Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
12,346
datasets available to search
ShareScore release 0.9.0
Dataset results
12,346 results for “derivatives”
TROPOMI-derived ground level NO2 concentrations (2019 Annual mean)
<p>Annual mean ground level NO2 concentrations derived from TROPOMI satellite NO<sub>2</sub> observations. Ground level concentrations are derived from observed column densities using the GEOS-Chem chemical transport model constrained with ground monitor observations following the method outlined in Cooper et al 2021 (DOI: 10.1038/s41586-021-04229-0)</p> <p><br> Annual mean data are provided at ~1x1 km<sup>2</sup> resolution at satellite overpass time (~1:30 PM local). Datasets are in netcdf (.nc) format.</p>
Annual mean TROPOMI-derived ground-level NO2 mixing ratio (2019 - North America v1)
<p>Annual mean ground-level NO2 mixing ratio for 2019 inferred from the TROPOMI satellite instrument over North America at 0.025x0.03125 degree resolution. Included is 2019 annual mean and 1.5 year mean spanning July 2018 – December 2019.</p> <p><strong>Reference:</strong></p> <p>Cooper, M.J., R.V. Martin, C.A. McLinden, and J.R. Brook (2020), Inferring ground-level nitrogen dioxide concentrations at fine spatial resolution applied to the TROPOMI satellite instrument, Env. Res. Lett., DOI:10.1088/1748-9326/aba3a5</p>
Tree-ring dataset derived from timbers of roof structures at Colegial del Salvador church in Seville and Jaen Cathedral (Spain)
<p>Tree-ring dataset in Heidelberg format derived from pine (Pinus sp.) timbers of the roof structures at Jaen Cathedral (dendro code JCS) and the Colegial del Salvador church in Seville (code SCS). These samples were researched within the scope of the NWO-funded project <em>Filling in the blanks in European dendrochronology</em>. They are documented in the following article:</p> <p>Domínguez-Delmás, M.,<strong> </strong>Van Daalen, S., Alejano-Monge, R., Wazny,T., 2018. Timber resources, transport and woodworking techniques in post-medieval Andalusia (Spain): Insights from dendroarchaeological research on historic roof structures. <em>Journal of Archaeological Science</em> <strong>95</strong>: 64–75. <a href="https://doi.org/10.1016/j.jas.2018.05.002">https://doi.org/10.1016/j.jas.2018.05.002</a></p> <p>This upload includes the supplementary material accompanying the article (tables with sampled elements on each building and their metadata). While most of the timbers from Jaen Cathedral are dated, only two of 71 from the Colegial are dated.If discrepancies exist between the metadata inserted in the headers of the measurements and tables uploaded here and the metadata on the article, the metadata published in the article prevails.</p>
SEVIRI derived ET data sets
<p>There are two relevant SEVIRI derived ET data sets distributed by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF) (<a href="https://landsaf.ipma.pt/en/data/">https://landsaf.ipma.pt/en/data/</a>; last access: 1 December 2021); (i) SEVIRI- actual ET (SEVIRI-ET<sub>a</sub>) that accounts for the water evaporated from the soil surface, vegetation canopy and water bodies, and (ii) SEVIRI- ‎reference ET (SEVIRI-ET<sub>0</sub>) that accounts for the (local) atmospheric demand and corresponds to the ET from a hypothetical well-watered green grass having 12 cm height and 0.23 albedo under the given down-welling short-wave radiation (Allen et al., 1998). These data sets are being provided in near real-time through the LSA SAF operational system and we used them in the GEOEssential project for water stress workflow development. For more information, please contact Dr. Bagher Bayat (bagher.bayat@gmail.com and b.bayat@fz-juelich.de).</p>
SEVIRI derived ET data sets V2
<p>This data set is SEVIRI derived ET distributed by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF) (<a href="https://landsaf.ipma.pt/en/data/">https://landsaf.ipma.pt/en/data/</a>; last access: 1 December 2021). There are two relevant SEVIRI derived ET data sets (i) SEVIRI- actual ET (SEVIRI-ET<sub>a</sub>) that accounts for the water evaporated from the soil surface, vegetation canopy and water bodies, and (ii) SEVIRI- ‎reference ET (SEVIRI-ET<sub>0</sub>) that accounts for the (local) atmospheric demand and corresponds to the ET from a hypothetical well-watered green grass having 12 cm height and 0.23 albedo under the given down-welling short-wave radiation (Allen et al., 1998). These data sets are being provided in near real-time through the LSA SAF operational system and we used them in the GEOEssential project for water stress workflow development. For more information, please contact Dr. Bagher Bayat (bagher.bayat@gmail.com and b.bayat@fz-juelich.de).</p>
