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377 results for “Mass spectrometry”
Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome
<p>Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS metaproteomic measurements using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data highlighting specific needs to further improve DIA tools to enable analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising data collection strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.</p>
DATASET - Mass Spectrometry - Snake venom proteomics of Deinagkistrodon acutus
<p><strong>This DATASET collection includes the mass spectrometry files for shotgun proteomics venom investigation the sharp-nosed viper (<em>Deinagkistrodon acutus</em>) from China.</strong></p> <p><strong>Species list:</strong></p> <ol> <li>Deinagkistrodon acutus</li> </ol> <p><strong>Folders 01-02 - BOTTOM-UP SHOTGUN PROTEOMICS</strong>: The venom pool was investigated by the bottom-up shotgun (labled as SG) approach and in short: in-solution processed by DTT, IAC and finally o/n tryptic digested. Samples submitted to HPLC-MS/MS. Folders includes the MS and MS/MS spectra of Deinagkistrodon acutus. Files are included as RAW and MZML format in folder 01 and 02, respectively.</p> <p>Used instrument:</p> <p>Advion TriVersa NanoMate (Advion BioSciences) into an Orbitrap Eclipse Tribrid MS instrument (Thermo Fisher Scientific) with an UltiMate 3000RSLCnano system (Thermo Fisher Scientific) using 50 cm μPAC C18 column (Pharma Fluidics).</p> <p>Modifications: UNIMOD:4 - \"Iodoacetamide derivative.\"</p>
Mass spectrometry Imaging dataset for a study on fungicide application to tomato leaves - II
<p>The dataset uploaded here is in association to a manuscript in press by Ajith et al., titled, "Visualizing active fungicide formulation mobility in tomato leaves with Desorption Electrospray Ionisation Mass Spectrometry Imaging". This dataset contains .imzML files along with zipped .ibd files of mass spectrometry imaging data and .mzML format LC-MS data for a fungicide applicaion study on tomato leaves. DESI Imprint imaging data here is for tomato leaves applied with Azoxystrobin standard after 24 hours, 56 hours and a week after formulation application along with a blank leaf data with no Azoxystrobin application.</p> <table> <tbody> <tr> <td><strong>File name</strong></td> <td><strong>Time point</strong></td> </tr> <tr> <td>DTIM_Std_24h</td> <td>24h</td> </tr> <tr> <td>DTIM_Std_56h</td> <td>56h</td> </tr> <tr> <td>DTIM_Std_1week</td> <td>1 week</td> </tr> <tr> <td>DTIM_Blank</td> <td> No application</td> </tr> </tbody> </table> <p>This data upload contains a zipped LC-MS data folder (LC_mzML.7z). The details of the files, the time point of sampling and part of leaf is in the excel sheet uploaded along with the data (LC-MS_datanames.xls).</p> <p> </p>
Locality-sensitive hashing enables signal classification in high-throughput mass spectrometry raw data at scale
<p>Raw data of nanoLC-IMS-MS/MS (DDA-PASEF) from HeLa whole proteome digest. </p> <p>HeLa cells were lysed in a urea-based lysis buffer (7 M urea, 2 M thiourea, 5 mM dithiothreitol (DTT), 2% (w/v) CHAPS) assisted by sonication for 15 min at 4°C in high potency using a Bioruptor instrument (Diagenode). Proteins were digested with Trypsin using a filter-aided sample preparation (FASP) [Wisniewski <em>et al</em>., 2009] as previously detailed [Distler <em>et al</em>., 2016]. 200 ng of peptide digest were analyzed using a nanoElute UPLC coupled to a TimsTOF PRO MS (Bruker). Peptides injected directly in an Aurora 25 cm x 75 µm ID, 1.6 µm C18 column (Ionopticks) and separated using a 120 min. gradient method at 400 nL/min. Phase A consisted on water with 0.1% formic acid and phase B on acetonitrile with 0.1% formic acid. Sample was injected at 2% B, lineally increasing to 20% B at 90 min., 35% B at 105 min., 95% at 115 min. and hold at 95% until 120 min. before re-equilibrating the column at 2%B. The MS was operated in DDA-PASEF mode [Meier <em>et al</em>., 2018], scanning from 100 to 1700 m/z at the MS dimension and 0.60 to 1.60 1/k0 at the IMS dimension with a 100 ms TIMS ramp. Each 1.17 sec MS cycle comprised one MS1 and 10 MS2 PASEF ramps (frames). The source was operated at 1600 V, with dry gas at 3 L/min and 200°C, without nanoBooster gas. The instrument was operated using Compass Hystar version 5.1 and timsControl version 1.1.15 (Bruker).</p>
mass spectrometry metabolomic analysis of Drosophila head extracts: 3 genotypes (control, RNAi Opa1 in muscle, RNAi Marf in muscle), 2 ages (30 days, 65 days)
<p>RNAi of the Drosophila mitochondrial fusion genes Opa1 and Marf (Mitofusin 2) in the muscle results in an extended lifespan. In order to detect metabolic changes in lipid in the neural tissue, we analysed the metabolome of fly heads by mass spectroscopy, comparing the two knock-down genotypes to a wild type control at two ages: 30 days (young flies) and 65 days (old flies).</p>
