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5,229 results for “Major”
Data: Breeding progress for pathogen resistance is a second major driver for yield increase in German winter wheat at contrasting N levels
<p>This is the experimental data set of Zetzsche, et. al. (2020, Scientific Reports: doi.org/10.1038/s41598-020-77200-0) based on a three-year field trial (2014/15, 2015/16, 2016/7) of 178 German elite winter wheat cultivars.</p> <p>The table (QLB_BRIWECS_WW_fieldtrial_adjustMeans_treatments.csv) subsumes the adjusted mean values of four fungal disease scores (average ordinates) and six yield-related traits investigated at four treatments (T1: 110 kg N ha<sup>-1</sup>, no fungicides; T2: 110 kg N ha<sup>-1</sup> + fungicide; T3: 220 kg N ha<sup>-1</sup>, no fungicides; T4: 220 kg N ha<sup>-1</sup> + fungicide) of two replicates each over three years. Data of each trait are considered independent for all four treatments. Details of the plant material, the experimental site, the trail design as well as the phenotyping of the diseases and agronomical traits are given in the material and methods section of the related publication. Further metadata on the plant material and the trial design are provided in the Supplementary information of the publication.</p>
Major ions in Trambau ice core, Nepal Himalaya
<p>An 81.2-m-long ice core was drilled in November 2019 at 5862m a.s.l. of Trambau Glacier, Rolwaling region, Nepal Himalaya (27.919° N, 86.545° E). This data set contains the concentrations of major ions and tritium concentrations in the ice core.</p> <p>The data set contains Depth in snow/ice (m), Depth in water equivalent (m w.e.), Date (digit year), Na (ppb), Cl (ppb), NH4 (ppb), K (ppb), Mg (ppb), Ca (ppb), NO3 (ppb), SO4 (ppb), T_rough (TU), T_fine (TU)</p>
Uncovering major types of deforestation frontiers across the world's tropical dry woodlands
<p>These datasets provide maps of deforestation frontier classsification into three themed typologies (severity, spatio temporal patterns and development stage) and archetypes of major frontier patterns. We do this for tropical dry woodland worldwide, for the period of 2000 to 2020, at ~3-km spatial resolution (Coordinate System: WGS_1984_Mollweide, float format). Datasets used for this analysis are publicly available, forest cover and loss data are available at: https://data.globalforestwatch.org/. Deforestation frontiers metrics were calculated and typologies developed in RStudio 1.3.1056. We share the code used to develop frontier metrics, frontier typologies, and archetypes, together with a sample dataset summarized from the originally publicly available dataset.</p> <p>Further details of the datasets can be found in Buchadas et. al. (2022): https://doi.org/10.1038/s41893-022-00886-9 </p> <p>For further questions or issues with the datasets, please contact Ana Buchadas at ana.buchadas@geo.hu-berlin.de.</p>
Data Release: "No evidence that the majority of black holes in binaries have zero spin"
<p>This dataset contains the results presented in "<em>No evidence that the majority of black holes in binaries have zero spin</em>".</p> <p>In this paper, we systematically explored the effective and component spin distributions of binary black holes among the LIGO/Virgo GWTC-3 catalog. In particular, we tried to answer the following core questions, which have been the subject of active exploration and some debate in the literature:</p> <p><em>1. Is there an excess of binary black holes with vanishing spin, as predicted by some theories of angular momentum transport in stellar cores?</em></p> <p><strong>We find no evidence for an excess of vanishing spin systems.</strong> This finding is confirmed by three complementary analyses: one relying only on the Bayes factors between spinning and non-spinning priors for each BBH observation, one that seeks to model the distribution of effective aligned spins, and one modeling the distribution of component spin magnitudes and misalignment angles. Instead, we find BBH spin magnitudes to be consistent with a single, continuous distribution that remains finite at magnitude zero.</p> <p><em>2. Do there exist binaries with component spins misaligned by more than 90 degrees relative to their orbits?</em></p> <p><strong>We find a strong preference for the existence of such strongly misaligned spins.</strong> Our analysis of the BBH component spin distribution indicates that at least some component spins are misaligned from their orbits by more than 90 degrees. This result is robust under a variety of modeling choices regarding both the distribution of component spin magnitudes and tilts.