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12,346 results for “derivatives”
RNA-Seq read counts from monocyte- and ips-derived macrophages
<p>This file contains raw RNA-Seq read counts from monocyte-derived macrophages (MDMs) and induced pluripotent stem cell-derived macrophages (IPSDMs) before and after 6 hours stimulation after LPS.</p> <p>The file was created using featureCounts. The first two columns are:</p> <ul> <li>gene_id: Ensembl 74 gene id.</li> <li>length: Length of the gene in bp.</li> </ul> <p>The MDM samples are:</p> <ul> <li>B1_ctrl</li> <li>B1_LPS</li> <li>B4_ctrl</li> <li>B4_LPS</li> <li>B5_ctrl</li> <li>B5_LPS</li> <li>B2_ctrl</li> <li>B2_LPS</li> <li>B3_ctrl</li> <li>B3_LPS</li> </ul> <p>The IPSDM samples are:</p> <ul> <li>CRL1_ctrl</li> <li>CRL1_LPS</li> <li>S7RE_ctrl</li> <li>S7RE_LPS</li> <li>FSPS10C_ctrl</li> <li>FSPS10C_LPS</li> <li>FSPS11B_ctrl</li> <li>FSPS11B_LPS</li> </ul> <p> </p>
Host-derived viral transporter protein for nitrogen uptake in infected marine phytoplankton
<p>Dataset for the article "Host-derived viral transporter protein for nitrogen uptake in infected marine phytoplankton", Monier et al.</p> <p>Data for all phylogenetic tree reconstructions (raw and masked protein sequence alignments in fasta format, tree file in newick format) and placement file (jplace format) of two environmental sequences are available.</p> <p>Data for all assay experiments are available: ammonium and urea assays, Omnilog phenotype screening (Nitrogen substrates).</p>
LiDAR-derived forest structure data and predictions of the locations of old-growth forests for Central Finland.
<p><strong>INTRO</strong><br> This archive contains data and analysis code for the Biodiversity Map -project conducted by Open Knowledge Finland (http://fi.okfn.org/projects/biodiversity-map/)</p> <p><strong>LICENCE</strong><br> The files listed below are all released to the public domain under a CC0 public domain dedication (https://creativecommons.org/publicdomain/zero/1.0/)</p> <p><strong>FILE DESCRIPTIONS</strong></p> <p><em><strong>FILE 1:</strong></em> background.zip<br> Inside the archive is a comma-separated file "background.csv" containing LiDAR-derived forest structure variables for 2/3 of Central Finland. These were derived from 3 raster data sets describing forest canopy maximum height (mh), forest canopy cover (cc) and lidar return intensity (in). The rasters had resolutions of 6 metres, 6 metres and 2 metres, respectfully. An 18 m resolution grid was then used to aggregate the rasters into average, minimum and maximum values + standard deviations of the original variables. The original LiDAR data was made available by the National Land Survey of Finland.</p> <p><br> <em><strong>FILE 2:</strong></em> conservation.lambdas<br> This file contains fitted parameters for the maxent model. For more information, check maxent documentation at https://www.cs.princeton.edu/~schapire/maxent/</p> <p><strong><em>FILE 3:</em></strong> conserved_swd.csv<br> Forest structure variables at 18 meter resolution for old-growth conservation areas in Central Finland. A subset of background.csv. This file still has a header, the variables are the same as in background.csv</p> <p><em><strong>FILE 4:</strong></em> grass_create_forest_rasters_from_las.sh<br> A shell script used to convert LiDAR files to raster maps of forest structure with GRASS 7.</p> <p><em><strong>FILE 5:</strong></em> lidar_coverage.png<br> A map showing the extent of LiDAR data available for Central Finland when we did the analyses.</p> <p><em><strong>FILE 6:</strong></em> maxent_model_run_product.sh<br> A shell script used to fit the maximum entropy model to predict the locations of conservation-area-like forests in Central Finland.</p> <p><em><strong>FILE 7:</strong></em> projection_product.csv<br> The results of the maxent model in a comma separated file. The first row has the variable names: x,y,product_fit. x and y are coordinates in the CRS ETRS-TM35FIN (EPSG:3067). product_fit is "the probablility that this 18*18 meter grid cell is old-growth conservation area".