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3,696 results for “Reference”
RirC3: Rhizophagus irregularis reference genome and annotation
<p>Reference genome assembly of <em>Rhizophagus irregularis</em> isolate C3, made with PacBio Sequel II SMRT sequencing, and polished with Illumina reads. Annotation was produced with FunAnnotate.</p>
LMAS Test Dataset - NIBSC Gut DNA Reference
<p>The twenty bacterial replicons of the National Institute for <a href="https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-020-00856-3">Biological Standards and Control (NIBSC) Gut Community Standards</a> were used as reference. It includes the following strains:</p> <table> <thead> <tr> <th>Species</th> <th>Culture collection number</th> <th>Accession numbers</th> <th>Status</th> <th>Gut-Mix-RR Coverage (x)</th> <th>Gut-HiLo-RR Coverage (x)</th> </tr> </thead> <tbody> <tr> <td>Akkermansia muciniphila</td> <td>DSM 22959</td> <td>NC_010655</td> <td>Complete genome</td> <td>33.33</td> <td>0.94</td> </tr> <tr> <td>Alistipes finegoldii</td> <td>DSM 17242</td> <td>NC_018011</td> <td>Complete genome</td> <td>16.94</td> <td>4.85</td> </tr> <tr> <td>Anaerostipes hadrus</td> <td>DSM 3319</td> <td>NZ_KB290627</td> <td>Complete genome</td> <td>24.04</td> <td>6.89</td> </tr> <tr> <td>Bacteroides thetaiotaomicron</td> <td>DSM 2079</td> <td>NC_004663</td> <td>Complete genome</td> <td>5.99</td> <td>17.19</td> </tr> <tr> <td>Bacteroides uniformis</td> <td>DSM 6597</td> <td>GCF_000154205</td> <td>Scaffold</td> <td>10.81</td> <td>3.10</td> </tr> <tr> <td>Bifidobacterium longum subsp. infantis</td> <td>DSM 20088</td> <td>NC_011593</td> <td>Complete genome</td> <td>29.52</td> <td>84.63</td> </tr> <tr> <td>Bifidobacterium longum subsp. longum</td> <td>DSM 20219</td> <td>GCF_900104835</td> <td>Contig</td> <td>40.19</td> <td>115.10</td> </tr> <tr> <td>Blautia wexlerae</td> <td>DSM 19850</td> <td>GCF_000484655</td> <td>Scaffold</td> <td>11.68</td> <td>0.34</td> </tr> <tr> <td>Clostridium butyricum</td> <td>DSM 10702</td> <td>GCF_000409755</td> <td>Contig</td> <td>11.21</td> <td>32.09</td> </tr> <tr> <td>Collinsella aerofaciens</td> <td>DSM 13712</td> <td>GCF_902501475</td> <td>Contig</td> <td>44.03</td> <td>12.61</td> </tr> <tr> <td>Escherichia coli</td> <td>DSM 1103</td> <td>CP009072</td> <td>Complete genome</td> <td>8.86</td> <td>25.34</td> </tr> <tr> <td>Eubacterium hallii</td> <td>DSM 3353</td> <td>GCF_000173975</td> <td>Contig</td> <td>21.79</td> <td>6.25</td> </tr> <tr> <td>Faecalibacterium prausnitzii</td> <td>DSM 17677</td> <td>NZ_CP048437</td> <td>Complete genome</td> <td>24.66</td> <td>0.72</td> </tr> <tr> <td>Lactobacillus gasseri</td> <td>DSM 20077</td> <td>NC_008530</td> <td>Complete genome</td> <td>66.00</td> <td>1.91</td> </tr> <tr> <td>Parabacteroides distasonis</td> <td>DSM 20701</td> <td>NC_009615</td> <td>Complete genome</td> <td>10.20</td> <td>29.26</td> </tr> <tr> <td>Prevotella copri</td> <td>DSM 18205</td> <td>GCF_000157935</td> <td>Scaffold</td> <td>19.23</td> <td>55.11</td> </tr> <tr> <td>Prevotella melaninogenica</td> <td>DSM 7089</td> <td>NC_014370,1 and NC_014371,1</td> <td>2 Chromosomes</td> <td>23.49</td> <td>6.73</td> </tr> <tr> <td>Roseburia hominis</td> <td>DSM 16839</td> <td>NC_015977</td> <td>Complete genome</td> <td>18.31</td> <td>5.24</td> </tr> <tr> <td>Roseburia intestinalis</td> <td>DSM 