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608 results for “Heat stress”
Data and software: Stress and heat flux via automatic differentiation
<h4><strong>glp-archive</strong></h4><h2><strong>Code and Data for "Stress and heat flux with automatic differentiation"</strong></h2><p>This repository contains data, code, and related artefacts supporting the following publication (<a href="https://arxiv.org/abs/2305.01401">preprint</a>):</p><p>Stress and heat flux via automatic differentiation</p><p>by Marcel F. Langer, J. Thorben Frank, and Florian Knoop</p><p><i>J. Chem. Phys.</i> 159, 174105 (2023) <a href="https://doi.org/10.1063/5.0155760">doi:10.1063/5.0155760</a></p><p>This repository is available at <a href="https://github.com/sirmarcel/glp-archive">https://github.com/sirmarcel/glp-archive</a>. Selected versions are archived on Zenodo, under <a href="https://doi.org/10.5281/zenodo.7852529">doi:10.5281/zenodo.7852529</a>.</p><h2><strong>Overview</strong></h2><p>Each subfolder in this repository contains a README.md with additional information. The subfolders are:</p><ul><li>results/: Data and code that produced the figures in the manuscript</li><li>work/: Computational workflows, models, etc.</li><li>infra/: Project-specific infrastructure code</li><li>meta/: Scripts for assembling this archive; can be ignored but is retained for transparency.</li></ul><h2><strong>Related external code</strong></h2><p>The work in this repository relies on a few tools that the authors maintain separately:</p><ul><li><a href="https://github.com/sirmarcel/glp">glp</a> implements the quantities discussed in the manuscript</li><li><a href="http://github.com/thorben-frank/mlff">mlff</a> implements the so3krates model</li><li><a href="https://github.com/flokno/tools.mlff">tools.mlff</a> provides tools for the equation of state experiments</li></ul><p>These tools were developed during the work in the manuscript. The following versions/tags reflect what was used to obtain results:</p><ul><li>glp @ v0.1.0 (tag)</li><li>mlff @ v1.0 (branch)</li><li>mlff.tools @ v0.0.1</li></ul><p>We additionally note that the GK-MD functionality has been factored out into <a href="https://github.com/sirmarcel/gkx">gkx</a>.</p><h2><strong>Versions</strong></h2><ul><li>v1.1: published version, archived at <a href="https://doi.org/10.5281/zenodo.8406532">doi:10.5281/zenodo.8406532</a></li><li>v1.0: arXiv submission v1, archived at <a href="https://doi.org/10.5281/zenodo.7852530">doi:10.5281/zenodo.7852530</a></li></ul>
MCR LTER: Coral Reef: Coral bleaching with nitrogen and heat stress: 2016 data in support of Donovan et al. submitted to PNAS
During 2016, maximum water temperature in the lagoons of Moorea exceeded a threshold for heat stress for 70 straight days from early February through mid-April. In early May 2016, at the peak of accumulated heat stress, coral bleaching surveys were conducted to test the hypothesis that bleaching prevalence and severity were correlated with differences in heat stress and nutrient availability. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2019). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Data for: Heat induces multiomic and phenotypic stress propagation in zebrafish embryos
<p>This contains the data for the manuscript Feugere et al., "Heat induces multiomic and phenotypic stress propagation in zebrafish embryos" (2023). Zebrafish embryos were exposed to thermal stress ("TS") and stress metabolites ("SM") released by heat-stressed conspecifics in a two-way factorial design ("TSxSM"). The folder includes raw molecular data (cortisol levels, HSP70 protein levels, and gene expression acquired with LAMP and RNA-seq) and raw phenotypic data (morphology, hatching, survival, and behaviour) of zebrafish <em>Danio rerio </em>at 1 day and 4 days of development.</p> <p>The .csv files contain all quantitative data, whilst the .tab files contain the gene count data required for gene expression analysis. The data were analysed in R using the code shared in the "TSxSM2.stats.Rmd" file. The "Metadata" document provides the reader with an extensive description of each file.</p>
Light micrographs on the morphological response to heat stress in the filamentous Zygnematophyceae Mougeotia sp. and Spirogyra pratensis