</p> <p><em><strong>FILE 8:</strong></em> README<br> A file with a description of the dataset in human-readable form.</p> <p><strong>VALIDATION FILES</strong><br> The data in these files was collected to validate the results of the aforementioned maxent model. The data were collected in a hierarchical sampling scheme: six randomly determinded unintersecting 9 km * 9 km landscape windows were chosen for sampling. From each window, three samples were taken. One sample from conservation areas, one sample from the "best" 10 % of forests as determined by the maxent model excluding conservation areas and one random sample. Not all windows contained conservation areas, and not all areas were accessible (islands, for example). In addition a few areas were skipped due to time constraints.</p> <p>The sampled points are identified by their lanscape window (suuralue), their sample (otos) and their sample number (mittauspiste).</p> <p><em><strong>FILE 9:</strong></em> validation_felled.csv<br> A comma separated list of those points that were not measured because they were felled.</p> <p><em><strong>FILE 10:</strong></em> validation_gps_results_2016-09-07.csv<br> A list of gps coordinates for all the sample points. product_fit is the value of the geographically closest prediction from the maxent model described above.</p> <p><em><strong>FILE 11:</strong></em> validation_lying_deadwood_transects_2016-08-30.csv<br> A comma separated file with data from deadwood transects. From each validation point, three 30 m long transects were made with 120 degree angles between them, and all lying deadwood more than 2 cm in diameter were measured. For some validation points, there were geographical obstructions which prevented the full 90 m of transect being surveyed, this is also recorded in the data. Each row holds measurements from one lying trunk.<br> </p> <p><em><strong>FILE 12:</strong></em> validation_relascope_2016-08-30.csv<br> Relascope measurements from the validation points. Each row is measurements for one species from one validation point. Dead and alive trees are counted separately.<br> </p> <p><strong>MORE INFORMATION</strong></p> <p>For more in-depth descritions of the files, read the file named README.<br> For some auxilliary files and information, check our old hackathon repository on github: https://github.com/Koalha/bdm_hackathon</p>
Research data supporting "Synthesis of hetero-bifunctional, end-capped oligo-EDOT derivatives"
<p>Raw research data supporting the paper "Synthesis of hetero-bifunctional, end-capped olido-EDOT derivatives", Chem, Volume 2, Issue 1, p125–138, 12 January 2017 by C. Spicer <em>et al</em>.</p>
Flow cytometry data from human iPSC-derived macrophages
<p>Human induced pluripotent cells (iPSCs) were obtained from the HipSci project (http://www.hipsci.org) and differentiated into macrophages using an established protocol (van Wilgenburg, 2013). The genotype_id column of the flow_sample_metadata.txt file contains the canonical HipSci iPSC line name from which the macrophages were differentiated.</p> <p><strong>Data acquisition</strong></p> <p>We used flow cytometry to measure the cell surface expression of three canonical macrophage markers: CD14, CD16 (FCGR3A/FCGR3B) and CD206 (MRC1). Macrophages were cultured in 10 cm tissue-culture treated plates and detached from the plates by incubation in 6 mg/ml lidocaine-PBS solution (Sigma L5647) for 30 minutes followed by gentle scraping. From each cell line we harvested between 300,000-500,000 cells. Detached cells were washed in media, centrifuged at 1200 rpm for 5 minutes and resuspended in flow cytometry buffer (2% BSA, 0.001% EDTA in D-PBS) and split into two wells of a 96-well plate. Nonspecific antibody binding sites were blocked by incubating cells with Human TruStain FcX (Biolegend) for 45 minutes and washing with flow cytometry buffer. Half of the cells were stained for 1 hour with the PE-isotype control (BD 555749) antibody. The other half of the cells were co-stained for 1 hour with following three antibodies: CD14-Pacific Blue (BD 558121), CD16-PE (BD 555407), CD206-APC (BD 550889). After staining, the cells were washed three times. Resuspended cells were filtered through cell-strainer cap tubes (BD 352235) and measured on the BD LSRFortessa Cell Analyzer.</p>