14610</td> <td>NZ_LR027880</td> <td>Complete genome</td> <td>12.04</td> <td>0.34</td> </tr> <tr> <td>Ruminococcus gauvreauii</td> <td>DSM 19829</td> <td>GCF_000425525</td> <td>Scaffold</td> <td>14.04</td> <td>0.41</td> </tr> </tbody> </table> <p>The raw sequence data of the mock communities, with an even and staggered distribution of species, is available at:</p> <ul> <li><a href="https://www.ebi.ac.uk/ena/browser/view/SRR11487941?show=reads">SRR11487941</a> - Gut-Mix-RR Illumina MiSeq sample</li> <li><a href="https://www.ebi.ac.uk/ena/browser/view/SRR11487935?show=reads">SRR11487935</a> - Gut-Mix-HiLo Illumina MiSeq sample</li> </ul>
A chromosomal-scale reference genome of the New World Screwworm, Cochliomyia hominivorax
<p>The New World Screwworm, <em>Cochliomyia hominivorax</em> (Calliphoridae), is the most important myiasis-causing species in America. Screwworm myiasis is a zoonosis that can cause severe lesions in livestock, domesticated and wild animals, and occasionally in people. Beyond the sanitary problems associated with this species, these infestations negatively impact economic sectors, such as the cattle industry.</p> <p>Here, we present a chromosome-scale assembly of <em>C</em>. <em>hominivorax</em>'s genome, organized in 6 chromosome-length and 515 unplaced scaffolds spanning 534 Mb. There was a clear correspondence between the <em>D</em>. <em>melanogaster</em> linkage groups A-E and the chromosomal-scale scaffolds. Chromosome Quotient (CQ) analysis identified a single scaffold from the X chromosome that contains most of the orthologs of genes that are on the <em>D</em>. <em>melanogaster</em> fourth chromosome (linkage group F or dot chromosome). CQ analysis also identified potential X and Y unplaced scaffolds and genes. Y-linkage for selected regions was confirmed by PCR with male and female DNA. Some of the long chromosome-scale scaffolds include Y-linked sequences, suggesting misassembly of these regions. These resources will provide a basis for future studies aiming at understanding the biology and evolution of this devastating obligate parasite.</p>
Reference genes for quantitative Arabidopsis single molecule RNA fluorescence in situ hybridization
Abstract Subcellular mRNA quantities and spatial distributions are fundamental for driving gene regulatory programmes. Single molecule RNA fluorescence in situ hybridization (smFISH) uses fluorescent probes to label individual mRNA molecules, thereby facilitating both localization and quantitative studies. Validated reference mRNAs function as positive controls and are required for calibration. Here we present selection criteria for the first set of Arabidopsis smFISH reference genes. Following sequence and transcript data assessments, four mRNA probe sets were selected for imaging. Transcript counts per cell, correlations with cell size, and corrected fluorescence intensities were all calculated for comparison. In addition to validating reference probe sets, we present sample preparation steps that can retain green fluorescent protein fluorescence, thereby providing a method for simultaneous RNA and protein detection. In summary, our reference gene analyses, modified protocol, and simplified quantification method together provide a firm foundation for future quantitative single molecule RNA studies in Arabidopsis root apical meristem cells.
