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111,247 results for “cells”
Annona squamosa Leaf Extract Inhibit Migration of Human Cervical Cancer Cells Through MMP-9 Expression
<p> Figure 1. a.<em>Annona squamosa</em> leaf . b.Simplicia powder of <em>Annona squamosa</em> leaves</p> <p>Figure 2. <em>Annona squamosa</em> leaves ethanol extract.</p> <p>Figure 3. FTIR spectrophotometer results of acetogenin compounds of<em> </em><em>Annona squamosa</em> leaves extract</p> <p>Figure 4. The cytotoxic test of HeLa cells at 24 hours. The combination of ASL (<em>Annona squamosa</em> leaf Extract) 12.5 mg/ml + cisplatin was very effective compared with a single therapy. *<em>P</em> < 0.05Figure 4. The cytotoxic test of HeLa cells at 24 hours. The combination of ASL (<em>Annona squamosa</em> leaf Extract) 12.5 mg/ml + cisplatin was very effective compared with a single therapy. *<em>P</em> < 0.05</p> <p>Figure 5. The percentage of living cells of HeLa cells were cultured with different concentrations of <em>Annona squamosa</em> leaf extract.</p> <p>Figure 6. The combination therapy of ASL with cisplatin reduced the expressions of MMP-9 in HeLa cells. a. A significant concentration for cytotoxicity was a concentration of 12.5 mg/mL ASL + 5 μg/mL Cisplatin. b. The number of MMP-9 positive cells. *<em>P< </em>0.005.</p> <p>Figure 7. The combination therapy of ASL and Cisplatin inhibit cell migration. a. HeLa cells were treated with single cisplatin or in combination with ASL 12.5; 25, 50, and a single dose of ASL 75 mg/mL. b. Percentage area of cells undergoing migration. *<em>P</em><0.005.</p> <p> </p> <p> </p>
The cellular response to extracellular vesicles is dependent on their cell source and dose
<p><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">Extracellular </span><span class="NormalTextRun SCXW24798733 BCX0">vesicles</span> <span class="NormalTextRun SCXW24798733 BCX0">(EV) </span><span class="NormalTextRun SCXW24798733 BCX0">have been </span><span class="NormalTextRun SCXW24798733 BCX0">established</span><span class="NormalTextRun SCXW24798733 BCX0"> to play important roles in cell-cell communication and have </span><span class="NormalTextRun SCXW24798733 BCX0">shown promise as therapeutic agents</span><span class="NormalTextRun SCXW24798733 BCX0">.</span><span class="NormalTextRun SCXW24798733 BCX0"> However</span><span class="NormalTextRun SCXW24798733 BCX0">, </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">we still lack a</span><span class="NormalTextRun SCXW24798733 BCX0"> basic</span><span class="NormalTextRun SCXW24798733 BCX0"> understanding of</span></span><span class="TextRun SCXW24798733 BCX0"> <span class="NormalTextRun SCXW24798733 BCX0">how cells respond </span><span class="NormalTextRun SCXW24798733 BCX0">upon exposure to </span><span class="NormalTextRun SCXW24798733 BCX0">EVs from different cell sources at </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">var</span><span class="NormalTextRun SCXW24798733 BCX0">ious</span> </span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">doses. </span><span class="NormalTextRun SCXW24798733 BCX0">Thus</span><span class="NormalTextRun SCXW24798733 BCX0">, </span><span class="NormalTextRun SCXW24798733 BCX0">we treated fibroblasts with EVs from twelve different cell </span><span class="NormalTextRun SCXW24798733 BCX0">sourc</span><span class="NormalTextRun SCXW24798733 BCX0">es at doses between </span><span class="NormalTextRun SCXW24798733 BCX0">2</span><span class="NormalTextRun SCXW24798733 BCX0">0</span><span class="NormalTextRun SCXW24798733 BCX0"> and </span><span class="NormalTextRun SCXW24798733 BCX0">2</span><span class="NormalTextRun SCXW24798733 BCX0">00,000 per cell, </span><span class="NormalTextRun SCXW24798733 BCX0">a</span><span class="NormalTextRun SCXW24798733 BCX0">nalyzed </span><span class="NormalTextRun SCXW24798733 BCX0">their transcript</span><span class="NormalTextRun SCXW24798733 BCX0">i</span><span class="NormalTextRun SCXW24798733 BCX0">onal effects, </span><span class="NormalTextRun SCXW24798733 BCX0">and functionally confirmed the findings</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> in various cell types</span><span class="NormalTextRun SCXW24798733 BCX0"> <em>in vitro</em></span><span class="NormalTextRun SCXW24798733 BCX0">,</span><span class="NormalTextRun SCXW24798733 BCX0"> and <em>in vivo</em> using single-cell RNA-sequencing</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Unbiased g</span><span class="NormalTextRun SCXW24798733 BCX0">lobal</span><span class="NormalTextRun SCXW24798733 BCX0"> analysis revealed EV dose to have </span><span class="NormalTextRun SCXW24798733 BCX0">a more significant effect than cell source, </span><span class="NormalTextRun SCXW24798733 BCX0">such that </span><span class="NormalTextRun SCXW24798733 BCX0">high doses downregulat</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span><span class="NormalTextRun SCXW24798733 BCX0"> exocytosis and upregulat</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span> <span class="NormalTextRun SCXW24798733 BCX0">lysozomal</span><span class="NormalTextRun SCXW24798733 BCX0"> act</span><span