Identification of significant KLH-derived peptide - Fig. S2
<p>Supplemental figure 2 (S2) of the manuscript “Surface LAMP-2 is an endocytic receptor that diverts antigen internalized by human dendritic cells into highly immunogenic exosomes” by Dario A. Leone et al. (Journal of Immunology). </p> <p>ProPresent® antigen presentation assay from ProImmune was used here to identify potential differences in the presentation of immunogenic regions in Keyhole Limpet Hemocyanin (KLH), compared to KLH conjugated to anti-LAMP2 antibody (H4B4*KLH). The peptide eluted from HLA-DR of MoDC isolated from four different donors were identified using mass spectrometry (LCMSMS)-based analysis in order to identify the putative immunogenic peptides from KLH and two endogenous protein – myeloperoxidase(MPO) and heat shock protein 70 (HSc70). </p>
Differential gene expression in iPSC-derived macrophages after IFNg stimulation and Salmonella infection
<p>We used likelihood ratio test implemented in DESeq2 v1.10.0 (test = “LRT”) to test if a model that allowed different mean expression in each condition explained the data better than a null model assuming the same mean expression across conditions. See the manuscript for more details: http://www.biorxiv.org/content/early/2017/05/18/102392 .</p> <p>We used the following commands in DESeq2:<br> #Run DESeq2<br> dds = DESeq2::DESeqDataSetFromMatrix(combined_expression_data_filtered$counts, design, ~condition_name) <br> dds = DESeq2::DESeq(dds, test = "LRT", reduced = ~ 1)</p> <p>#Extract differentially expressed genes in each condition<br> ifng_genes = results(dds, contrast=c("condition_name","IFNg","naive")) <br> sl1344_genes = results(dds, contrast=c("condition_name","SL1344","naive")) <br> ifng_sl1344_genes = results(dds, contrast=c("condition_name","IFNg_SL1344","naive"))</p>
Research data supporting "Sequence-Dependent Self-Assembly and Structural Diversity of Islet Amyloid Polypeptide-Derived β-Sheet Fibrils"
<p>Research data supporting the publication:</p> <p>Wang, S.-T. et al., 2017, Sequence-Dependent Self-Assembly and Structural Diversity of Islet Amyloid Polypeptide-Derived β-Sheet Fibrils, ACS Nano, http://dx.doi.org/10.1021/acsnano.7b02325</p>
Global scale leaf broadband optical properties derived from CliMA Land and associated CESM simulations
<p>Leaf level broadband reflectance and transmittance computed from leaf traits.</p> <ul> <li>clm_refl_tran_1m_weighted.nc: monthly data (144*96 pixels)</li> <li>surfdata_CMIP6_fluspect_v3.nc: surface data to run CESM (144*96 pixels)</li> </ul> <p>Global scale simulation results</p> <ul> <li>research_data_coupled_future_v2.nc: CESM coupled future simulations</li> <li>research_data_coupled_history_v2.nc: CESM coupled historical simulations</li> <li>research_data_uncoupled_history_v2.nc: CESM uncoupled future simulations</li> <li>research_data_uncoupled_ssp_v2.nc: CESM uncoupled SSP245 and SSP585 simulations</li> </ul> <p>Code changes</p> <ul> <li>SurfaceAlbedoMod.F90: modified CLM module</li> <li>Julia-and-Python-Code.tar.gz: code used for processing the data and plot the figures</li> </ul>
Discovery of microsized RNA-derived RNAs and polypeptides in human cells
<p>This repository comprises the predicted sequences for msdRs and msdPs, main source/raw data, and scripts for msdR/msdP prediction. Refer to the AAA_README.pdf for details.</p>
Comparative Analysis of Anthraquinone and Chalcone Derivatives-Based Virtual Combinatorial Library. A Cheminformatics "Proof-of-Concept" Study