<p>Herein are the light micrographs of <em>Mougeotia</em> sp. and <em>Spirogyra pratensis</em> that were used to obtain the quantitative information for Figure 1 in the article "Heat stress response in the closest algal relatives of land plants reveals conserved stress signaling circuits" published in The Plant Journal, doi: 10.1111/tpj.14782</p>
Data for "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis"
<p>Raw data associated with the publication "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis". Temperature profile, daily measurements, physiological measurements, elemental analysis, NanoSIMS data, and cell density data are included as individual tabs in the Excel file. </p>
Data from: The interactive effects of heat stress, parasitism, and hostplant quality in a host-parasitoid system
<p>Species interactions are expected to change in myriad ways as the frequency and magnitude of extreme temperature events increase with anthropogenic climate change. The relationships between endosymbionts, parasites, and their hosts are particularly sensitive to thermal stress, which can have cascading effects to other trophic levels. We investigate the interactive effects of heat stress and parasitism on a terrestrial tritrophic system consisting of two hostplants (one common, high-quality plant and one novel, low-quality plant), a caterpillar herbivore, and a specialist parasitoid wasp. We used a fully-factorial experiment to determine the bottom-up effects of the novel hostplant on both the caterpillars' life history traits and the wasps' survival, and the top-down effects of parasitism and heat shock on caterpillar developmental outcomes and herbivory levels. Hostplant identity interacted with thermal stress to affect wasp success, with wasps performing better on the low-quality hostplant under constant temperatures but worse under heat shock conditions. Surprisingly, caterpillars consumed less leaf material of the low-quality hostplant to reach the same final mass across developmental outcomes. In parasitized caterpillars, heat shock reduced parasitoid survival and increased both caterpillar final mass and development time on both hostplants. These findings highlight the importance of studying community-level responses to climate change from a holistic and integrative perspective and provide insight into potential substantial interactions between thermal stress and diet quality in plant-insect systems.</p>
Impact of heat stress on the fitness outcomes of symbiotic infection in aphids: a meta-analysis
<p>This is the dataset for the article "<em><strong>Impact of heat stress on the fitness outcomes of symbiotic infection in aphids: a meta-analysis</strong></em>". </p> <p>Beneficial symbiosis shape their host eco-evolutionary responses. Here we show how the responses of insect-microbe associations may be modulated by rising temperatures. The outcome of the symbiotic association is therefore temperature-dependent, but also trait-dependent. We show the importance of better understanding the cost-benefits balance of insect-microbe associations faced with climate change.</p>
Genome-wide analysis identified candidate variants and genes associated with heat stress adaptation in Egyptian sheep breeds
<p>The current study was conducted from 2009 to 2019 in three hot and dry agroecological zones in Egypt: Western Desert coastal zone, New Valley desert oasis, and hot-dry Upper Egypt. Within these zones, three local sheep breeds were studied: Barki (83 ewes), Wahati (55 ewes) and Saidi (68 ewes). During the study period, the animals exercised under natural heat stress (simulating summer grazing on poor pasture). Meteorological and physiological parameters were measured and recorded. The heat tolerance index of the animals was calculated to identify animals with high and low heat tolerance based on the animals' response to the five main physiological parameters (scale from 0 to 5). DNA samples were extracted for genomic analysis. The genetic diversity measurements showed a significant influence of breed and location on the populations. The influence of breed is more significant than that of location. The inbreeding analysis shows that the desert breeds (Wahati and Barki) have lower values than the urban breed (Saidi). The high rate of sub-clustering indicates the process of sub-population through inbreeding pressure. Wahati and Barki are very distinct breeds with strong identification, while Saidi breed has crosses with other breeds. The most significant SNPs associated with heat tolerance were found in MYO5A, PRKG1, GSTCD, and RTN1 genes (P < 0.0001). MYO5A had an effect of 0.74 on the trait heat tolerance in the studied population. It produces a protein that is widely distributed in the melanin-producing neural crest of the skin. Genetic association between genetic and phenotypic variations showed that OAR1 18300122.1, located in ST3GAL3, had the greatest positive effect on heat tolerance. GWAS analysis identified SNPs associated with heat tolerance in the PLCB1, STEAP3, KSR2, UNC13C , PEBP4, and GPAT2 genes.