Maps of thermal inertia, dielectric constant and brightness temperature of asteroid (16) Psyche derived from ALMA data
<p>These data and results are in support of the findings by Cambioni, S., de Kleer, K. and Shepard, M. in their paper "The Heterogeneous Surface of Asteroid (16) Psyche", Journal of Geophysical Research: Planets, link: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JE007091. </p> <p>If using any of this material, please cite the above article as doi: 10.1029/2021JE007091</p> <p> </p>
Basic tools for deriving photolysis endpoints for soil photo-transformation products in groundwater
<p>This spreadsheet has been designed to determine input parameters for consideration of the photolysis pathway in FOCUS-PELMO 5.5.3 and subsequent versions. It should be used alongside the EFSA scientific guidance on “Soil phototransformation products in groundwater – consideration, parameterisation and simulation in the exposure assessment of plant protection products”.</p> <p>The tools in the spreadsheet allow to identify the relevant grid points in the solar database 'AGRI4CAST', to retrieve irradiance values for the relevant grid points and for the period of the study from the 'AGRI4CAST' database via a spatial interpolation of the irradiance values (this can also be used for other solar databases besides 'AGRI4CAST'). Furthermore, the tools enable to convert the irradiance from kWh/m², kJ/m² or J/cm² into W/m², to perform a time-step normalisation for field studies, and to compare the normalised k<sub>fast</sub> values from different field studies.</p>
Raw Data for the article: Changes in the Transcriptome Profiles of Human Amnion-Derived Mesenchymal Stromal/Stem Cells Induced by Three-Dimensional Culture: A Potential Priming Strategy to Improve Their Properties
<p>Mesenchymal stromal/stem cells (MSCs) are believed to function in vivo as a homeostatic tool that shows therapeutic properties for tissue repair/regeneration. Conventionally, these cells are expanded in two-dimensional (2D) cultures, and, in that case, MSCs undergo genotypic/phenotypic changes resulting in a loss of their therapeutic capabilities. Moreover, several clinical trials using MSCs have shown controversial results with moderate/insufficient therapeutic responses. Different priming methods were tested to improve MSC effects, and three-dimensional (3D) culturing techniques were also examined. MSC spheroids display increased therapeutic properties, and, in this context, it is crucial to understand molecular changes underlying spheroid generation. To address these limitations, we performed RNA-seq on human amnion-derived MSCs (hAMSCs) cultured in both 2D and 3D conditions and examined the transcriptome changes associated with hAMSC spheroid formation. We found a large number of 3D culture-sensitive genes and identified selected genes related to 3D hAMSC therapeutic effects. In particular, we observed that these genes can regulate proliferation/differentiation, as well as immunomodulatory and angiogenic processes. We validated RNA-seq results by qRT-PCR and methylome analysis and investigation of secreted factors. Overall, our results showed that hAMSC spheroid culture represents a promising approach to cell-based therapy that could significantly impact hAMSC application in the field of regenerative medicine.</p>
The urban boundaries of 196 cities in China for deriving urban precipitation intensity-duration-frequency curves
<p>The shapefiles of urban boundaries of 196 cities in China are generated by processing and filtering the outputs of Li et al., (2018). Mapping global urban boundaries from the global artificial impervious area (GAIA) data. </p>
Thermal demagnetization data of Risica et al. (Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala)
<p>Thermal demagnetization data (repository data) of Risica et al. "Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala".</p>
MOLECULAR MIMICRY BETWEEN TUMOR ASSOCIATED ANTIGENS AND MICROBIOTA-DERIVED EPITOPES.
