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1,049 results for “robustness”
Supporting material for: A multi-batch design to deliver robust estimates of efficacy and reduce animal use – a syngeneic tumour case study
<p>Underlying data, R scripts and subsequent figures are presented to deliver a replicable and transparent analysis for the manuscript "A multi-batch design to deliver robust estimates of efficacy and reduce animal use – a syngeneic tumour case study"</p> <p>Published in Scientific Reports</p> <p>See: <a href="https://protect-de.mimecast.com/s/kCQLCgpRGySlzOwmCNma6d?domain=rdcu.be">https://rdcu.be/b3vj2</a> </p> <p> </p> <p>This is version 2 of this data. This differs from version 1 in the following</p> <p>1. The number of simulation has increased from 300 to 2000 in each simulation cycle</p> <p>2. Script has been added to generate publication level figures</p> <p> </p> <p> </p> <p> </p>
Supplementary Figures for the manuscript 'Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph' by Albergante et al.
<p>Multidimensional datapoint clouds representing large datasets are frequently characterized by non‐trivial low‐dimensional geometry and topology which can be recovered by unsupervised machine learning approaches, in particular, by principal graphs. Principal graphs approximate the multivariate data by a graph injected into the data space with some constraints imposed on the node mapping. Here we present ElPiGraph, a scalable and robust method for constructing principal graphs. ElPiGraph exploits and further develops the concept of elastic energy, the topological graph grammar approach, and a gradient descent‐like optimization of the<br> graph topology. The method is able to withstand high levels of noise and is capable of approximating data point clouds via principal graph ensembles. This strategy can be used to estimate the statistical significance of complex data features and to summarize them into a single consensus principal graph. ElPiGraph deals efficiently with large datasets in various fields such as biology, where it can be used for example with single‐cell transcriptomic or epigenomic datasets to infer gene expression dynamics and recover differentiation landscapes.</p> <p> </p>
Data from: Facile fabrication of fluoro-polymer self-assembled ZnO nanoparticles mediated, durable and robust omniphobic surfaces on polyester fabrics
<p>Omniphobic surfaces have been widely used in many applications, especially due to their self-cleaning property. Omniphobicity of a surface is directly interpreted by measuring the contact angle that it makes with a liquid of interest. In this study, polyester fabric was made omniphobic with a measured water contact angle (WCA) of 152° by reducing the surface free energy of the fabric surface via the polymerization of 3,3,4,4,5,5,6,6,7,7,8,8,8-tridecafluorooctyl methacrylate(TDM) on a ZnO seed layer. The fabrics with and without the seed layer were characterized using various analytical techniques. The WCA of the fabric with the seed layer was 153° compared to 142° of the fabric without the seed layer. The treated fabric made a contact angle of 132° with SAE 40 motor oil indicating its oleophobicity while non-treated fabric made no contact angle. In addition to that, the treated fabric is omniphobic against milk tea, coffee, coconut oil, and ethanol. The morphological analysis using scanning electron microscopy (SEM) of the treated and non-treated fabrics revealed that the particle size of the seed layer applied fabric was ranging from 100-300 nm and upon the TDM application it became less than 100 nm. Elemental analysis by EDS showed the presence of fluorine and FT-IR analysis confirmed the polymerization of TDM. The polymerization of fluoropolymer was further confirmed by TGA and DSC analyses. The contact angle of the surface-modified fabric remained unchanged even after 1.5 h washing and 50 cycles of abrasion. The modified fabric is robust and no change was observed in the colour of the fabric during the process. More importantly the preparation method of the fabric is simple, low cost and quick.</p>
Data for 'Robust Enhancement of Tropical Convective Activity by the 2019 Antarctic Sudden Stratospheric Warming'
<p>These data were used for making plots in the manuscript entitled 'Robust Enhancement of Tropical Convective Activity by the 2019 Antarctic Sudden Stratospheric Warming'. DOI: 10.1029/2020GL088743. Data format is NetCDF.</p>
A multi-state occupancy modeling framework for robust estimation of disease prevalence in multi-tissue disease systems