</p>
Heat stress at Uva Island during the 1982-83, 1997-98 and 2015-16 ENSOs
<p><strong>Heat stress at Uva Island during the 1982-83, 1997-98 and 2015-16 ENSOs</strong></p> <p><strong>Description</strong>: This repository obtains and analyzes SST data for Uva Island reef to compare the intensity of heat stress during the past three major ENSOs.</p> <p><strong>Content</strong>:</p> <p>A.Temperature_DHW.Rmd: This script uses the temperature data in the <strong>B.Temperature_data</strong> folder to calculate the accumulated heat stress (DHW) at Uva Island reef, based on three different temperature data sources (OISST, CRW and In situ sensors). Figures resulting from running the script are saved in the <strong>C.Outputs</strong> folder.</p> <p>B.Temperature_data: Directory containing data files in .csv format with the temperature data for Uva Island reef from different sources</p> <ul> <li> <p><strong>B.Temperature_data/Uva_CRW_MMM_1985-2012.csv:</strong> Coral Reef Watch MMM (5km products v3.1) for the closest pixel to Uva Island reef</p> </li> <li> <p><strong>B.Temperature_data/Uva_Daily_CRW_5km_1985-2016.csv:</strong> Coral Reef Watch SST data (5km products v3.1) for the closest pixel to Uva Island reef</p> </li> <li> <p><strong>B.Temperature_data/Uva_Daily_InSitu_1997-2018.csv:</strong> In situ temperature data obtained from 1997-2018 at Uva Island reef ("Gardineroseris city') ~ 3m depth</p> </li> <li> <p><strong>B.Temperature_data/Uva_Daily_OISST_1982-2016.csv:</strong> Optimal Interpolation SST data (V2) for the closest pixel to Uva Island reef</p> </li> <li> <p><strong>B.Temperature_data/BanderasBay_Daily_OISST_1982-2016.csv:</strong> Optimal Interpolation SST data (V2) for the closest pixel to Uva Island reef</p> </li> </ul> <p>C.Outputs: Directory containing figure files related with temperature and DHW included on the paper.</p> <ul> <li>Figure 1a and 3a</li> <li>Figure S6</li> <li>Figure S7</li> <li>Figure S8</li> <li>Figure S9</li> <li>Figure S5b</li> </ul> <p>D.SST_nc: Directory containing scripts used to download and extract OISST and CRW SST data from .nc files. You do not have to run the code in the <strong>D.SST_nc</strong> folder to produce the data analysis in the paper (this can be achieved by running <strong>A.Temperature_DHW.Rmd</strong> using the temperature data already provided in <strong>B.Temperature_data</strong>). However, you could use these scripts to retrieve and extract the SST data by yourself.The outputs of these scripts are already included in <strong>B.Temperature_data/Uva_CRW_MMM_1985-2012.csv:</strong>, <strong>B.Temperature_data/Uva_Daily_CRW_5km_1985-2016.csv</strong>" and <strong>B.Temperature_data/Uva_Daily_OISST_1982-2016.csv</strong>. By running the scripts inside this folder you will create those files again in the "<strong>D.SST_nc</strong>" folder.</p> <p>You would need ~ 123GB of space for CRW SST data and ~17GB for OISST data</p> <ul> <li> <p><strong>D.SST_nc/1.Get_OISST_data.sh:</strong> This script downloads 1981-2016 NOAA OI SST V2 High Resolution data from ftp://ftp.cdc.noaa.gov/Datasets/noaa.oisst.v2.highres/</p> </li> <li> <p><strong>D.SST_nc/2.Get_CoralTemp_data.sh:</strong> This script downloads NOAA CRW 5km SST data (CoralTemp v3.1) (fftp://ftp.star.nesdis.noaa.gov/pub/sod/mecb/crw/data/coraltemp/v1.0/nc/) and the 1985-2012 climatology (ftp://ftp.star.nesdis.noaa.gov/pub/sod/mecb/crw/data/5km/v3.1/climatology/nc/ct5km_climatology_v3.1.nc). It could also download the already calculated DHW values (ftp://ftp.star.nesdis.noaa.gov/pub/sod/mecb/crw/data/5km/v3.1/nc/v1.0/daily/dhw/) directly from NOAA CRW 5km products. However, these lines are commented by default since we performed these calculations ourselves based on the CRW SST data (CoralTemp) and MMM.</p> </li> <li> <p><strong>D.SST_nc/3.Extract_SST_Uva.Rmd:</strong> This script extracts the SST data from OISST and CRW datasets for Uva Island. It also extracts the already calculated climatology (MMM) from CRW 5km products. CRW DHW values from NOAA CRW 5km products can be extracted as well. However, these lines are commented by default since we performed these calculations ourselves based on the CRW SST data (CoralTemp) and MMM.</p> </li> </ul>