Data and GenX analysis for "Liquid Helium as a reference may provide clarity for some neutron reflectometry experiments"
<p>Data and GenX analysis for "Liquid Helium as a reference may provide clarity for some neutron reflectometry experiments"</p>
Revised transcript annotations for GRCh38 reference genome and Ensembl v87.
<p>Custom transcript annotations generated using the reviseAnnotations package. </p> <p>Reference genome: GRCh38<br> Ensembl version: 87</p> <p>See the GitHub page of reviseAnnotations for more details:<br> https://github.com/kauralasoo/reviseAnnotations</p>
Revised transcript annotations for GRCh37 (hg19) reference genome and Ensembl v90.
<p>Custom transcript annotations generated using the reviseAnnotations package. </p> <p>Reference genome: GRCh37<br> Ensembl version: 90</p> <p>See the GitHub page of reviseAnnotations for more details:<br> https://github.com/kauralasoo/reviseAnnotations</p>
Reference libraries for execute the Annopipe software
<p>Libraries needed to run the software ANNOPIPE, available in the following link:</p> <p>https://github.com/celiosantosjr/annopipe</p>
16S and ITS Reference Annotation Databases
<p>Unite is a mirror of Unite 7.2 mothur release.</p> <p>Silvamod and GreenGenes datasets represent a mirror of the extracted data files used for:</p> <blockquote> <p>Lanzén A , Jørgensen SL, Huson D, Gorfer M, Grindhaug SH, Jonassen I, Øvreås L, Urich T (2012) CREST - Classification Resources for Environmental Sequence Tags, <em>PLoS ONE</em> <strong>7</strong>:e49334</p> </blockquote>
ATLAS reference databases
<p>Pre-formatted databases for use with ATLAS assembly and annotation protocol.</p>
OBR running reference data and software
<p>These files contain the data/software that was obtained/used in a research project using an<br> Optical Backscatter Reflectometer (OBR) to obtain strain data of curing epoxy.</p> <p>ATTENTION: The archive that contains the raw-measurement files is several GB big. It may take a while to open it.</p> <p>The results are to be published and the journal/article-title will be added as soon as possible.</p> <p>Please, see the README-Files for additional information.</p> <p>The software is published under the GNU General Public License, version 3.<br> For the data the stated license is valid.</p>
Enhancing Full Waveform Inversion of Field GPR Data: A Source-Independent Approach with Dynamic Reference Selection via SE-Wave-U-Net
<p>Data presented in the manuscript titled 'Enhancing Full Waveform Inversion of Field GPR Data: A Source-Independent Approach with Dynamic Reference Selection via SE-Wave-U-Net'</p>
Data from: A 3D geometric morphometric analysis of the bovid distal humerus, with special reference to Rusingoryx atopocranion (Pleistocene, Eastern Africa)
<p>The family Bovidae [Mammalia: Artiodactyla] is speciose and has extant representatives on every continent, forming key components of mammal communities. For these reasons, bovids are ideal candidates for studies of ecomorphology. In particular, the morphology of the bovid humerus has been identified as highly related to functional variables such as body mass and habitat. This study investigates the functional morphology of the bovid distal humerus in isolation due to its increased likelihood of preservation in the fossil record, and the resulting opportunity for better understanding the ecomorphology of extinct bovids. A landmark scheme of 30 landmarks was used to capture the 3D distal humerus morphology in 111 extant bovid specimens. We find that the distal humerus has identifiable morphologies associated with body mass, habitat preference, and tribe affiliation, and that some characteristics are shared between high body mass bovids and those living on hard, flat terrain which is likely due to the high stress on the bone in both cases. We directly apply our findings regarding extant bovids to the extinct alcelaphine bovid, <em>Rusingoryx</em> <em>atopocranion</em> from the mid to late Pleistocene (>33-45 ka) Lake Victoria region of Kenya. This species is known for some peculiar morphologies including a domed cranium with hollow nasal crests, and having small hooves for a bovid of its size. Another interesting