<p>1. Given the public health, economic, and conservation implications of zoonotic diseases, their effective surveillance is of paramount importance. The traditional approach to estimating pathogen prevalence as the proportion of infected individuals in the population is biased because it fails to account for imperfect detection. A statistically robust way to reduce bias in prevalence estimates is to obtain repeated samples (or sample many tissues in multi-tissue disease systems) and to apply statistical methods that account for imperfect detection and permit the interdependence of the infection process across multiple tissues.</p> <p>2. We developed a multi-state occupancy modeling framework which considers two scenarios about the infection process, one where no assumptions about the dependencies among the tissues are made (general), and another where dependence among tissues is not permitted (constrained).</p> <p>3. We applied this model to pseudorabies virus (PrV) DNA detection data obtained from whole blood; and oral, nasal, and genital mucosa of 510 feral swine (Sus scrofa) during the years 2014-2016 in Florida, USA.</p> <p>4. The constrained model was better supported by data. Estimated PrV prevalence varied among tissues, ranging from to 0.06 (CI: 0.02-0.14) in genital to 0.54 (CI: 0.14-0.82) in nasal tissue. Probability of PrV detection ranged from 0.11 (CI: 0.06-0.18) in nasal to 0.51 (CI: 0.21-0.81) in genital tissue. Estimates of PrV prevalence after accounting for imperfect detection were higher than the naïve estimates for all four tissues.</p> <p>5. PrV prevalence was not affected by the age or sex of the animal or the year of sampling, but prevalence increased as drought severity increased.</p> <p>6. The conditional probability of detecting PrV given infection in at least one tissue type within an individual was highest for nasal tissue, suggesting that nasal is the best tissue to sample for PrV surveillance if only one tissue can be sampled, at least for systems with tissue-specific prevalence and detection probabilities similar to ours.</p> <p>7. We found that pathogen prevalence in multi-tissue disease systems can vary across tissues. Our results emphasize the importance of sampling multiple tissues, and the application of robust statistical models to account for imperfect detection in the surveillance of systemic diseases. The multi-state modeling framework is broadly applicable to the surveillance of pathogens that infect multiple tissues and where the infection status or detection of the pathogen in one tissue may depend on the infection status of the pathogen in other tissues). 29-Jul-2020</p>
Synthetic MISE Data for Radiation Robustness Analysis
<p>This dataset contains synthetic observations similar to those that will be produced by the Mapping Imaging Spectrometer for Europa (MISE) instrument. The dataset was created by taking visible Galileo Solid-State Imaging (SSI) experiment observations resized to 300x300 pixels, using pixel intensity as a proxy for albedo, and linearly mixing two 451-channel spectra in proportion to albedo for each pixel.</p> <p>The contents of this directory include the original SSI images and PDS label files, rescaled versions of the images, and the spectral cubes in HDF5 format corresponding to synthetic MISE digital number (DN) measurements. The cube files contain two datasets, "cube" containing the DN values, and "wavelengths," which holds the wavelength in nanometers corresponding to each value in a spectrum.</p> <p>The dataset was created to evaluate the radiation robustness of the Reed-Xiaoli (RX) algorithm used for spectral anomaly detection. For the radiation robustness analysis, only the first 421 channels of the spectra are used.</p> <p>The full dataset size is roughly 781 MB.</p>
Data file for the paper: Jun Wu, Peng Li, Andres Parra-Puerto, Shuang Wu, Xiaoqian Lin, Denis Kramer, Shengli Chen, Anthony Kucernak, "Controllable heteroatom doping effects of CrxCo2-xP Nanoparticles: A Robust Electrocatalyst for Overall Water Splitting in Alkaline Solutions"
<p>The data in this spreadsheet was used to produce the figures in the paper<br> <br> Authors:Jun Wu,Peng Li,Andres Parra-Puerto,Shuang Wu,Xiaoqian Lin,Denis Kramer,Shengli Chen,Anthony Kucernak</p> <p>Title:Controllable heteroatom doping effects of CrxCo2-xP Nanoparticles: A Robust Electrocatalyst for Overall Water Splitting in Alkaline Solutions</p> <p>Journal:Acs Applied Materials & Interfaces<br> <br> DOI: 10.1021/acsami.0c10441<br> <br> Please cite the above reference if you wish to use this data<br> <br> DOI of this data:10.5281/zenodo.4067857<br> <br> <br> <br> <br> <br> </p>
Robustness of consensus is independent from preference diversity among group members in the American cockroach (Periplaneta american)
Collective choices and consensus resulting from the competition of positive feedbacks, are the subject of numerous studies. However, how the interindividual diversity of preferences among the group members affects these dynamics is usually overlooked apart from vertebrates based studies. Gregarism is a useful model for studying how the interindividual diversity of preferences affects the collective choices and consensus. The decision-making of three types of groups of the cockroach <i>Periplaneta americana</i> is tested in a choice between an odorous shelter and an odourless one: naïves (individuals showing an inherent preference towards the odorous shelter); conditioned (individuals with the preference for the odorous shelter inhibited); and mixed (a combination of conditioned individuals and a minority of naïve ones). We show that while the consensus is robust for all groups (>90% of the total population is in the same shelter), the group composition determines the rate to achieve a consensus and the frequency of selection of the odorous shelter. Indeed, increasing the proportion of naïves in the group leads to an increasing number of consensuses towards the odorous shelter and to an increasing rate to reach them. We also show that the minority of naïve individuals in mixed groups act as leaders or influencers.