<p><strong>Background: </strong>The gut microbiota profile is unique for each individual and are composed by different bacteria species according to individual birth-to-infant transitions. In the last years, the local and systemic effects of microbiota on cancer onset, progression and response to treatments, such as immunotherapies, have been extensively described. Here we offer a new perspective, proposing a role for the microbiota based on the molecular mimicry of tumor-associated antigens by microbiome-associated antigens.</p> <p><strong>Methods:</strong> In the present study we looked for homology between published TAAs and non-self microbiota-derived epitopes. Blast search for sequence homology was combined with extensive bioinformatics analyses.</p> <p><strong>Results:</strong> Several evidences for homology between TAAs and microbiota-derived antigens have been found. Strikingly, three cases of 100% homology between the paired sequences has been identified. The predicted average affinity to HLA molecules of microbiota-derived antigens is very high (<100nM). The structural conformation of the microbiota-derived epitopes is, in general, highly similar to the corresponding TAA. In some cases, it is identical and contact areas with both HLA and TCR chains are indistinguishable. Moreover, the spatial conformation of TCR-facing residues can be identical in paired TAA and microbiota-derived epitopes, with exactly the same values of planar as well as dihedral angles.</p> <p><strong>Conclusions:</strong> The data reported in the present study show for the first time the high homology in the linear sequence as well as in structure and conformation between TAAs and peptides derived from microbiota species of the Firmicutes and the Bacteroidetes phyla, which together account for 90% of gut microbiota. Cross-reacting CD8<sup>+</sup> T cell responses are very likely induced. Therefore, the anti-microbiota T cell memory may turn out to be an anti-cancer T cell memory, able to control the growth of cancer developed during the lifetime if the expressed TAA is similar to the microbiota epitope. This may ultimately represent a relevant selective advantage for cancer patients and may lead to a novel preventive anti-cancer vaccine strategy.</p>
Satellite-derived chlorophyll-a concentrations for Lake Hume (Australia) using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery
<p>This dataset contains satellite-derived chlorophyll-a data of Lake Hume (Australia) for the period 21 Mar. 2013 - 01 Feb. 2021. Chlorophyll-a concentrations have been calculated using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery.</p> <p>Mixture Density Networks are a class of neural networks that tackle the inverse problem by modelling the multimodal distribution of target variables using a mixture of Gaussians. For more information, please refer to the following:</p> <ul> <li>Pahlevan, N., Smith, B., Alikas, K., Anstee, J., et al. (2022). Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3. <em>Remote Sensing of Environment, 270</em>, 112860</li> <li>Smith, B., Pahlevan, N., Schalles, J., et al. (2021). A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks. <em>Frontiers in Remote Sensing, 1</em></li> <li>Pahlevan, N., Smith, B., Schalles, J., et al. (2020). Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach. <em>Remote Sensing of Environment, 240</em>, 111604</li> </ul>
Satellite-derived chlorophyll-a concentrations for Western Water Treatment Plant (Melbourne, Australia) using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery
<p>This dataset contains satellite-derived chlorophyll-a data of the Western Water Treatment Plant (Melbourne, Australia) for the period 21 Mar. 2013 - 01 Feb. 2021. Chlorophyll-a concentrations have been calculated using Mixture Density Networks and Sentinel-2 and Landsat 8 imagery.</p> <p>Mixture Density Networks are a class of neural networks that tackle the inverse problem by modelling the multimodal distribution of target variables using a mixture of Gaussians. For more information, please refer to the following:</p> <ul> <li>Pahlevan, N., Smith, B., Alikas, K., Anstee, J., et al. (2022). Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3. <em>Remote Sensing of Environment, 270</em>, 112860</li> <li>Smith, B., Pahlevan, N., Schalles, J., et al. (2021). A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks. <em>Frontiers in Remote Sensing, 1</em></li> <li>Pahlevan, N., Smith, B., Schalles, J., et al. (2020). Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach. <em>Remote Sensing of Environment, 240</em>, 111604</li> </ul>