aspect of <em>Rusingoryx</em>'s skeletal morphology which has not been addressed is an unusual protrusion on the lateral epicondyle of the distal humerus. Despite considerable individual variation in the <em>Rusingoryx</em> specimens, we find evidence to support its historical assignment to the tribe Alcelaphini, and that it likely preferred open grassland habitats, which is consistent with independent reconstructions of the paleoenvironment. We also provide the most accurate body mass estimate for <em>Rusingoryx</em> to date, based on distal humerus centroid size. Overall, we are able to conclude that the distal humerus in extant bovids is highly informative regarding body mass, habitat preference and tribe, and that this can be applied directly to a fossil taxon with promising results.</p>
Experiment resources for "Quality of Binaural Rendering From Baffled Microphone Arrays Evaluated Without an Explicit Reference"
<div>This data set contains the following resources to reproduce the listening experiment and statistical analysis of the referenced manuscript:</div> <div> <ul> <li>The <em>binaural room impulse responses</em> (<strong>BRIR</strong>s) of all listening conditions presented in the perceptual experiment.</li> <li>The tools to create the listening test infrastructure, including <em>Pure Data</em> (<strong>Pd</strong>) patches and configuration files for the <em>SoundScape Renderer</em> (<strong>SSR</strong>) and <em>graphical user interface</em> (<strong>GUI</strong>).</li> <li>The raw response data as gathered from the experiment subjects.</li> <li>The R and Stan scripts to perform the statistical analysis and generate the resulting plots and tables.</li> </ul> </div> <div> <p> </p> <p>The archive contains the following components described below.</p> <p>Directory "dependencies/":</p> <ul> <li>Matlab, R, Stan, and Pd functions that are utilized in the code and experimental setup</li> <li>Additional dependencies of available open-source projects may be required for certain code functions. If so, the source and setup process for the necessary dependencies are documented in the file header.</li> </ul> </div> <div> <p>Directory "plots/4_Equalization/":</p> <ul> <li>Plots of all available headphone equalization filters as generated by the following Matlab scripts.</li> </ul> <p>Directory "plots/8_User_study/":</p> <ul> <li>Plots of the raw and analyzed experimental results as generated by the following Matlab and R scripts.</li> </ul> </div> <div> <p>Directory "resources/BRIR_auralization/":</p> <ul> <li>Audio files with static binaural auralizations of all listening conditions presented in the perceptual experiment as generated by the following Matlab scripts.</li> <li>The files in "Kemar_HRTF_sofa_N44_adjusted" do not include a headphone equalization.</li> <li>The files in "Kemar_HRTF_sofa_N44_adjusted+Sennheiser_HD650_lin" include the equalization for the <em>Sennheiser HD650</em> headphones employed in the listening experiment. The files are identical to the annotated <a href="http://www.ta.chalmers.se/research/audio-technology-group/audio-examples/jaes-2024a/" target="_blank" rel="noopener">listening examples</a> published for the manuscript.</li> </ul> <p>Directory "resources/BRIR_rendered/":</p> <ul> <li>BRIRs and rendering parameters of all listening conditions presented in the perceptual experiment as generated from the associated <a href="../doi/10.5281/zenodo.8206570" target="_blank" rel="noopener">data set</a> and <a href="https://github.com/HaHeho/baffled-arrays-to-binaural/releases/tag/v2024.JAES" target="_blank" rel="noopener">rendering code</a>.</li> <li>Scene configuration files for the SSR with all listening conditions presented in the perceptual experiment as generated from the following Matlab scripts.</li> </ul> <p>Directory "resources/HPCF_KEMAR/":</p> <ul> <li>Impulse responses of equalization filters for various headphones on the G.R.A.S KEMAR acoustic dummy head as measured for this experiment.</li> </ul> <p>Directory "resources/User_study/":</p> <ul> <li>Various resources for the listening experiment.</li> <li>The files in "Exp1_analysis" include intermediate and final statistical analysis results as generated from the following R scripts.