Dataset related to article "Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging"
<p><em>The .zip file contains raw data related to the article "Quantitative determination of niraparib and olaparib tumor distribution by mass spectrometry imaging", available from <a href="https://www.ijbs.com/v16p1363.htm">https://www.ijbs.com/v16p1363.htm</a>.</em></p> <ul> <li><em>The folder "<strong>fig 1 2 3 NIRA</strong>" contains raw data related to the experiments with niraparib presented in figures 1, 2 and 3 </em></li> <li><em>The folder "<strong>fig 1 2 3 OLA</strong>" contains raw data related to the experiments with olaparib presented in figures 1, 2 and 3 </em></li> <li><em>The folders "<strong>fig 4</strong>" and "<strong>fig 6</strong>" contain raw data related to figures 4 and 6, respectively.</em></li> </ul> <p><strong>For any additional information on how to read and reuse the dataset please contact Dr. Ubezio at paolo.ubezio@marionegri.it.</strong></p> <p> </p> <p><strong>ABSTRACT OF THE MANUSCRIPT:</strong></p> <p><strong>Rationale</strong>: Optimal intratumor distribution of an anticancer drug is fundamental to reach an active concentration in neoplastic cells, ensuring the therapeutic effect. Determination of drug concentration in tumor homogenates by LC-MS/MS gives important information about this issue but the spatial information gets lost. Targeted mass spectrometry imaging (MSI) has great potential to visualize drug distribution in the different areas of tumor sections, with good spatial resolution and superior specificity. MSI is rapidly evolving as a quantitative technique to measure the absolute drug concentration in each single pixel.</p> <p><strong>Methods</strong>: Different inorganic nanoparticles were tested as matrices to visualize the PARP inhibitors (PARPi) niraparib and olaparib. Normalization by deuterated internal standard and a custom preprocessing pipeline were applied to achieve a reliable single pixel quantification of the two drugs in human ovarian tumors from treated mice.</p> <p><strong>Results</strong>: A quantitative method to visualize niraparib and olaparib in tumor tissue of treated mice was set up and validated regarding precision, accuracy, linearity, repeatability and limit of detection. The different tumor penetration of the two drugs was visualized by MSI and confirmed by LC-MS/MS, indicating the homogeneous distribution and higher tumor exposure reached by niraparib compared to olaparib. On the other hand, niraparib distribution was heterogeneous in an ovarian tumor model overexpressing the multidrug resistance protein P-gp, a possible cause of resistance to PARPi.</p> <p><strong>Conclusions</strong>: The current work highlights for the first time quantitative distribution of PAPRi in tumor tissue. The different tumor distribution of niraparib and olaparib could have important clinical implications. These data confirm the validity of MSI for spatial quantitative measurement of drug distribution providing fundamental information for pharmacokinetic studies, drug discovery and the study of resistance mechanisms.</p>
Mass Spectrometry Datasets for "Highly synergistic combinations of nanobodies that target SARS-CoV-2 and are resistant to escape"
<p>This repository contains mass spectrometry raw datasets for the research paper "<strong><em>Highly synergistic combinations of nanobodies that target SARS-CoV-2 and are resistant to escape</em></strong>". An early version of the manuscript can be viewed on <a href="https://www.biorxiv.org/content/10.1101/2021.04.08.438911v1">bioRxiv</a>.</p> <p>The datasets include two parts:</p> <ol> <li>Identification of nanobodies targeting SARS-CoV-2 spikes.</li> <li>Chemical cross-linking of nanobody-spikes complexes.</li> </ol> <p>The included <strong>.raw</strong> files are Thermo Orbitrap Raw files, and can be assessed by various software such as <em>Thermo Xcalibur</em>, <em><a href="https://proteowizard.sourceforge.io/">ProteoWizard</a></em> and <em><a href="https://pypi.org/project/pymsfilereader/">pymsfilereader</a></em>.</p>
Discovery proteomics by mass spectrometry comparing secreted proteins from young and old mouse lung mesenchymal stromal cells