</p> <p>The code used to generate this data can be found in the repository <a href="https://github.com/tcallister/gwtc3-spin-studies/">https://github.com/tcallister/gwtc3-spin-studies/</a>. This repository includes <a href="https://github.com/tcallister/gwtc3-spin-studies/tree/main/data">jupyter notebooks</a> that can be used to open, explore, and plot the files contained in this data set. Additional information about reproducing and/or using this dataset can be found in <a href="https://tcallister.github.io/gwtc3-spin-studies/build/html/index.html">our associated documentation</a>.</p> <p>Further notes:</p> <ul> <li>The files <em>sampleDict_FAR_1_in_1_yr.pickle</em> and <em>injectionDict_FAR_1_in_1.pickle</em>, used as inputs to our analyses, are created via code in the repository <a href="https://github.com/tcallister/get-lvk-data">https://github.com/tcallister/get-lvk-data</a> (see also <a href="https://zenodo.org/record/6505409">https://zenodo.org/record/6505409</a>).</li> <li>The file <em>posteriors_gaussian_spin_samples_FAR_1_in_1.json</em>, used for figure generation, was published by the LIGO Scientific Collaboration, Virgo Collaboration, and KAGRA Collaboration in support of the paper "<a href="https://arxiv.org/abs/2111.03634">The population of merging compact binaries inferred using gravitational waves through GWTC-3</a>" (see <a href="https://zenodo.org/record/5655785">https://zenodo.org/record/5655785</a>).</li> </ul>
Functional genomics analysis to disentangle the role of genetic variants in major depression - Supplementary Tables
<p>This entry contains the data generated by the study "Functional genomics analysis to disentangle the role of genetic variants in major depression" that are part of the Supplementary information of the article describing the study.</p> <p>The entry contains the following data:</p> <p><strong>Supplementary Tables S1-S7</strong></p> <p>Supplementary Table S1. Summary of resources.</p> <p>Supplementary Table S2. Causal GVs for MD.</p> <p>Supplementary Table S3. pGenes functional and disease enrichment analysis.</p> <p>Supplementary Table S4. Fine-mapped MD causal GVs disease enrichment analysis.</p> <p>Supplementary Table S5. Colocalizing GWAS-eQTLs association to disease.</p> <p>Supplementary Table S6. TFBS analysis.</p> <p>Supplementary Table S7. GVs state annotation. </p>
COMPREHENSIVE LIVESTOCK HEALTH PROGRAM: TARGETED TREATMENT AND HOLISTIC INTERVENTIONS FOR MAJOR PREVALENT DISEASES IN THE LIVESTOCK FARMING COMMUNITY OF DAYNILE DISTRICT, MOGADISHU, SOMALIA.
<p>The general objective of this project was to intervene with the most common livestock diseases in Dayniile district by carrying out a comprehensive campaign for treatment and control. The specific objectives consisted of a treatment campaign, improving infrastructure for establishing disinfectant foot dips and hand washing points, providing disinfectant tools, and finalising community engagement and education by doing training at the farm level.<br>The team visited different donors and added their contribution. After collecting sufficient funds from various sources, the team began the procurement of the necessary materials. This included purchasing veterinary drugs and supplies from local pharmacies and other essentials like stationery. The first activity was treatment campaigns, which were a central aspect of the project. Over 290 animals were treated for various diseases and conditions. The farm manager was informed of the diagnoses, and upon receiving their permission, the appropriate treatments were administered. The second intervention action was a vaccination campaign. The team vaccinated a total of 70 animals against clostridial bacteria, which is one of the most common camel diseases encountered in the area. The third intervention was the establishment of biosecurity facilities at select livestock farms. Among all the farms involved in the project, five were chosen for the provision of enhanced biosecurity measures. These measures included the installation of foot dips and teat dips. The fourth activity was educating livestock farmers on strategies for controlling and preventing livestock diseases. The training was held at Beder Camel Dairy Farm and attended by approximately 10 individuals, comprising 3 females and 7 males. The content of the training was three modules: the first was general farm biosecurity, the second was operational biosecurity, and the third was concern for vaccination. Recommendation: We recommend that each farm hire livestock health specialists to easily implement disease prevention steps and promptly solve each new case.<br> We recommend the livestock association, veterinary clinics, and other institutions working on livestock do routine campaigns that facilitate the determination of prevalent diseases and the treatment of those cases</p>