</li> <li>"Exp1_config.json" contains the configuration of the study GUI with conditions presented in the listening experiment.</li> <li>"Exp1_Introduction.pdf" contains the instructions presented to the subjects at the start of the listening experiment.</li> <li>"Exp1_Part2_data_strings.xls" contains all subjects' raw perceptual response data gathered from the listening experiment.</li> <li>"Questionnaire.pdf" contains the questionnaire given to the subjects at the end of the listening experiment.</li> </ul> <p>Matlab script "x4_Gather_Headphone_Compensations.m":</p> <ul> <li>Generate plots of measured headphone compensation filters. Furthermore, the generated minimum phase filters and filters to yield a linear phase response from the headphones are extracted as separate WAV files.</li> </ul> </div> <div> <p>Matlab script "x6_Gather_SSR_Configurations.m":</p> <ul> <li>Collect several specified pre-rendered binaural room impulse response sets into an ASD file. The SSR can load this scene to present all gathered configurations in direct comparison with head tracking.</li> </ul> </div> <div> <p>Readme file "x6a_Normalize_SSR_Loudnesses.txt":</p> </div> <div> <div> <div> <ul> <li>Ideally, the rendering script would implement a measure to provide a reliable estimation of the binaural loudness of the rendered configuration. This could be used to normalize all stimuli levels. However, such a measure is currently not available or implemented.</li> <li>Therefore, tuning the stimuli loudness for the user study was performed beforehand by ear. The adjusted playback levels are set in a modified SSR configuration file for the listening experiment.</li> </ul> </div> <div> <p>Matlab script "x6_Gather_SSR_Configurations.m":</p> <ul> <li>Perform convolution of (rendered) binaural room impulse responses with a source audio signal. This is done for a specified selection of static head orientations and a continuous rotation over all horizontal head orientations.</li> <li>The resulting auralizations are published as <a href="http://www.ta.chalmers.se/research/audio-technology-group/audio-examples/jaes-2024a/">supplementary materials</a> to the manuscript.</li> </ul> <p>Shell script "x7_Start_Study_GUI.sh":</p> <ul> <li>Initialize all required components to perform the perceptual user study, including: <ul> <li>SSR to perform the real-time rendering of the BRIRs with head tracking</li> <li>SSR to extract head-tracking data (in case a Polhemus tracker is used)</li> <li>Pd to extract head-tracking data (in case a Supperware tracker is used)</li> <li>Pd to perform real-time convolution to apply headphone compensation</li> <li>Pd to receive OSC messages from the study GUI</li> <li>Pd to trigger audio file playback from received OSC messages</li> <li>Pd to translate OSC messages into FUDI messages for the SSR</li> <li>The GUI to be used by the participants and implement the study procedure</li> </ul> </li> <li>Some static configuration variables can be adjusted, whereas other parameters are chosen during script execution.</li> </ul> <p>Matlab script "x8_Gather_Study_Data.m":</p> <ul> <li>Transform the raw result data from the questionnaire (*.xls) and the study GUI (*.json) into a compact format (*.xls) that can be loaded to plot the raw data and imported by software for the subsequent statistical analysis.</li> <li>Note that this contains the responses from all subjects, whereas responses from the investigators must be excluded from the statistical analysis (which is implemented in the analysis scripts).</li> </ul> <p>Matlab script "x8a_Plot_Study_Data.m":</p> <ul> <li>Generate a set of violin plots to visualize the initial distribution of the raw perceptual data. The data is split by specified attributes and plotted separately for visual inspection.</li> <li>The data may also be transformed into ranks for a first distribution inspection. Note that implementing the ranking method, notably how ties are resolved, may differ from the technique employed in the statistical analysis.</li> <li>Note that this contains the responses from all subjects, whereas responses from the investigators must be excluded from the statistical analysis (which is implemented in the analysis scripts).