<p>Lung mesenchymal stromal cells (L-MSCs) were isolated from the young ( 3 months) and old (22-24 months) mice (N = 4 each) following collagenase digestion of the lungs and anchorage-dependent growth. Culture media was collected from young and old L-MSCs (10^6 cells) grown in culture for 24 hrs in serum-free condition. Culture media was then centrifuged to remove any cellular debris. Five (5) ml of supernatants were concentrated using 3kDa Molecular weight cut-off filters, and 10 micrograms of proteins were <span><span><span><span><span>run as multiple MW 1D PAGE fractions using a standard </span><span>GeLC</span><span> approach with a </span><span>nano</span><span>-HPLC in-line with a </span><span>Velos</span><span> Pro Orbitrap MS. </span></span></span></span></span><span><span><span><span><span>Individual data files were searched using </span><span>Sequest</span><span>, the results were then combined for each sample, followed by grouping, filtering, and quantifying by normalized spectral counts. </span></span></span></span></span></p> <p> </p>
Novel Insights into the Bioactive Metabolites of Macrocybe gigantea (Massee) Pegler & Lodge, a Wild Edible Macrofungi Using Gas Chromatography Mass Spectrometry (GC-MS) Combined with Chemoinformatics Approaches
<p><em>Macrocybe gigantea </em>(MG) is an edible mushroom and has multiple pharmacological activities such as antibacterial, antioxidant, and antitumor activities. However, only a few reports were available on the bioactive compounds and bioactivity of this mushroom. In this concern, the present study was aimed to explore the unique chemical diversity from the fruiting body of MG<em>. </em>The species identification was done accurately with morphological and molecular methods followed by mycochemical extraction in different solvent systems. The ethanolic extract of the fruiting body gave maximum yield and its Gas Chromatography-Mass Spectrometry (GC-MS) analysis was performed along with antibacterial activity and cell viability by MTT assay. The GC-MS analysis revealed 50 metabolites and further chemoinformatics analysis of these metabolites revealed their possible biological activities. In addition, the mushrooms' physico-chemical and mineral element analysis revealed the quality and authenticity of the species. Altogether, the current investigation gives a comprehensive overview of the bioactive metabolites of MG.</p>
Titanium dioxide nanoparticles assessment in seaweeds by single particle inductively coupled plasma – Mass spectrometry
<p>n this study, a first attempt for isolating and determining (characterising) background levels of <a href="https://www.sciencedirect.com/topics/chemistry/titanium-dioxide-nanoparticle">titanium dioxide nanoparticles</a> (TiO<sub>2</sub> NPs) in seaweed has been developed by using single particle inductively coupled plasma – mass spectrometry (SP-ICP-MS). Seaweeds were processed using an optimised <a href="https://www.sciencedirect.com/topics/chemistry/ultrasound-extraction">ultrasound assisted extraction</a> (UAE) procedure based on <a href="https://www.sciencedirect.com/topics/chemistry/tetramethylammonium-hydroxide">tetramethylammonium hydroxide</a> (TMAH) before dilution and SP-ICP-MS analysis. The effect of the TMAH percentage in the extracting solution, as well as the volume of extracting solution and <a href="https://www.sciencedirect.com/topics/chemistry/sonication">sonication</a> (extraction) time, has been fully assessed. Additional experiments also showed that TiO<sub>2</sub> NPs were quantitatively released from the seaweed matrix in one UAE step since the analysis of residues gave TiO<sub>2</sub> NPs concentrations lower than the limit of quantification (LOQ) of the method. Validation of the method with 50 and 100 nm TiO<sub>2</sub> NPs (10 μg L<sup>−1</sup> as Ti) showed good analytical recovery (115% and 112% for 50 and 100 nm TiO<sub>2</sub> NPs, respectively), and good reproducibility (2% for size and 16% for number of TiO<sub>2</sub> NPs). Experiments regarding TiO<sub>2</sub> NPs stability showed that the extracted NPs are stable since there were not changes on the number of TiO<sub>2</sub> NPs and TiO<sub>2</sub> NPs size distributions when exposing TiO<sub>2</sub> NPs standards to the optimised extractive conditions.</p>
Mass spectrometry-based aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol
<p>Dataset of Thoma et al. published at Atmospheric Measurements and Techniques:</p> <p>Mass spectrometry-based aerosolomics: a new approach to resolve sources, composition, and partitioning of secondary organic aerosol</p>
Data for: Oligonucleotide mapping via mass spectrometry to enable comprehensive primary structure characterization of an mRNA vaccine against SARS-CoV-2