Robustness of a meta‐network to alternative habitat loss scenarios
<p>Studying how habitat loss affects the tolerance of ecological networks to species extinction (i.e. their robustness) is key for our understanding of the influence of human activities on natural ecosystems. With networks typically occurring as local interaction networks interconnected in space (a meta-network), we may ask how the loss of specific habitat fragments affects the overall robustness of the meta-network. To address this question, for an empirical meta-network of plants, herbivores and natural enemies we simulated the removal of habitat fragments in increasing and decreasing order of area, age and connectivity for plant extinction and the secondary extinction of herbivores, natural enemies and their interactions. Meta-network robustness was characterized as the area under the curve of remnant species or interactions at the end of a fragment removal sequence. To pinpoint the effects of fragment area, age and connectivity, respectively, we compared the observed robustness for each removal scenario against that of a random sequence. The meta-network was more robust to the loss of old (i.e. long-fragmented), large, connected fragments than of young (i.e. recently fragmented), small, isolated fragments. Thus, young, small, isolated fragments may be particularly important to the conservation of species and interactions, while contrary to our expectations larger, more connected fragments contribute little to meta-network robustness. Our findings highlight the importance of young, small, isolated fragments as sources of species and interactions unique to the regional level. These effects may largely result from an unpaid extinction debt, in which case these fragments are likely to lose species over time. Yet, there may also be more long-lasting effects from cultivated lands (e.g. water, fertilizers and restricted cattle grazing) and network complexity in small, isolated fragments. Such fragments may sustain important biological diversity in fragmented landscapes, but maintaining their conservation value may depend on adequate restoration strategies.</p>
Data from: Robust inference on large-scale species habitat use with interview data: the status of jaguars outside protected areas in Central America
Evaluating range-wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains, and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given <4 and ≥4 observers per unit). True probability of detection (mean=0.58) increased with the number of days interviewees spent in a survey unit per year. Failing to account for false positives biased predicted habitat use high (˜1.8x), especially where occurrence records were sparse. Probability of site use by jaguars increased with greater forest cover, prey richness, and distance from human settlements, and decreased with greater agricultural cover, elevation, and distance from protected areas. Site use probabilities averaged 0.15-0.97 by corridor, providing relatively fine-scale resolution of predicted jaguar occurrence consistent with known patterns of jaguar gene flow across Central America. Model validation, accounting for both false positives and negatives in the observation process, indicated moderate correspondence between model-predicted observations and actual observations for withheld data (0.65, 95% CRI 0.59–0.71), with sensitivity and specificity rates of 0.69 (0.61 – 0.77) and 0.59 (0.50 – 0.68), respectively. These results demonstrate that reliable predictions can be achieved despite the complexity of large-scale, interview-based analyses of species occurrence. Synthesis and applications. Our Bayesian hierarchical occupancy model accommodated heterogeneity caused by typical sampling inequities and idiosyncrasies associated with interview data, yielding robust estimates of jaguar habitat use. Our approach is applicable to any wide-ranging and readily identifiable species and has particular utility for rare species in human-dominated landscapes where traditional survey techniques (e.g., camera traps) may be impractical.