Endmember spectra and classified maps derived from CRISM targeted data at the south pole of Mars
<p><strong>Overview</strong></p> <p>Current maps of compositional variation across south polar ice exposures on Mars do not resolve the meter-scales at which erosional processes are most active, ultimately limiting our understanding of how the deposits form and evolve and how they can be used to interpret long-term climate records. In this study, we use <em>k</em>-means clustering and random forest classification to identify and map a set of universal spectral endmembers across 167 high-resolution observations acquired during southern summer by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). The 21 endmembers show distinct combinations and strengths of key infrared absorption features reflecting diverse mixtures of CO<sub>2</sub> ice, H<sub>2</sub>O ice, and dust. The resulting compositional framework can be used to characterize the nature of both seasonal CO<sub>2</sub> frost and the residual ices it overlies across a variety of terrains. </p> <p> </p> <p><strong>Contents</strong></p> <p>The repository contains three .zip files, which can be expanded to access the files described below:</p> <ul> <li><strong>classified_maps.zip</strong> <ul> <li>lookup_files <ul> <li><em>SP_CRISM_RF_ColorMap.clr</em> : An ESRI-formatted color map file that can be used to apply the endmember color scheme to random forest-classified maps in ArcGIS (see Symbology settings).</li> <li><em>SP_CRISM_RF_ColorMap.txt</em> : A text file that can be loaded into Python as a numpy array and used to generate a matplotlib color ramp. Row indices correspond to endmember numbers (see below) and columns are red, green, and blue values scaled from 0 to 1.</li> <li><em>SP_CRISM_RF_Endmember_Lookup.csv</em> : A lookup table that can be used to cross-reference between endmember numbers (as stored in GeoTiffs or the indices of the colormaps above) and corresponding endmember names (C1, Dc2, etc.).</li> </ul> </li> <li>morphologic_reference <ul> <li>Contains GeoTiffs of the R1330 spectral parameter (reflectance at 1330 nm) for each processed CRISM observation. Filenames indicate the observation ID, Mars Year, and solar longitude (Ls) of acquisition ("Ls314-07" = Ls 314.07º). These images can be used as a reference for the surface morphology and albedo of each scene. Tie points used to georeference these images to other datasets can be applied to the random forest classification maps to properly align endmember mapping results.</li> </ul> </li> <li>random_forest_classification <ul> <li>Contains GeoTiffs of the random forest classification results for each processed CRISM observation. Filenames indicate the observation ID, Mars Year, and solar longitude (Ls) of acquisition ("Ls314-07" = Ls 314.07º). These images are not rendered to display colors consistent with the publication figures, but instead store the endmember classification for each pixel as a number from 0 to 21; use the contents of <em>lookup_files</em> to find the corresponding endmember name or render the image with the color scheme from the publication. To view rendered summary plots of each observation, see the contents of <em>observation_info</em>. To georeference these images to other datasets, use the corresponding morphologic reference (see above) to set tie points.</li> </ul> </li> </ul> </li> <li><strong>observation_info.zip</strong> <ul> <li>footprint_shapefile <ul> <li>Contains the components of an ESRI shapefile that outlines the surface footprint/coverage of each processed CRISM observation. The attributes associated with each observation are the same as those in <em>observation_lookup</em> below. Note that the polygons extend slightly beyond the area shown in maps in <em>random_forest_classification</em> due to the inclusion of border pixels.