Evolutionary potential under heat and drought stress at the southern range edge of North American Arabidopsis lyrata
<p>The warm edges of species' distributions are vulnerable to global warming. Evidence is the recent range retraction from there found in many species. It is unclear why populations cannot easily adapt to warmer, drier, or combined hot and dry conditions and locally persist. Here, we assessed the ability to adapt to these stressors in the temperate species <em>Arabidopsis lyrata</em>. We grew plants from replicate seed families of a central population with high genetic diversity under a temperature and precipitation regime typical of the low-latitude margin or under hotter and/or drier conditions within naturally occurring amplitudes. We then calculated genetic variance-covariance (G-) matrices of traits depicting growth and allocation as well as selection vectors to compare the predicted adaptation potential under the different climate-stress regimes. We found that the sum of genetic variances and genetic correlations were not significantly different under stress as compared to benign conditions. However, under drought and heat drought, the predicted ability to adapt was severely constrained due to strong selection and selection pointing in a direction with less multivariate genetic variation. The much-reduced ability to adapt to dry and hot-dry conditions is likely to reduce the persistence of populations at the low-latitude margin of the species' distribution and contribute to the local extinction of the species under further warming.</p>
IuliaMargineanGitHub/Projecting-Heat-Stress-Vulnerable-Populations-at-Intra-Urban-Scales: Projecting heat stress vulnerable populations at intra-urban scales
<p>This repository provides the data and scripts necessary for full reproduction of results, as well as example datasets that were used for data generation and analysis in the manuscript Marginean et al., "High-resolution Modelling and Projecting Local Dynamics of Differential Vulnerability to Urban Heat Stress".</p> <p>The folders in this repository contain the following:</p> <ol> <li>The input datasets: <ul> <li>shares of educational attainment in 2012 and 2020, by sex, age group and census tract</li> <li>internal migration by sex, age group and census tracts</li> <li>decadal mortality and fertility, by sex, age group, scenario, and census tract</li> </ul> </li> <li>Projected decadal data (2012 to 2050) by sex, age group, scenario and census tract</li> <li>Scripts for generating high resolution projections for three Shared Socioeconomic Pathways (SSPs): one script for SSP 2 projections and one scripts for SSP 1 and SSP 3 projections</li> <li>Example input data to reconstruct the projections in SSP 1, 2 and 3 for females ages 25 to 64</li> </ol>
Fig. 1 in The Influence Of Thermal Preadaptation On Some Oxidative Processes In The First Leaves Of Wheat Seedlings (Triticum Aestivum L.) Under Heat Stress
Fig. 1. The rate of superoxide (O2˙ˉ) production (µmol/h) in the etiolated first leaves at the early (from 4th to 5th days) and late (from 7th to 8th days) stages of seedlings development.
Fig. 2 in The Influence Of Thermal Preadaptation On Some Oxidative Processes In The First Leaves Of Wheat Seedlings (Triticum Aestivum L.) Under Heat Stress
Fig. 2. Catalase activity in the etiolated first leaves at the early (from 4th to 5th days) and late (from 7th to 8th days) stages of seedling development.
Fig. 4 in The Influence Of Thermal Preadaptation On Some Oxidative Processes In The First Leaves Of Wheat Seedlings (Triticum Aestivum L.) Under Heat Stress
Fig. 4. Catalase activity in the etiolated first leaves at the (A) early (from 4th to 5th days) and (B) late (from 7th to 8th days) stages of seedling development (C ‒ control 26oC; E ‒ 26oC → 32oC; E1 ‒ 32o→42oC; E2 ‒ 26oC → 42oC).