Near-optimal robust bilevel linear instances
<p>This repository contains the bilevel instances used in the paper Near-Optimal Robust Bilevel Optimization (https://arxiv.org/abs/1908.04040). They come in four groups, small, medium, large and mips instances, with different numbers of variables and constraints as described in the paper.</p> <p>The MIPS instances are constructed from the MIPS/RANDOM instances from https://coral.ise.lehigh.edu/data-sets/bilevel-instances/</p> <p>The /data folder contains instances in JLD format, the DataReader folder contains a Julia project for reading the data.</p>
Agricultural intensification drives changes in hybrid network robustness by modifying network structure
<p>Within ecological communities, species engage in myriad interaction types, yet empirical examples of hybrid species interaction networks composed of multiple types of interactions are still scarce. A key knowledge gap is understanding how the structure and stability of such hybrid networks are affected by anthropogenic disturbance. Using 15,169 interaction observations, we constructed 16 hybrid herbivore-plant-pollinator networks along an agricultural intensification gradient to explore changes in network structure and robustness to local extinctions. We found that agricultural intensification led to declines in modularity but increases in nestedness and connectance. Notably, network connectance, a structural feature typically thought to increase robustness, caused declines in hybrid network robustness, but the directionality of changes in robustness along the gradient depended on the order of local species extinctions. Our results not only demonstrate the impacts of anthropogenic disturbance on hybrid network structure, but they also provide unexpected insights into the structure-stability relationship of hybrid networks.</p>
SIDIRE: Synthetic Image Dataset for Illumination Robustness Evaluation
<p>SIDIRE is a freely available image dataset which provides synthetically generated images allowing to investigate the influence of illumination changes on object appearance. The images are renderings of 3D coin models with different material BRDFs and levels of texturedness. Thus, the dataset makes it possible to directly evaluate the influence of these conditions on the performance of image recognition without introducing a bias due to different objects used between image sets. The dataset has been used for evaluation in [1].</p> <p><strong>Usage</strong></p> <p>The dataset is freely available for non-commercial research use. Please cite our paper [1] when using the dataset for your research.</p> <p><strong>Technical Details</strong></p> <p>Full Image Dataset</p> <p>The full image dataset consists of images of 14 coin models which have been rendered using the open-source graphics software <a href="http://www.blender.org">Blender</a>. For each model, twelve sets of 500×500 images with 65 illumination directions were rendered where each set represents one out of four material BRDFs and one out of three texture density levels. Material BRDFs are intended to represent different levels of specularity starting from a Lambertian material with zero specularity up to specular intensity values of 0.25, 0.50 and 1.00. The first texture density level shows no texture and thus represents the set of textureless objects. For the remaining two levels synthetically generated textures were used. The camera image plane is placed parallel to the coin and light source positions are defined by their azimuth angle φ and elevation angle λ. We used eight levels of λ with eight levels of φ each to produce 64 images. The 65th image is rendered with the light placed at the camera position (i.e. λ=90°).<br> In the provided RAR-file, all the 65 images of a specific model, specularity level and texturedness level are contained in separate directories. For instance, the directory ‘texture_level0\Ref_level2\2874-back’ contains the images of the model ‘2874-back’ rendered without texture and a specularity of 0.50.</p> <p><strong>Patch Dataset</strong></p> <p>The patch dataset contains 50000 matching patch pairs for every of the 12 subsets of SIDIRE. It can be used to generate groups of feature distances by means of true and false patch pairs, in the same manner as, e.g., Matthew Brown’s <a href="http://phototour.cs.washington.edu/patches/default.htm">patch dataset</a>. Please see [1,2] for a detailed description of the evaluation scheme of patch pair databases.<br> The patches have a size of 64×64 and are arranged in images of size 3200×3200. Thus, every image contains 2500 patches where corresponding patches are placed side by side. The patches of the 12 subsets are contained in directories indicating their texture density and reflectance level, e.g. patches rendered without texture and a specularity of 0.50 are contained in the directory ‘tex0_ref2’.<br> </p> <p><strong>References</strong></p> <p>[1] Zambanini S., Kampel M. “Evaluation of Low-Level Image Representations for Illumination-Insensitive Recognition of Textureless Objects”, <em>International Conference on Image Analysis and Processing – ICIAP’13</em>, Naples, Italy, September 2013. (<a href="https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/iciap13.pdf">pdf</a>, <a href="https://cvl.tuwien.ac.at/wp-content/uploads/2014/12/iciap13_supp1.pdf">supplementary material</a>)<br> [2] Brown, M., Gang Hua, Winder, S., “Discriminative Learning of Local Image Descriptors”, <em>Pattern Analysis and Machine Intelligence, </em> vol.33, no.1, pp.43-57, 2011.</p>
Data from: Error-robust modes of the retinal population code
Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina's output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells' collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina.
Data from: The impact of gene expression variation on robustness and evolvability of a developmental gene regulatory network
Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear), allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.