A Global Plate Model Including Lithospheric Deformation Along Major Rifts and Orogens Since the Triassic
<p>Global deep‐time plate motion models have traditionally followed a classical rigid plate approach, even though plate deformation is known to be significant. Here we present a global Mesozoic–Cenozoic deforming plate motion model that captures the progressive extension of all continental margins since the initiation of rifting within Pangea at ~240 Ma. The model also includes major failed continental rifts and compressional deformation along collision zones. The outlines and timing of regional deformation episodes are reconstructed from a wealth of published regional tectonic models and associated geological and geophysical data. We reconstruct absolute plate motions in a mantle reference frame with a joint global inversion using hot spot tracks for the last 80 million years and minimizing global trench migration velocities and net lithospheric rotation. In our optimized model, net rotation is consistently below 0.2°/Myr, and trench migration scatter is substantially reduced. Distributed plate deformation reaches a Mesozoic peak of 30 × 106 km2 in the Late Jurassic (~160–155 Ma), driven by a vast network of rift systems. After a mid‐Cretaceous drop in deformation, it reaches a high of 48 x 106 km2 in the Late Eocene (~35 Ma), driven by the progressive growth of plate collisions and the formation of new rift systems. About a third of the continental crustal area has been deformed since 240 Ma, partitioned roughly into 65% extension and 35% compression. This community plate model provides a framework for building detailed regional deforming plate networks and form a constraint for models of basin evolution and the plate‐mantle system.</p> <p> </p> <p>The agegrids associated with this model can be accessed at: <a href="https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2019_Tectonics/" target="_blank" rel="noopener">https://repo.gplates.org/webdav/PlateModel_Age_SR_Grids/Muller_etal_2019_Tectonics/</a></p>
Supplementary Dataset: chapter 9 of "Chemostratigraphy Across Major Chronological Boundaries"
<p>This dataset belongs to the book chapter (ch 9): "Chemostratigraphy across the Permian-Triassic Boundary: The Effect of Sampling Strategies on Carbonate-carbon Isotope Stratigraphic Markers" written by: Schobben, M., Heuer, F., Tietje, M., Ghaderi, A., Korn, D., Korte, C., Wignall, P.B., as part of the book: "Chemostratigraphy Across Major Chronological Boundaries", published by the American Geophysical Union and Wiley, The book is edited by Sial, A.N., Gaucher, C., Ramkumar, M., Ferreira, V.P. and is due to appear in Januari 2019. The dataset is the bulk carbonate carbon and oxygen isotope data used in the aforementioned chapter. The x and y column refer to coordinates on the drilled surface of the polished rock slabs.</p>
Panel data used in the paper ""The shadow price of irrigation water in major groundwater depleting countries"
<p>The panel data are used in an econometric analysis estimating Cobb-Douglas production functions that are subsequently used to calculate the shadow price (current marginal value) or irrigation water in 11 major groundwater depleting countries.</p>
Data archive associated with "Landscape age as a major control on the geography of soil weathering" (https://doi.org/10.1029/2019GB006266)
<p>(1) Table including parameter values and weathering model outputs associated with NASGLP sampling locations (SLP_data.csv). </p> <p>(2) List of rivers used for calibrating erosion estimates (river_list.csv).</p> <p>(3) R workspace with same data as (1), plus a data frame of global parameter values ("gm") and spatial polygons giving continent boundaries ("con").</p> <p>(4) Scripts with functions for running the single-compartment weathering model at individual point locations or running a global sample of locations and computing summary statistics by continent (run_soilgenesis.R; soilgenesis.R). </p>
Geoscience undergraduate major course requirements