Fig. 3 in The Influence Of Thermal Preadaptation On Some Oxidative Processes In The First Leaves Of Wheat Seedlings (Triticum Aestivum L.) Under Heat Stress
Fig. 3. The rate of superoxide (O2˙ˉ) production (µmol/h) in the etiolated first leaves at the (A) early (from 4th to 5th days) and (B) late (from 7th to 8th days) stages of seedlings development (C ‒ control 26oC; E ‒ 26oC → 32oC; E1 ‒ 32o→42oC; E2 ‒ 26oC → 42oC).
Fig. 1 in Oxidative stress parameters in juvenile Brazilian flounder Paralichthys orbignyanus (Valenciennes, 1839) (Pleuronectiformes: Paralichthyidae) exposed to cold and heat shocks
Fig. 1. (TBARS), (GST) and (CAT) activity in the liver of Paralichthys orbignyanus juveniles exposed to different temperatures (17.1, 23.0 and 28.8ºC) as a function of time exposition (72 h). Values are expressed as means ± SEM, N=5. aLower case letters indicate significantly different at the different temperatures and same time (P <0.05), determined by two-way ANOVA and by Dunnet test. ACapital letters indicate significantly different at the same temperatures and different times (P <0.05), determined by two-way ANOVA and by Dunnet test.
Interactive map of Heat Stress Compensability Classification (HSCC) application in 96 United States cities.
<p>This repository includes the interactive map in format .html of the very first application of the <strong>Heat Stress Compensability Classification (HSCC) in 96 cities in the United States </strong>showing the proportion of days with compensable and uncompensable heat stress from the top 10th percentile of hottest days from 2005-2020 in each place.</p> <p>This map offers the detailed results of the very first application of the classification system as in the journal article: <strong>The Development of an Adaptive Heat Stress Compensability Classification Applied to the United States</strong>, published in the 4th SNP special issue in the International Journal of Biometeorology. The results of this visualization were obtained from open-source data and coding packages such as Folium, and the model results were obtained by applying the Python Human Heat Balance (PyHHB) on weather dataset freely available.</p> <p>The interactive map offers a detailed visualization of the results from each of the cities, allowing you to see 3 tabs when the icon of the pie chart from each location is clicked.</p> <p><strong>Tab statistics:</strong> Detail per city of Figure 4b of related paper.</p> <p><strong>Tab Histogram 2D: </strong>Details per city of Fig 6 of related paper</p> <p><strong>Tab How to read: </strong>Figure 2 in related paper.</p> <p>Please for questions related to this dataset/code contact Gisel Guzman-Echavarria (gguzma20@asu.edu).</p> <p>Guzman-Echavarria, G., & Vanos, J. (2023). PyHHB: Physiological-based estimations of human survivability and liveability to heat in a changing climate (Nature Communications (1.0.0)). Zenodo. https://doi.org/10.5281/zenodo.10020137</p> <p> </p> <p> </p>
As built and post heat treatment residual stresses in 316L stainless steel additively manufactured benchmark arches
<p>The data presented is the residual stress in three orthogonal directions determined by neutron diffraction (SALSA at ILL) and synchrotron X-ray diffraction (P07 and P61A at Desy operated by Hereon). The data is for residual stress in a benchmark 316L stainless steel arches manufactured by laser powder bed fusion using MetalFAB1 and EOS M290 additive manufacturing machines. These arches are square topped with dimensions of nominally 20 mm in both the x and y direction (in plane). The overhang which creates the arch shape runs parallel to the y direction. The height of the arch is nominally 10 mm with the ligament above the over hang being of 2 mm nominal thickness. </p> <p>Data for part in both an as built and after a 700 °C 2 hour heat treatment are presented. The measurement line runs from the centre of the top surface (defined at the origin) down into the arch (defined as positive z direction).</p> <p>The stress-free reference used was a reference comb cut from an identically made arches. For heat treated samples, heat treated combs were used.</p> <p>Different gauge volume sizes and shapes were defined at each institution, all measurement locations indicate the centre of the gauge volume during each measurement. gauge volumes were: P07 200 x 200 µm2, ~1.9 mm, P61A 150 × 150 µm2 ~2.9 mm, ID15A 200 x 50 µm2 ~1.7 mm, SALSA 0.6 x 0.6 x2 mm3.</p>