<p>This computational “proof-of-concept” study illustrated the combinatorial approach used to explain how the selected natural products' structures undergo molecular diversity analysis. A virtual combinatorial library (1.6M) based on 20 anthraquinones and 24 chalcones were enumerated. The resulting compounds were optimized to the near drug-likeness properties and the physicochemical descriptors were calculated for all datasets including FDA, Non-FDA, and natural products (NPs) datasets from ZINC 15. UMAP and principal component analysis (PCA) were applied to compare and represent the chemical space coverage of each dataset. Subsequently, the Laplacian score, and Gini coefficient, were applied to delineate feature selection, and selectivity among properties respectively. Finally, we demonstrated the diversity between the datasets by employing Murcko’s, and central scaffolds systems, calculated three fingerprint descriptors, and analyzed their diversity by PCA and self-organizing maps (SOM). The optimized enumeration resulted in 1,610,268 compounds with NP-Likeness, and synthetic feasibility mean scores close to FDA, Non-FDA, and NPs datasets. The overlap between the chemical space of 1.6M was more prominent with NPs. Laplacian score has prioritized NP-likeness and hydrogen bond acceptor properties (1.0 and 0.923) respectively, while the Gini coefficient showed that all properties have selective effects on datasets (0.81 to 0.93). Scaffold and fingerprint diversity indicated that the descending order for the tested datasets was FDA, Non-FDA, NPs, 1.6M. Virtual combinatorial libraries based on NPs can be considered as a source of the combinatorial compound with NP-likeness properties. Furthermore, measuring molecular diversity is supposed to be performed by different methods to allow for comparison and better judgment. </p> <p>This link provides an illustration of the whole virtual combinatorial library using the TMAP algorithm in addition to the complete dataset. TMAP is a recent algorithm applied to visualize ultra-large high-dimensional chemical libraries for structures and physicochemical properties (Probst & Reymond, 2020). This approach creates and distributes intuitive tree representations of big data sets with arbitrary dimensionality in the order of 10<sup>7</sup>.</p> <p><strong>To visualize the whole library of compounds, download the "index(2).rar", then extract the index.html that pop-up in the WinRAR application.</strong></p>
Can accurate demographic information about people who use prescription medications non-medically be derived from Twitter?
<p>This archive contains over 3 billion Tweet IDs associated with the paper:<br>"Can accurate demographic information about people who use prescription medications non-medically be derived from Twitter?"</p> <p>The data provides:<br>X (Twitter) IDs of posts included in the study. The IDs can be used to retrieve the original posts via the Twitter API. Posts removed by the original subscribers or whose visibilities are no longer public cannot be retrieved by the poster. </p> <p>Full citation:<br>Yang YC, Al-Garadi MA, Love JS, Cooper HLF, Perrone J, Sarker A. Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter? Proc Natl Acad Sci U S A. 2023 Feb 21;120(8):e2207391120. doi: 10.1073/pnas.2207391120. Epub 2023 Feb 14. PMID: 36787355; PMCID: PMC9974473.</p> <p>Python scripts related to the analysis are available as supplementary material with the paper. </p> <p>Contact: <br>Abeed Sarker<br>abeed@dbmi.emory.edu</p> <p>Funding:<br>National Institute on Drug Abuse (R01DA057599).</p>
ECMWF ERA interim derived atmospheric mass, moisture and energy budget products