<p>This data compilation contains course requirements for undergraduate geoscience majors in Earth Science departments at 50 R1 universities in the United States. The authors of this compilation (Ken Ferrier, Eva Golos, and Marianne Haseloff at the University of Wisconsin-Madison) collected these data in March-April 2024 (n = 966 courses in total) from each department’s publicly accessible webpage. These data are organized in four tables, which contain data on the geoscience courses and credits required inside the home department and the cognate courses and credits required outside the home department (e.g., Math, Physics, Chemistry).</p>
Major facilitator superfamily domain-containing protein 10 (MFSD10) A Target Enabling Package (TEP)
<p>MFSD10 (also known as TETRAN in humans) has been proposed to function as an organic anion efflux pump and as a transporter for some NSAIDs. We have produced milligram quantities of purified recombinant protein and solved its structure in an outward-facing state at 2.6 Å resolution by X-ray crystallography. The structure - the first example for a human atypical SLC - provides the initial clues to understanding the broad specificity of its putative substrate-binding site.</p>
Building a data curation pipeline for complex diseases: the case of Major Depression - Supplementary Material
<p>This entry contains the data generated by the study "Building a data curation pipeline for complex diseases: the case of Major Depression".</p>
fusion-jena/befchina-test-collection: Major service release
<p>This repository provides a test collection for dataset search in biodiversity. The test collections consists of 14 questions collected in different biodiversity research related projects and reflecting real user informations needs, a corpus of 372 datasets created in the scope of the <a href="https://bef-china.com">BEF-China project</a> and human assessments evaluating which dataset is relevant to a question.</p> <p>Further information on the BEF-China project can be obtained from the website: <a href="https://bef-china.com">https://bef-china.com</a>.</p> <p><em>version 2.0:</em> This service release provides the relevance judgments in the proper TREC format: <TOPIC><ITERATION><DATASET NUMBER><RELEVANCE> and duplicate entries are removed.</p> <p><a href="https://github.com/fusion-jena/befchina-test-collection">https://github.com/fusion-jena/befchina-test-collection</a></p>
Model agreement and trend analysis data associated to the publication: "Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050"
<p>This dataset is associated with the following publication:</p> <p>Haslebacher, C., Demory, M.-E., Demory, B.-O., Sarazin, M., and Vidale, P. L., “Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050. Projected increase in temperature and humidity leads to poorer astronomical observing conditions”, <em>Astronomy and Astrophysics</em>, vol. 665, 2022. doi:10.1051/0004-6361/202142493.</p> <p>In the folder 'model_agreement', there are pickle files from which a python dictionary can be extracted with:</p> <pre><code>with open('mypklfile.pkl', 'rb') as myfile: dload = pickle.load(myfile)</code></pre> <p>Pickle files ending with '_d_obs_ERA5.pkl' contain in situ data and ERA5 data. Pickle files ending with 'd_model.pkl' contain PRIMAVERA model data. A few explanations:<br> - 'ds_sel': contains monthly timeseries of selected intersecting data<br> - 'ds_taylor': contains data used for the Taylor diagram (Figs. 4-10)<br> - 'ds_mean_month': contains seasonal cycle for plotting (Figs. 4-10)<br> - 'ds_mean_year': contains yearly timeseries for plotting (Figs. 4-10) </p> <p>The subfolder 'median_nc_u_v_t' contains NETCDF files with the median and interquartile range of the wind speed in u and v direction, the temperature and geopotential height. This was used for Figs. G1-G8 and to calculate the refractive index structure constant Cn2.</p> <p>The subfolder 'skill_score_classification' contains csv files with the sorted skill score classifications. The column headers are: model_name, skill score, correlation coefficient, standard deviation, centred root mean square error.</p> <p>The folder 'trend_analysis' contains for each variable csv files of ERA5 and PRIMAVERA monthly time series used for trend analysis, pdf files of analysis summaries, csv files of Bayesian analysis results and png files of longitude-latitude maps of trends (analysed with linear regression). Additionally, there is a csv file of averaged in situ pressures.</p> <p>Code that generated and used this data is available on github: <a href="https://github.com/CarolineHaslebacher/Astroclimate-future-project">https://github.com/CarolineHaslebacher/Astroclimate-future-project</a> </p> <p> </p>