<p>Oligonucleotide mapping via liquid chromatography mass spectrometry mass spectrometry (LC-MS/MS) was recently developed to support development of Comirnaty®, the world's first commercial mRNA vaccine which immunizes against the SARS-CoV-2 virus. Analogous to peptide mapping of therapeutic protein modalities, oligonucleotide mapping described here provides direct primary structure characterization of mRNA, through enzymatic digestion, accurate mass determinations, and optimized collisionally-induced fragmentation. Sample preparation for oligonucleotide mapping is a rapid, one-pot, one-enzyme digestion. The digest is analyzed via LC-MS/MS with an extended gradient and resulting data analysis employs semi-automated software. In a single method, oligonucleotide mapping readouts include a highly reproducible and completely annotated UV chromatogram with >98% sequence coverage and a microheterogeneity assessment of 5´ terminus capping and 3´ terminus poly(A) tail length. Oligonucleotide mapping was pivotal to ensure the quality, safety, and efficacy of mRNA vaccines by providing: confirmation of construct identity and primary structure and assessment of product comparability following manufacturing process changes. More broadly, this technique may be used to directly interrogate the primary structure of RNA molecules in general.</p>
Mass spectrometry- based biomarkers to detect prostate cancer: A multicentric study based on non- invasive urine collection without prior intervention
<p>These are datasets related to mass spectrometry proteomics analysis, in particular Capillary Electrophoresis coupled to Mass Spectrometery (CE-MS). CE-MS was employed to acquire proteomics profiles from 970 patients from two different clinical centers. with the aim to develop a biomarker model to detect Prostate Cancer. </p>
Trichoderma-Arabidopsis interaction by Ambient Ionization Mass Spectrometry
<p>Interaction between the plant <em>Arabidopsis thaliana</em> and the fungus <em>Trichoderma atroviride</em>.</p> <p>Three sample groups (<em>Arabidopsis thaliana</em>, <em>Trichoderma atroviride</em> and <em>Trichoderma-Arabidopsis</em> interaction) with 3 biological replicates were monitored for 10 days, resulting in 40 points. This experiment was focused on monitoring the kinetics of the volatile organic compound (VOC) 6-Pentyl-2H-Pyran-2-One (6-PP), a molecule produced by <em>Trichoderma</em> that helps to establish interaction with plants. More details and results are available in the publication written by Torres-Ortega et al. (DOI: <a href="https://doi.org/10.3390/metabo12121231">10.3390/metabo12121231</a>). </p> <p>Data were collected with custom 3D-printed Low-Temperature Plasma (DOI: <a href="https://doi.org/10.1021/acs.analchem.6b01019">10.1021/acs.analchem.6b01019</a>) ambient ionization source, coupled to an LCQ-fleet ion trap (Thermo Scientific, USA). Mass spectra were taken in full spectra at 50-500 <em>m/z</em> range, on profile mode. Each MS scan consists of 10 micros cans. Data was saved under the RAW property format of Thermo. To convert to mzML open format, Proteowizard was used.</p>
Genomically predicted theoretical protein mass database for mass spectrometry (GPMsDB) evaluation datasets
<p>These are datasets obtained for the evaluation of GPMsDB (genomically predicted protein mass database) and its toolkits (GPMsDB-tk/GPMsDB-dbtk). The following datasets are deposited.</p> <ul> <li>The genome sequences of the strains newly sequenced and added using GPMsDB-dbtk (genomes_added.zip)</li> <li>MALDI-TOF-MS peak lists obtained from reference bacterial and archaeal strains (MALDI_peaklists.zip)</li> <li>16S rRNA gene sequences of the faecal isolates (mice_isolates_16S_nanopore.zip)</li> <li>Metagenome-assembled genomes from mouse faeces (mice_MAGs.zip)</li> </ul>
Ultra-Accurate Correlation Between Precursor and Fragment Ions in Two-lDimensional Mass Spectrometry: Acetylated vs. Trimethylated Histone Peptides
<p>Two-dimensional mass spectrometry (2D MS) is a method<br> for tandem<br> mass spectrometry in which precursor and fragment ions are correlated<br> by manipulating ion radii rather than by ion isolation. A 2D mass<br> spectrum contains the fragmentation patterns of all analytes in a<br> sample, acquired in parallel. We report ultrahigh-resolution narrowband<br> 2D mass spectra of a mixture of two histone peptides with the same<br> sequence, one of which carries an acetylation and the other a trimethylation<br> (m/z 0.006 difference). We reduced<br> the distance between data points in the precursor ion dimension and<br> compared the accuracy of the precursor-fragment correlation with the<br> resolving power. We manage to perform label-free quantification on<br> the histone peptide mixture and show that precursor and fragment ions<br> can be accurately correlated even though the precursor ions are not<br> resolved. Finally, we show that increasing the resolution of a 2D<br> mass spectrum in the precursor ion dimension too far can lead to a<br> decline in the signal-to-noise ratio.</p>
Porcine cell-free system mass spectrometry compiled data sets