<p>As observations and atmospheric reanalyses have improved, the diagnostics that can be computed with confidence also increase. Accordingly, a new formulation of the energetics of the atmosphere is laid out, with a view to advancing diagnostic studies of Earth's energy budget and flows. It is utilized to produce assessments of the vertically integrated divergences in both the atmosphere and ocean. Careful conservation of mass is required, with special attention given to the hydrological cycle and redistribution of mass associated with precipitation and evaporation, and a new method for ensuring this is developed. It guarantees that the atmospheric divergence is associated with moisture and precipitation, unlike previous methods. A new term, identified as associated with the enthalpy of precipitation, is included in a preliminary way. It is sensitive to the formulation, and the use of temperature in degrees Celsius instead of Kelvin greatly reduces errors and produces the extra term with values up to about 65 W/m2. New results for 2000 to 2017 are presented for the vertical-mean and annual-mean diabatic atmospheric heating, atmospheric moistening, and total atmospheric energy divergence. Results for the atmospheric divergence are combined with top-of-atmosphere radiation observations to deduce total surface energy fluxes.</p> <p>These data files are monthly and span from 1979 to 2017, smoothed at T-106 resolution. The data format is NetCDF. A full dataset description is available at https://journals.ametsoc.org/view/journals/clim/31/16/jcli-d-17-0838.1.xml</p>
CLDF dataset derived from Kitchen et al.'s "Bayesian phylogenetic analysis of Semitic languages" from 2009
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Andrew Kitchen, Christopher Ehret, Shiferaw Assefa, Connie J. Mulligan. Proc. R. Soc. B 2009 -; DOI: 10.1098/rspb.2009.0408. Published 29 April 2009</p> </blockquote>
A Versioned Literature Corpus derived from Biodiversity Heritage Library hash://md5/b3cd9de0685deeebf57a5d225e59c10f
<p>THIS DESCRIPTION IS A WORK IN PROGRESS, THE CONTENT OF THIS VERSIONED CORPUS IS FINAL.</p> <p>Biodiversity Heritage Library (BHL, https://biodiversitylibrary.org) contains hundreds of thousands of digital works related to biodiversity. This publications contains a versioned snapshot of work metadata and the digital signatures of their associated pdfs as seen in period 2025-03-26/2025-06-25 . </p>
Derived-ECVs for Case Studies (maps)
<p>Climate maps (raster layers .tif) of derived-ecvs with a spatial resolution of 5.5 km (1 km for Azores) obtained by statistically downscaling a set of CMIP6 simulations for different IPCC climate scenarios (historical, SSP1-2.6, SSP2-4.5, SSP5-8.5) and time horizons (reference, short time-horizon, medium time-horizon, long time-horizon). Data are representative of specific climate normals (yearly averaged values) and created by RethinkAction.</p> <p>We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.</p> <p>Moreover, we acknowledge the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) to provide access to CMIP6, CERRA, ERA5 and ERA5-Land data:</p> <ul> <li>Copernicus Climate Change Service, Climate Data Store, (2021): CMIP6 climate projections. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.c866074c.</li> <li>Schimanke S., Ridal M., Le Moigne P., Berggren L., Undén P., Randriamampianina R., Andrea U., Bazile E., Bertelsen A., Brousseau P., Dahlgren P., Edvinsson L., El Said A., Glinton M., Hopsch S., Isaksson L., Mladek R., Olsson E., Verrelle A., Wang Z.Q., (2021): CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.622a565a</li> <li>Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D.,Thépaut, J-N. (2023): ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.adbb2d47</li> <li>Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac</li> </ul> <p>Acknowledgement also to:</p> <ul> <li>DRAAC, 2023, Regional climate data provided by the Regional Ditectorate for the Environment and Climate Change of the Regional Autonomous Government of Azores (<a href="https://urldefense.com/v3/__https:/portal.azores.gov.pt/en/web/draac__;!!D9dNQwwGXtA!TAB9_FXZEEA4K_6AkmoIqX-krFMSiGcKRY--rOpV9psI98vjxa-sLAZQYR1s0G1fFmBrENoHHpZCdvP0s67vzss$" target="_blank" rel="noopener">https://portal.azores.gov.pt/en/web/draac</a>)</li> <li>SRAA\CCIAM, 2017. Programa Regional de