</li> </ul> <p>R script "x8b_Analyze_Exp1_Data.R":</p> <ul> <li>Perform the statistical analysis by transforming the observed subject ratings into a predicted distribution of ranks using a hierarchical generalized linear regression model.</li> <li>Executing the statistical model may take some time due to the Bayesian framework employing Markov-chain Monte Carlo simulations.</li> <li>Data is exported at various intermediate steps to be loaded and visualized by the following R script.</li> </ul> <p>R markdown script "x8c_Plot_Exp1_Results.Rmd":</p> <ul> <li>Generate various plots and data tables of the observed data and the predicted results to visualize the distribution and influence of different analysis parameters.</li> <li>Some of the resulting plots were used in the manuscript.</li> <li>"x8c_Plot_Exp1_Results.html" conveniently summarizes all plots and data tables generated by "knitting" the R markdown script.</li> </ul> </div> </div> </div>
Data for: Raw count data, transcribed variant count data, and reference genomic annotation files for Boocock et al. 2024
<p>Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in <em>Saccharomyces cerevisiae</em> by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene <em>GPA1</em>, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.</p>
BOLD curated data and reference library
<ul> <li>BOLD_Public.05-Apr-2024.BAGS.d39fc06c483ea4a7252b6a4e203ca15c6ce4dd24.tsv - BAGS ranking of BIN x species combinations</li> <li>BOLD_Public.05-Apr-2024.3c74c5e91daa2ddccce41d38881edc2e242e9c81.tsv.gz - BCDM rated with curation pipeline</li> <li>refdb.fa - COI-5P records with BAGS=(A,B,C), rating=(1,2,3) with <a href="https://github.com/naturalis/galaxy-tool-BLAST">galaxy-tool-BLAST</a>-compliant full lineage</li> <li>families-for-curation.tar.gz - TSVs of families with BCDM records for manual curation</li> </ul>
Control panel created from 30-40 Nanopore or PacBio HiFi sequencing data from the Human Pangenome Reference Consortium
<p>This is control panel for <a href="https://github.com/friend1ws/nanomonsv">nanomonsv</a> software, which is expected to exclude many false positives as well as improve computational cost. This is made by aligning 30-40 Nanopore or PacBio HiFi sequencing data from Human Pangenome Reference Consortium (HPRC) to the GRCh38 or CHM13 reference genomes with <a href="https://github.com/lh3/minimap2">minimap2</a> version 2.24.</p> <p><strong>When you use these control panels and publish, do not forget to credit to <a href="https://humanpangenome.org/data-use-protocol/">HPRC</a>!</strong></p> <div> <div> <div> <p>Reference genomes:</p> <ul> <li>GRCh38: <a href="https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz">Download GRCh38</a></li> <li>CHM13: <a href="https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0_maskedY_rCRS.fa.gz">Download CHM13</a> <div> <div> <div> <div> </div> </div> </div> </div> </li> </ul> </div> </div> </div>
CO1 reference sequences dataset of the sedDNA Chironomidae study by Blattner et al. 2024
<p>This dataset contains the CO1 reference sequences used to identify the sedDNA metabarcoding reads in the study entitled "Sediment core DNA-Metabarcoding and chitinous remain identification: Integrating complementary methods to characterise Chironomidae biodiversity in lake sediment archives", which was submitted to Molecular Ecology Resources.</p>
Existing Urban Hyperspectral Reference Data
<p>This dataset supports the publication "Urban Hyperspectral Reference Data Availability and Reuse: State-of-the-Practice Review" DOI: 10.1111/phor.12508. The urban hyperspectral signatures of 9 pre-existing spectral libraries have been converted into .xlsx file formats and organized by material category. This reformatted and compiled dataset is uploaded to this open-source repository to promote FAIR (Findable, Accessible, Interoperable, Reusable) data principles and facilitate data preservation and reuse. </p>
S-LDSC reference annotations for CT-FM model (Kim et al., 2024 in prep.)
Open the record for dataset details and reuse information.
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.