<p><span>The degradation of sperm-borne mitochondria after fertilization is a conserved event. This process known as post-fertilization sperm mitophagy, ensures exclusively maternal inheritance of the mitochondria-harbored mitochondrial DNA genome. This mitochondrial degradation is in part carried out by the ubiquitin proteasome system. In mammals, ubiquitin-binding pro-autophagic receptors such as SQSTM1 and GABARAP have also been shown to contribute to sperm mitophagy. These systems work in concert to ensure the timely degradation of the sperm-borne mitochondria after fertilization. We hypothesize that other receptors, cofactors, and substrates are involved in post-fertilization mitophagy. <span>Mass spectrometry was used in conjunction with a porcine cell-free system to identify other autophagic cofactors involved in post-fertilization sperm mitophagy. This porcine cell-free system is able to recapitulate early fertilization proteomic interactions. Altogether, 185 proteins were identified as statistically different between control and cell-free treated spermatozoa. Six of these proteins were further investigated, including MVP, PSMG2, PSMA3, FUNDC2, SAMM50, and BAG5. These proteins were phenotyped using porcine <em>in vitro </em>fertilization, cell imaging, proteomics, and the porcine cell-free system. The present data confirms the involvement of known mitophagy determinants in the regulation of mitochondrial inheritance and provides a master list of candidate mitophagy co-factors to validate in the future hypothesis-driven studies.</span></span></p>
MultiplexMS: A mass spectrometry-based multiplexing strategy for ultra-high-throughput analysis of complex mixtures
<p>Abstract: Throughput for chemical analysis of natural products mixtures has not kept pace with recent developments in genome sequencing technologies and laboratory automation for high-throughput screening, leading to a disconnect between chemical and biological profiling at the library scale that limits new molecule discovery. Here we report a new strategy for sample multiplexing that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. This strategy involves the analysis of pooled samples and subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using <em>in silico</em> experiments and demonstrated that the method has a high precision (>97%) for large, pooled samples (n = 30), particularly for infrequently occurring metabolites (n < 10) of relevance in drug discovery applications. Finally, we repeated a recently reported biological activity profiling study on 925 natural products extracts, leading to the rediscovery of all previously reported bioactive metabolites using just 5% of the previously required MS acquisition time. This new method is compatible with mass spectrometry data from any instrument vendor and is supported by an open-source software package available at <a href="https://github.com/liningtonlab/MultiplexMS">https://github.com/liningtonlab/MultiplexMS</a>.Throughput for chemical analysis of natural products mixtures has not kept pace with recent developments in genome sequencing technologies and laboratory automation for high-throughput screening, leading to a disconnect between chemical and biological profiling at the library scale that limits new molecule discovery. Here we report a new strategy for sample multiplexing that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. This strategy involves the analysis of pooled samples and subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using <em>in silico</em> experiments and demonstrated that the method has a high precision (>97%) for large, pooled samples (n = 30), particularly for infrequently occurring metabolites (n < 10) of relevance in drug discovery applications. Finally, we repeated a recently reported biological activity profiling study on 925 natural products extracts, leading to the rediscovery of all previously reported bioactive metabolites using just 5% of the previously required MS acquisition time. This new method is compatible with mass spectrometry data from any instrument vendor and is supported by an open-source software package available at <a href="https://github.com/liningtonlab/MultiplexMS">https://github.com/liningtonlab/MultiplexMS</a>.</p>
Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator
<p>Dataset related to Huu-Hien Huynh, Vincent Delatour, Maxence Derbez-Morin, Qinde Liu, Amandine Boeuf, and Joëlle Vinh, (2022) Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator. Anal. Chem. 2022, 94, 10, 4146–4154.</p>
Modeling flexible protein structure with AlphaFold2 and cross-linking mass spectrometry
<p>Ensembles of models predicted by AlphaFold for the proteins C3 (Complement component 3), luciferase and QBP (glutamine-binding periplasmic protein). Models interpolated between two conformations of C3, and luciferase are also included. This dataset is cited in the following paper: https://www.biorxiv.org/content/10.1101/2023.09.11.557128v1</p>
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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.