following protocols specifically designed to maximize detections of species of interest at locations representative of the species range. We then used the SDMs to refine isotopic assignments of breeding areas of autumn-migrating and wintering Sora (Porzana carolina), Virginia Rails (Rallus limicola), and Yellow Rails (Coturnicops noveboracensis) based on feathers collected from individuals caught at various locations in the United States from Minnesota south to Louisiana and South Carolina. Sora were assigned to an area that included much of the western U.S. and prairie Canada, covering parts of the Pacific, Central, and Mississippi Flyways. Yellow Rails were assigned to a broad area along Hudson and James Bay in northern Manitoba and Ontario, as well as smaller parts of Quebec, Minnesota, Wisconsin, and Michigan, including parts of the Mississippi and Atlantic Flyways. Virginia Rails were from several discrete areas, including parts of Colorado, New Mexico, the central valley of California, and southern Saskatchewan and Manitoba in the Pacific and Central Flyways. Our study demonstrates extensive data from organized citizen science monitoring programs are especially useful for improving isotopic assignments of migratory connectivity in birds, which can ultimately lead to better informed management decisions and conservation actions.
Data from: High quality statistical shape modelling of the human nasal cavity and applications
The human nose is a complex organ that shows large morphological variations and has many important functions. However, the relation between shape and function is not yet fully understood. In this work, we present a high quality statistical shape model of the human nose based on clinical CT data of 46 patients. A technique based on cylindrical parametrization was used to create a correspondence between the nasal shapes of the population. Applying principal component analysis on these corresponded nasal cavities resulted in an average nasal geometry and geometrical variations, known as principal components, present in the population with a high precision. The analysis led to 46 principal components, which account for 95 percent of the total geometrical variation captured. These variations are first discussed qualitatively, and the effect on the average nasal shape of the first five principal components is visualized. Hereafter, by using this statistical shape model, two application examples that lead to quantitative data are shown: nasal shape in function of age and gender, and a morphometric analysis of different anatomical regions. Shape models, as the one presented here, can help to get a better understanding of nasal shape and variation, and their relationship with demographic data.
Data for "Advanced momentum sampling and Maslov phases for a precise semiclassical model of strong-field ionization"
<p>Data and plot scripts used to produce the figures in "Advanced momentum sampling and Maslov phases for a precise semiclassical model of strong-field ionization", available in preprint on arXiv <a href="https://doi.org/10.48550/arXiv.2311.01845">https://doi.org/10.48550/arXiv.2311.01845.</a></p><p>Abstract: Recollision processes are fundamental to strong-field physics and attoscience, thus models connecting recolliding trajectories to quantum amplitudes are a crucial part in furthering understanding of these processes. We report developments in the semiclassical path-integral-based Coulomb quantum-orbit strong-field approximation model for strong-field ionization by including an additional phase known as Maslov's phase and implementing a new solution strategy via Monte-Carlo-style sampling of the initial momenta. In doing so, we obtain exceptional agreement with solutions to the time-dependent Schrödinger equation for hydrogen, helium, and argon. We provide an in-depth analysis of the resulting photoelectron momentum distributions for these targets, facilitated by the quantum-orbits arising from the solutions to the saddle-point equations. The analysis yields a new class of rescattered trajectories that includes the well-known laser-driven long and short trajectories, along with novel Coulomb-driven rescattered trajectories. By virtue of the precision of the model, it opens the door to detailed investigations of a plethora of strong-field phenomena such as photoelectron holography, laser-induced electron diffraction and high-order above threshold ionization.</p><p>For more information on the files and their content, see the README file.</p>
Data from 'Sensorimotor model of obstacle avoidance in echolocating bats'
<p>The entry contains all data reported in the paper.</p> <p>Data are provided as MATLAB mat files. These can be read using MATLAB and other (free) software, including:</p> <ul> <li>R: https://www.r-project.org/</li> <li>SciPy: http://wiki.scipy.org/Cookbook/Reading_mat_files</li> </ul> <p>Each .mat file contains the data for a separate simulation:</p> <ul> <li>Experiment1.mat: randomly distributed reflectors in horizontal plane</li> <li>Experiment2.mat: randomly distributed reflectors in vertical plane</li> <li>Experiment3.mat: randomly distributed reflectors, 3D</li> <li>Experiment4.mat: torus setting</li> <li>Experiment7.mat: patch of fir forest</li> <li>Experiment8.mat: forest road</li> <li>Experiment9.mat: vertical wires</li> <li>Experiment10.mat: horizontal wires</li> <li>Experiment11.mat: randomly distributed reflectors in horizontal plane, for FM bat</li> <li>Experiment12.mat: randomly distributed reflectors in vertical plane, for FM bat</li> </ul> <p>The files contain the same entries. The relevant entries are the following:</p> <p><strong>condition labels</strong>: the various conditions (i.e. controller variants) are encoded using the values in the arrays RD, EF, OA and CS. For example, for experiment1.mat these have following values below.</p> <ul> <li>RD = [0 0 1 2 0];</li> <li>EF = [0 1 0 0 0];</li> <li>OA = [0 0 0 0 0];</li> <li>RF = [1 1 1 1 1];</li> <li>CS = [0 0 0 0 1];</li> </ul> <p>RD: a value of 1 in RD indicates controller random A, 2 indicates controller random B.</p> <p>EF: a value of 1 indicates the the fixed ear controller.</p> <p>OA: indicates the controller with the ears fixed of axis</p> <p>RF: indicates the phases of the reflections were randomized</p> <p>CS: indicates the controller with constrained elevation</p> <p>Hence, the 5 conditions/controllers simulated for the randomly distributed reflectors in horizontal plane are the Default controller (no random, no fixed ears, no constraints), Fixed Ear, Random A, Random B and Constrained controller, respectively.</p> <p>The controller types in the other .mat files can be decoded similarly.</p> <ul> </ul> <p>Batpositions is 4D matrix [simulation steps x dimension (x, y, z) x condition x replication]. This matrix contains the 3D <strong>positions </strong>for the simulated bat for all replications and controllers. Similarly, velocities, distances, reflectors contain the <strong>speed of the bat, the distance to the nearest reflector, the number of reflectors returning an echo > 0 dB, respectively</strong>.</p> <p>Worlds contains the <strong>3D positions of the reflectors</strong> for each of the replications.</p> <p>Other variables are support variables used while running the simulations.</p>
DATA of Effect of different iterative reconstruction algorithms on ultra-low dose CT of inflammatory bowel disease in a rabbit model
<p>This file contains the experimental data of the scientific paper titled: " <strong>Effect of different iterative reconstruction algorithms on ultra-low dose CT of inflammatory bowel disease in a rabbit model"</strong></p>
An example of ECMWF Deterministic Model analysis data for DYNAMO
<p>The full dataset is hosted by Earth Observing Laboratory at the National Center for Atmospheric Research. This is only one example used to compute momentum budget associated with the Madden-Julian Oscillation during DYNAMO. </p>
Figure_8_Model_Data
<p>The smbl file will give you the specifics of the model. The lm file was generated with lattice microbes, it is in hdf5 format. This is the data that was used in the manuscript.</p>
Figure_9_Model_Data
<p>Supercoiling domain 1 from figure 8 with gene #1 inhibited. The data is in the lm file which is an hdf5 file. Use the smbl file for the specifics of the different reactions.</p>
Fig_6_and_7_Model_Data
<p>Use the smbl to determine which reactions are which in the lm file, use the lm file to determine the actual rates used for that dataset. The lm file is a hdf5 file generated by lattice microbes. </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.