Alterações Climáticas (PRAC), Secretaria Regional do Ambiente e Ação Climática (SRAA) of the Governo dos Açores, Climate Change Impacts, Adaptation and Modelling (CCIAM) of the Faculdade de Ciências da Universidade de Lisboa (FCUL), <a href="https://urldefense.com/v3/__https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search*/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1__;Iw!!D9dNQwwGXtA!SmILhnS0zICNt1ZcxuQ0VPP7VxtFeSEdLt4chAw8y5tsdlWqsgkyt9kESGhRu-00ZQqakzH36tvV-_DcQI7jGo-lOg$" target="_blank" rel="noopener">https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search#/metadata/8804acd9-9d0f-40fb-bc2e-e4dff8c2b4b1</a></li> </ul> <p>This v2 includes metadata.</p>
Data and Code: Host-derived organic acids enable gut colonization of the honey bee symbiont Snodgrassella alvi
<p>Raw data and codes underlying the CFU count, qPCR, metabolomics, and NanoSIMS data for the paper "Host-derived organic acids enable gut colonization of the honey bee symbiont Snodgrassella alvi". Data is subdivided by main figure in the paper. Additionally, raw GC-MS datafiles (.cdf) are provided in separate folders. </p>
Approximations of derivatives by finite differences
<p>As supplementary material of the paper, it follows many of the approximations of derivatives by finite differences in PDF and text format, following the table model proposed in the paper to store the finite difference equations.</p>
Chemoselective Lipase-Catalyzed Synthesis of Amido Derivatives from 5-Hydroxymethylfurfurylamine
<p>The acylations of furfurylamine and 5-hydroxymethylfurfurylamine (HMFA) have been studied finding immobilized <i>Candida antarctica</i> lipase B (CALB) as an ideal biocatalyst. CALB was used immobilized on two different supports (Novozyme 435 and EziG-CALB), with the polymer-coated controlled porosity glass carrier material from EnginZyme being an excellent carrier to yield an active and stable enzymatic preparation for the acylation of the primary amine group. The amount of the acyl donor in the reaction was a key factor to achieve the mono- and chemoselective N-protection of HMFA with large excess of ethyl acetate leading to the formation of the N,O-diacetylated product. Thus, a series of 16 nonactivated esters were used to selectively modify the amine group of HMFA, obtaining 9 hydroxy amides under mild reaction conditions and with quantitative yields through chromatography-free transformations. The influence of substrate concentration was studied, resulting in complete conversions in all cases after 22 h (100–1000 mM). Excellent results were observed at 100 and 200 mM of HMFA, while higher concentrations led to longer reaction times and, to some extent, the formation of the diacetylated product (up to 7% after 22 h at 1 M). After this optimization, a metric analysis was performed to confirm the high sustainability of the presented process (<i>E</i>-factor of 1.1 excluding solvents) upon intensification of the biotransformation to 1 g at 200 mM HMFA concentration. The possibility of obtaining orthogonally protected HMFA-derived amido esters has been achieved through a clean and sequential one-pot process using EziG-CALB, which involved the use of ethyl methoxy acetate as the nonactivated ester for N-acylation and the activated vinyl acetate for O-protection.</p>
Characterization of a loss-of-function NAPB mutation in monozygotic triplets affected with epilepsy and autism using cortical neurons from proband-derived and CRISPR-corrected iPSC lines. Author names and affiliations
<p>RNA-seq data of matured cortical neurons (8-weeks old) derived from induced pluripoent stem cells (iPSC). There are three replicates (Rep1, Rep2, Rep3) for each sample with Forwad read (R1_001.fastq.gz) and reverse read (R2_001.fastq.gz).</p> <p>CtrlF: Control Father sample</p> <p>CtrlM: Control mother sample</p> <p>NDD_01: Proband sample</p> <p>NDD_04: Proband sample</p> <p>NDD_05: Proband sample</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.