Restriction of access to the central cavity is a major contributor to substrate selectivity in plant ABCG transporters
<p>The input and main output files used for the paper <em><strong>"Restriction of access to the central cavity is a major contributor to substrate selectivity in plant ABCG transporters"</strong></em> are separated in the different tar files depending the MD stage they belong to.</p> <p><strong>Content</strong></p> <p>00_AlphaFold2: The models predicted from AlphaFold2</p> <p>01_build_system: The parameters for ATP and the initial pdb file used to build each system</p> <p>02_minimization: Minimization input files for each variant</p> <p>03_equilibration: Equilibration input files for each variant</p> <p>04_long_equilibration: ATP restrained equilibration input files for each variant</p> <p>05_free_equilibration: Free equilibration input files for each variant</p> <p>06_production: Free production input files for each variant</p> <p>07_caver: Caver calculations for each variant and replica</p> <p>08_transport_tools: Analysis of tunnel networks using TransportTools software</p> <p>09_tunnel_selection: Selection of the tunnels with widest bottleneck radius to perform CaverDock experiments</p> <p>10_caverdock: CaverDock calculations for each variant and for each ligand tested</p> <p>11_membrane_patch: MD simulations for liquiritigenin and POPC membrane only</p> <p>12_MD_analysis: Calculations of RMSD, RMSF of each system. Calculation of helical parameters for trans-membrane helices 2, 5, 8 and 11 (not for APO). Calculation of X1 and X2 angles for residue N1331 in each variant (not for APO)</p> <p>13_US_closed_to_open: Umbrella Sampling simulations to obtain the inward facing (IF) open state of each variant. Not used for PMF analysis.</p> <p>14_US_opening_energy: Umbrella Sampling simulations to obtain the Potential of Mean Force for the transition from IF-closed to IF-open conformations.</p> <p>15_US_equilibration: Equilibration input files for WT and F562L variants in IF-open states.</p> <p>16_US_production: Production input files for WT and F562L variants in IF-open states.</p> <p>17_US_caver: Caver calculations for WT and F562L variants in IF-open states.</p> <p>18_US_transport_tools: Analysis of tunnel networks using TransportTools software of WT and F562L variants in IF-open states.</p> <p>19_US_tunnel_selection: Selection of the tunnels with widest bottleneck radius to perform CaverDock experiments for WT and F562L variants in IF-open states.</p> <p>20_US_caverdock: CaverDock calculations for WT and F562L variants in IF-open states.</p> <p>21_US_MD_analysis: Calculations of RMSD, RMSF of each system. Calculation of helical parameters for trans-membrane helices 2, 5, 8 and 11.</p> <p>ABC_Sequences.fasta: Sequences from 1KP analysis</p>
Major South African highway binary crack dataset
<p>Binary crack dataset prepared using flexible road pavement images from a major South African Highway.The dataset has been used in the publication titled: Convolutional Neural Networks for Crack Detection on Flexible Road Pavements which was presented at the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) and forms part of the conference proceedings published by Springer.</p>
Supplementary Datasets and Movies for the Paper "Major California faults are smooth across multiple scales at seismogenic depth"
<p>Supplementary Datasets and Movies for the Paper<br> <strong>M</strong><strong>ajor California faults </strong><strong>are</strong><strong> smooth </strong><strong>across</strong><strong> multiple scales </strong><strong>at </strong><strong>seismogenic </strong><strong>depth</strong><br> by Anthony Lomax and Pierre Henry</p> <p>DOI: <a href="https://doi.org/10.26443/seismica.v2i1.324">https://doi.org/10.26443/seismica.v2i1.324</a></p> <p>Movies S1-2 Seismicity along the central San Andreas fault zone around Parkfield as Figure 1 in the main text. Shows rotating, lateral view around ~S40°E for (Movie S1) NCSS-DD and (Movie S2) NLL-SSST-coherence. See Figure 1 caption in the main text for key to figure elements.</p> <p>Movie S3-7 Animated, rotating later views of NLL-SSST-coherence relocations of seismicity other than Parkfield presented in the main paper and this supplement.