Life stage-specific effects of heat stress on spermatogenesis and oogenesis in Drosophila melanogaster
<p><br>#Life stage-specific effects of heat stress on spermatogenesis and oogenesis in Drosophila melanogaster</p> <p>##Authors</p> <p>Abhishek Meena, Alessio N. De Nardo, Komal Maggu, Sonja Sbilordo, Benjamin Eggs, Rawaa Al Toma Sho, Stefan Lüpold</p> <p><br>## Citation of associated article<br>Meena, A., Maggu, K., De Nardo, A.N., Sbilordo, S.H., Eggs, B., Al Toma Sho, R., Lüpold, S., 2024. Life stage-specific effects of heat stress on spermatogenesis and oogenesis in Drosophila melanogaster. Journal of Thermal Biology 125, 104001. https://doi.org/10.1016/j.jtherbio.2024.104001</p> <p> </p> <p>##Overview<br>This dataset was collected to assess the impact of heat stress across various life stages on reproductive performance in Drosophila melanogaster. <br>The study focuses on stage- and sex-specific reproductive metrics such as: mating success, fertility, fecundity, hatching success, which for females were summed over four days and for males were assayed for four consecutive 24-hour periods, each with a different female. </p> <p>The dataset is structured to analyze these outcomes at different temperatures and developmental stages, providing insights into sex- and stage-specific vulnerabilities to heat stress. </p> <p>The analyses are performed in an R Markdown (.Rmd) file, using data stored in a CSV file</p> <p>##Contents</p> <p>The dataset includes the following files:</p> <p>Rscript.Rmd: An R Markdown file containing code for analyzing sex- and stage-specific reproductive fitness based on the data in Data.csv.<br>Data.csv: A CSV file with the raw data used for the analysis.</p> <p>##Data Description</p> <p>Note: NA's in each data file represent missing data (data not available). </p> <p>The Data.csv file contains the following columns:</p> <p>Unique.ID: Unique identifier for each experimental individual.</p> <p>SampleID: Identifier for each treatment group.</p> <p>Temperature: Thermal exposure temperature (measured in degrees Celsius) for 4 hours, with levels: 24.5°C, 28°C, 32°C, 36°C, and 38°C.</p> <p>Lifestage: Developmental stage during which thermal treatment was applied.</p> <p>Sex: Sex of the individual exposed to the thermal treatment.</p> <p>Day: Days post adult treatment exposure.</p> <p>Block: Experimental block identifier for randomized grouping.</p> <p>Total: Total number of eggs laid within 24 hours of oviposition.</p> <p>Hatched: Number of eggs that successfully hatched.</p> <p>Unhatched: Number of eggs that did not hatch (derived from the difference between Total and Hatched).</p> <p><br>##Usage</p> <p>To analyze the dataset, open and run the respective R Markdown (Rmd) files in RStudio or any compatible R Markdown environment. The Rmd files contain all the necessary code to reproduce the analyses described in the overview.</p> <p> </p>
Elucidating gene expression adaptation of phylogenetically divergent coral holobionts under heat stress
<p>As coral reefs struggle to survive under climate change, it is crucial to know whether they have the capacity to withstand changing conditions, particularly increasing seawater temperatures. Thermal tolerance requires the integrative response of the different components of the coral holobiont (coral host, algal photosymbiont, and associated microbiome). Here, using a controlled thermal stress experiment across three divergent Caribbean coral species, we attempt to dissect holobiont member metatranscriptome responses from coral taxa with different sensitivities to heat stress and use phylogenetic ANOVA to study the evolution of gene expression adaptation. We show that coral response to heat stress is a complex trait derived from multiple interactions among holobiont members. We identify host and photosymbiont genes that exhibit lineage-specific expression level adaptation and uncover potential roles for bacterial associates in supplementing the metabolic needs of the coral-photosymbiont duo during heat stress. Our results stress the importance of integrative and comparative approaches across a wide range of species to better understand coral survival under the predicted rise in sea surface temperatures.</p>
ScienceDex guides
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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.