Data from: Concordance in wetland physicochemical conditions, vegetation, and surrounding land cover is robust to data extraction approach
Concordance among wetland physicochemical conditions, vegetation, and surrounding land cover may result from the influence of land cover on the sources of plant propagules, on physicochemical conditions, and their subsequent determination of growing conditions. Alternatively, concordance may result if differences in climate, soils, and species pools are spatially confounded with differences in human population density and land conversion. Further, we expect that land cover within catchment boundaries will be more predictive than land cover in symmetrical buffers if runoff is a major pathway. We measured concordance between land cover, wetland vegetation and physicochemical conditions in 48 prairie pothole wetlands, controlling for inter-wetland distance. We contrasted land-cover data collected over a four-year period by multiple extraction approaches including topographically-delineated catchments and nested 30 m to 5,000 m radius buffers. After factoring out inter-wetland distance, physiochemical conditions were significantly concordant with land cover. Vegetation was not significantly concordant with land cover, though it was strongly and significantly concordant with physicochemical conditions. More, concordance was as strong when land cover was extracted from buffers <500 m in radius as from catchments, indicating the mechanism responsible is not topographically constrained. We conclude that local landscape structure does not directly influence wetland vegetation composition, but rather that vegetation depends on physicochemical conditions in the wetland (which are affected by surrounding land cover) and on regional factors such as the vegetation species pool and geographic gradients in climate, soil type, and land use.
Data from: Robust estimates of a high Ne/N ratio in a top marine predator, southern bluefin tuna
Genetic studies of several marine species with high fecundity have produced "tiny" estimates (≤10−3) of the ratio of effective population size (Ne) to adult census size (N), suggesting that even very large populations might be at genetic risk. A recent study using close-kin mark-recapture methods estimated adult abundance at N ≈ 2 × 106 for southern bluefin tuna (SBT), a highly fecund top predator that supports a lucrative (~$1 billion/year) fishery. We used the same genetic and life history data (almost 13,000 fish collected over 5 years) to generate genetic and demographic estimates of Ne per generation and Nb (effective number of breeders) per year and the Ne/N ratio. Demographic estimates, which accounted for age-specific vital rates, skip breeding, variation in fecundity at age, and persistent individual differences in reproductive success, suggest that Ne/N is >0.1 and perhaps about 0.5. The genetic estimates supported this conclusion. Simulations using true Ne = 5 × 105 (Ne/N = 0.25) produced results statistically consistent with the empirical genetic estimates, whereas simulations using Ne = 2 × 104 (Ne/N = 0.01) did not. Our results show that robust estimates of Ne and Ne/N can be obtained for large populations, provided sufficiently large numbers of individuals and genetic markers are used and temporal replication (here, 5 years of adult and juvenile samples) is sufficient to provide a distribution of estimates. The high estimated Ne/N ratio in SBT is encouraging and suggests that the species will not be compromised by a lack of genetic diversity in responding to environmental change and harvest.
Data from: Out-of-sample predictions from plant–insect food webs: robustness to missing and erroneous trophic interaction records
With increasing biotic introductions, there is a great need for predictive tools to anticipate which new trophic interactions will develop and which will not. Phylogenetic constraint of interactions in both native and novel food webs can make some novel interactions predictable. However, many food webs are sparsely sampled, or may include inaccurate interactions. In such cases, it is unclear whether modeling methods are still useful to anticipate novel interactions. We ran bootstrap simulations of host-use models on a Lepidoptera–plant data set to remove native trophic records or add erroneous records in order to observe the effect of missing or erroneous data on the prediction of interactions with novel plants. We found that the model was robust to a large amount of missing interaction records, but lost predictive power with the addition of relatively few erroneous interaction records. The loss of predictive power with missing records was due to inaccuracy in estimating phylogenetic distance between native and novel hosts. Removal of interaction records proportionally to their encounter frequency in the field had little effect on the loss of predictive power. Host-use models may have immediate value for predicting novel interactions from large, but sparsely sampled databases of trophic interactions.
Data from: Selective logging in tropical forests decreases the robustness of liana-tree interaction networks to the loss of host tree species
Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the 'health' and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growth tree species, which could exacerbate the loss of timber value and carbon storage already associated to logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana-tree interaction networks if heavily infested trees (i.e. the most connected ones) are more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of "extinction debt".
Data from: Learning and robustness to catch-and-release fishing in a shark social network
Individuals can play different roles in maintaining connectivity and social cohesion in animal populations and thereby influence population robustness to perturbations. We performed a social network analysis in a reef shark population to assess the vulnerability of the global network to node removal under different scenarios. We found that the network was generally robust to the removal of nodes with high centrality. The network appeared also highly robust to experimental fishing. Individual shark catchability decreased as a function of experience, as revealed by comparing capture frequency and site presence. Altogether, these features suggest that individuals learnt to avoid capture, which ultimately increased network robustness to experimental catch-and-release. Our results also suggest that some caution must be taken when using capture–recapture models often used to assess population size as assumptions (such as equal probabilities of capture and recapture) may be violated by individual learning to escape recapture.
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.