</li> </ul> </li> <li>observation_lookup <ul> <li><em>SP_CRISM_Classified_Obs_Info.csv</em> : Information on each processed CRISM observation; this is the same file as Table S1 in the publication. Includes the MY and Ls of acquisition and (where applicable) the figure panel where the observation appears in the publication. The location of each observation is indicated with Center Latitude/Longitude and the assigned Spatial Domain (see Figure 1 in the publication). The Observation ID can be used to locate the source Targeted Reduced Data Record (TRDRs, Version 3) on the Geosciences Node of the Planetary Data System. The spatial extent of each observation is provided in the <em>footprint_shapefile</em> described above. </li> </ul> </li> <li>summary_plots <ul> <li>Contains summary plots of the endmember map generated for each processed CRISM observation. Each plot notes the observation ID, Mars Year, and Ls and displays the morphologic reference map, random forest classification map, and a breakdown of the endmembers that are present. To access the maps rendered here, see the contents of <em>classified_maps.zip</em>.</li> <li>Also contains the full-resolution version of Figure S3 from the publication (<em>All_Obs_Unprojected.png</em>), which can be used to lookup observations of interest via small labels above each map. </li> </ul> </li> </ul> </li> <li><strong>spectral_library.zip</strong> <ul> <li>Contains spectral libraries with the median spectrum of each endmember as presented in Figure 3 in the publication. A basic text file listing the wavelength (WVL) and normalized reflectance values for each endmember is included (<em>SP_CRISM_EndmemberMedians.txt</em>) as well as an ENVI-formatted spectral library (S<em>P_CRISM_EndmemberMedians_ENVI.sli</em>). Note that a subset of the 438 wavelengths sampled in the source CRISM data were removed around the longest and shortest wavelengths and the filter boundary to avoid error-prone bands, leaving these spectral libraries with 404 bands.</li> </ul> </li> </ul>
Data/Code: Objective monitoring of functional recovery after total knee and hip arthroplasty using sensor-derived gait measures
<p>Abstract</p> <p>Background: Inertial sensors hold the promise to objectively measure functional recovery after total knee (TKA) and hip arthroplasty (THA), but their value in addition to patient-reported outcome measures (PROMs) has yet to be demonstrated. This study investigated recovery of gait after TKA and THA using inertial sensors, and compared results to recovery of self-reported scores of pain and function.</p> <p>Methods: PROMs and gait parameters were assessed before and at two and fifteen months after TKA (n=24) and THA (n=24). Gait parameters were compared with healthy individuals (n=27) of similar age. Gait data were collected using inertial sensors on the feet, lower back, and trunk. Participants walked for two minutes back and forth over a 6m walkway with 180° turns. PROMs were obtained using the Knee Injury and Osteoarthritis Outcome Scores and Hip Disability and Osteoarthritis Outcome Score.</p> <p>Results: Gait parameters recovered to the level of healthy controls after both TKA and THA. Early improvements were found in gait-related trunk kinematics, while spatiotemporal gait parameters mainly improved between two and fifteen months after TKA and THA. Compared to the large and early improvements found in of PROMs, these gait parameters showed a different trajectory, with a marked discordance between the outcome of both methods at two months post-operatively.</p> <p>Conclusion: Sensor-derived gait parameters were responsive to TKA and THA, showing different recovery trajectories for spatiotemporal gait parameters and gait-related trunk kinematics. Fifteen months after TKA and THA, there were no remaining gait differences with respect to healthy controls. Given the discordance in recovery trajectories between gait parameters and PROMs, sensor-derived gait parameters seem to carry relevant information for evaluation of physical function that is not captured by self-reported scores.</p>
Raw Data to "Theoretical Study on the Photoacidity of Hydroxypyrene Derivatives in DMSO Using ADC(2) and CC2"
<p>This data is a supplement to the publication entitled "Theoretical Study on the Photoacidity of Hydroxypyrene Derivatives in DMSO Using ADC(2) and CC2" in the The Journal of Physical Chemistry A (DOI: 10.1021/acs.jpca.2c04436). It contains the structures (as '.xyz' files) and HF/DFT energies from the quantum chemical (QC) calculations using TURBOMOLE (version 7.4).</p> <p>Additional information on the file structure is given in the README file.</p>