<br> Movie_S1_Parkfield_2022_sect_DD_movie_20230401.mp4 Movie_S2_Parkfield_2022_sect_NLL-SSST-coherence_movie_20230401.mp4 Movie_S3_S_Calaveras_2022_NLL-SSST-coherence_movie_20230401.mp4 – Southern Calaveras Fault Zone<br> Movie_S4_Mendocino_2021_NLL-SSST-coherence_movie_20230401.mp4 – Cape Mendocino<br> Movie_S5_MountLewis_1986_NLL-SSST-coherence_movie_20230401.mp4 – Mount Lewis<br> Movie_S6_SW_SanFrancisco_NLL-SSST-coherence_movie_20230401.mp4 - Southwest of San Francisco<br> Movie_S7_Calipatria_2021_NLL-SSST-coherence_movie_20230401.mp4 - Calipatria sequence</p> <p>Datasets S1-5 CSV format catalogs of NLL-SSST-coherence relocation results presented in the main text.<br> CSV fields correspond to data in the <a href="http://alomax.net/nlloc/soft7.00/formats.html#_location_hypphs_">NLLoc Hypocenter-Phase file</a></p> <ul> <li>ds01_Parkfield_2004_NLL_SSST_coherence.csv - Parkfield</li> <li>ds02_S_Calaveras_2022_NLL_SSST_coherence.csv – Southern Calaveras Fault Zone</li> <li>ds03_Mendocino_2021_NLL_SSST_coherence,csv – Cape Mendocino</li> <li>ds04_MountLewis_1986_NLL_SSST_coherence.csv – Mount Lewis</li> <li>ds05_SW_SanFrancisco_2021_NLL_SSST_coherence.csv - Southwest of San Francisco</li> <li>ds06_Calipatria_2021_NLL_SSST_coherence.csv - Calipatria sequence</li> </ul> <p>File S1 (project_run_scripts.zip) Archive of run scripts and related set-up, configuration and other meta-data files for locations cases presented in this paper.</p>
Data for "Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the IMO 2020 fuel sulfur regulations"
<p>Processed data used for the manuscript "Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the IMO 2020 fuel sulfur regulations".</p> <p>Includes input data for kriging algorithm as "SSF1deg_shipkrige_Terra.nc" and output data files as "Data_Terra_[VAR]_[YEAR]_C_M[MONTH].nc" for [VAR] Acld (overcast albedo) or cer (cloud droplet effective radius), [YEAR] the starting year of a three-year period starting with 2002 and ending at 2020 or "clim" for the 2002-2019 climatology, and [MONTH] 1to12 (annual mean) or 9to11 (austral spring).</p> <p>For the output data, "Obs" is the original data, "Est" is the mean counterfactual field obtained via kriging, "lowEst" and "highEst" are the 2.5th and 97.5th percentiles of the kriged fields for each grid box, "krSims" stores the results of the 5,000 simulated kriged fields, "Semivariance" is the binned empirical variogram values, "pVal" is the raw field significance (not adjusted for multiple testing), "nOut" is the number of individually significant grid boxes, "tran" is the transform applied (none for cer, logit for Acld), "iniPhi" and "iniSigma2" are the initial values for the fitted variogram, "Phi" and "Sigma2" are the fitted values using weighted least squares, and "parSel" is the list of selected regressors for the mean function that minimize the Bayesian information criterion.</p>
Driven distance by commuters to the center of major and minor cities in Europe
<p>The two files contains respectively a map of driving distances around major and minor cities in Europe. The distance is given by range of 5 km from 5 to 45 km in a resolution of 100m*100m. The encoding is uint8.</p> <p>The metropolitan areas considered in this study are those from this study of <a href="https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Archive:European_cities_%E2%80%93_the_EU-OECD_functional_urban_area_definition">functional urban area definition</a>.</p> <p>The corresponding geofile is available at <a href="https://circabc.europa.eu/ui/group/8eafb630-27cf-4fae-a4c2-f1234a123fd7/library/59bfa33a-8f4b-413d-8552-ac0a93ad7e5f/details">this adress</a>.</p> <p>Most of the cities with more than 50'000 habitants are included, some cities have been removed or added depending on the local context.</p> <p>As the geofile contains only polygones of the metropolitan areas and not the city point, the points form cities with the number of habitants have been dowloaded from <a href="http://www.naturalearthdata.com/downloads/110m-cultural-vectors/110m-populated-places/">Natural Data</a> and then selected by comparison with the polygones.</p> <p>Cities with more than 20'000 have also been selected as commuting center for rural areas. Only the cities outside the metropolitan commuting zones are included.</p> <p>The calculation of driving distances around centers have been performed with <a href="https://openrouteservice.org/">OpenRouteService</a> (personal API key required, free of charge).</p> <p> </p> <p> </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.