Composite geostationary weather satellite images (second time derivative of water vapor channel) for visualizing Lamb waves
<p>Second time derivative of water vapor channel (6.2 micrometer) brightness temperature from geostationary weather satellites (Units: K s<sup>-2</sup>)</p> <p>Himawari-8 (original data obtained from NICT Science Cloud)</p> <p>GOES-16/17 (original data obtained from Amazon AWS)</p> <p>Meteosat-8/9/10/11 (original data obtained from EUMETSAT)</p> <p> </p> <p>Time interval of the files: 5 minutes</p> <p> </p> <p>Time interval of each satellite, dt for time derivative:</p> <p>Himaawri-8, GOES-16/17: 10 minutes, 10 minutes</p> <p>Meteosat-8/9/11: 15 minutes, 15 minutes</p> <p>Meteosat-10: 5 minutes, 10 minutes</p> <p> </p> <p>Each file contains the latest images from those satellites at that time. The time stamp for each satellite represents the beginning of each full-disk scan.</p> <p> </p> <p>Bias correction:</p> <p>Himawari-8: bias removal for each swath</p> <p>GOES-16/17, Meteosat-11: bias removal for each east-west line</p> <p>Meteosat-8/9/10: bias removal for each east-west line (note: satellite attitude was not stable)</p> <p> </p> <p>Smoothing:</p> <p>Band-pass filter for each full-disk image separately: 2-40 degrees on lat-lon coordinate</p> <p>Stronger smoothing at latitudes higher than 60 degrees north/south</p> <p> </p> <p>Down-sampling:</p> <p>Full-disk images were mapped to a 0.04-degree lat-lon coordinate.</p> <p>Then, composite images were produced at the 0.2-degree resolution.</p> <p> </p> <p>Version 2:</p> <p>Improved interpolation algorithm</p> <p>Himawari-8: improved geolocation</p> <p>Meteosat-8/9: improved treatment of noise near the edge of full disk images</p>
Data for "Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study"
<p>Datasets underlying the analysis of the paper: "Associations between 3D surface scanner derived anthropometric measurements and body composition in a cross-sectional study"</p> <p>This upload includes the following:</p> <ul> <li><strong>data_study.csv </strong>: contains socio-demographic, health- and lifestyle factors, and body scan variables of each participant</li> <li><strong>healthscore.csv</strong> : contains the "healthy score" from the food frequency questions calculated from from five food categories: fruits, vegetables, wholegrain products, meat, and sweet/salty snacks. For each category the officially recommended minimum or maximum amount of weekly intake was used as the cut-off value and a point was assigned if the recommendation was met. A score from 0 to 5 was built to reflect the overall healthiness of the diet.</li> </ul>
Compositional maps of the lunar polar regions derived from the Kaguya Spectral Profiler and the Lunar Orbiter Laser Altimeter data
<p>Compositional maps of the lunar polar regions derived from the Kaguya Spectral Profiler and the Lunar Orbiter Laser Altimeter data as described in Lemelin et al. (2022). </p> <p>This folder includes different GeoTIFF files described and shown in Lemelin et al. (2022). The files are projected in Polar Stereographic Projection, at a spatial resolution of 1000 m/pixel. A version of each of the following file is given for the north and south polar region (50-90 N/S).</p> <p>- Gridded and interpolated Spectral Profiler reflectance mosaics scaled to the LOLA dataset at 1064 nm<br> - Data counts used in the gridded and interpolated Spectral Profiler reflectance mosaics scaled to the LOLA dataset at 1064 nm<br> - Spectral Profiler FeO mosaics <br> - Spectral Profiler OMAT mosaics <br> - Spectral Profiler plagioclase mosaics <br> - Spectral Profiler olivine mosaics <br> - Spectral Profiler low-calcium pyroxene mosaics<br> - Spectral Profiler high-calcium pyroxene mosaics <br> - Nanophase iron mosaics <br> - Correlation coefficient mosaics</p>
MD setup data for ansamer amanitin derivatives and precursors for atroposelective synthesis
<p>Setup files to reproduce the MD simulations for the amanitin derivatives <strong>4a </strong>and <strong>4b</strong> as well as the precursors <strong>3b</strong> and <strong>3c. </strong>The MD simulations were part of the study:</p> <p>G. Yao, S. Kosol, M. T. Wenz, E. Irran, B. G. Keller, O. Trapp, R. D. Süssmuth, <em>ChemRxiv</em> 2022, DOI 10.26434/chemrxiv-2022-ll8lq.</p> <p>For further instructions on the files, please refer to '0_README'.</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.