class="NormalTextRun SCXW24798733 BCX0">ivity. </span><span class="NormalTextRun SCXW24798733 BCX0">However, </span><span class="NormalTextRun SCXW24798733 BCX0">EV cell source-specific responses were </span><span class="NormalTextRun SCXW24798733 BCX0">observed</span><span class="NormalTextRun SCXW24798733 BCX0"> at low doses</span><span class="NormalTextRun SCXW24798733 BCX0">,</span><span class="NormalTextRun SCXW24798733 BCX0"> and </span><span class="NormalTextRun SCXW24798733 BCX0">these </span><span class="NormalTextRun SCXW24798733 BCX0">reflected the </span><span class="NormalTextRun SCXW24798733 BCX0">activities </span><span class="NormalTextRun SCXW24798733 BCX0">of the</span><span class="NormalTextRun SCXW24798733 BCX0"> EV</span><span class="NormalTextRun SCXW24798733 BCX0">'</span><span class="NormalTextRun SCXW24798733 BCX0">s</span><span class="NormalTextRun SCXW24798733 BCX0"> source cell</span><span class="NormalTextRun SCXW24798733 BCX0">s</span><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Finally, </span><span class="NormalTextRun SCXW24798733 BCX0">we </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">assess</span><span class="NormalTextRun SCXW24798733 BCX0">ed</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> EV</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">-derived</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0"> transcript abundance </span><span class="NormalTextRun SCXW24798733 BCX0">and foun</span><span class="NormalTextRun SCXW24798733 BCX0">d that immune cell</span><span class="NormalTextRun SCXW24798733 BCX0">-derived</span><span class="NormalTextRun SCXW24798733 BCX0"> EVs were </span><span class="NormalTextRun SCXW24798733 BCX0">most </span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">associated with</span> <span class="NormalTextRun SCXW24798733 BCX0">recipient</span><span class="NormalTextRun SCXW24798733 BCX0"> cells</span></span><span class="TextRun SCXW24798733 BCX0"><span class="NormalTextRun SCXW24798733 BCX0">. </span><span class="NormalTextRun SCXW24798733 BCX0">Together, t</span><span class="NormalTextRun SCXW24798733 BCX0">his study </span><span class="NormalTextRun SCXW24798733 BCX0">provides</span><span class="NormalTextRun SCXW24798733 BCX0"> important insight into the </span><span class="NormalTextRun SCXW24798733 BCX0">cellular response to EVs.</span></span></p>
Lattice kinetic Monte Carlo model to simulate RNA polymerase II clusters during stem cell differentiation
<p>This data set includes Python scripts (numerical simulation and analysis) and already generated simulation data for RNA polymerase II clusters during stem cell differentiation. It includes the whole data to recreate panels.</p>
Data from: HIV-1 capsid stability enables inositol phosphate-independent infection of target cells and promotes integration into genes
<p>The mature HIV-1 capsid is stabilized by host and viral determinants. The capsid protein CA binds to the cellular metabolites inositol hexakisphosphate (IP6) and its precursor inositol (1, 3, 4, 5, 6) pentakisphosphate (IP5) to stabilize the mature capsid. In target cells, capsid destabilization by the antiviral compounds lenacapavir and PF74 reveals an HIV-1 infectivity defect due to IP5/IP6 (IP5/6) depletion. To test whether intrinsic HIV-1 capsid stability and/ or host factor binding determines HIV-1 insensitivity to IP5/6 depletion, a panel of CA mutants was assayed for infection of IP5/6-depleted T cells and wildtype cells. Four CA mutants with unstable capsids exhibited dependence on host IP5/6 for infection and reverse transcription (RTN). Adaptation of one such mutant, Q219A, by spread in culture resulted in Vpu truncation and a capsid three-fold interface mutation, T200I. T200I increased intrinsic capsid stability as determined by <em>in vitro</em> uncoating of purified cores and partially reversed the IP5/6-dependence in target cells for each of the four CA mutants. T200I further rescued the changes to lenacapavir sensitivity associated with the parental mutation. The premature dissolution of the capsid caused by the IP5/6-dependent mutations imparted a unique defect in integration targeting that was rescued by T200I. Collectively, these results demonstrate that T200I restored other capsid functions after RTN for the panel of mutants. Thus, the hyperstable T200I mutation stabilized the instability defects imparted by the parental IP5/6-dependent CA mutation. The contribution of Vpu truncation to mutant adaptation was linked to BST-2 antagonization, suggesting that cell-to-cell transfer promoted replication of the mutants. We conclude that interactions at the three-fold interface are adaptable, key mediators of capsid stability in target cells and are able to antagonize even severe capsid instability to promote infection.</p>
Wound Healing and Fluorescence Analyzes of Theranekron D6 AppliedAML-12 and HepG2 cells
<p>This file includes original jpeg files of wound closure area calculation of AML-12 and HepG2 cells and fluorescence microscopy photos of TD6 applied AML-12 and HepG2 cells uniquely.</p>
Additional raw data in `Cell-type-specific co-expression inference from single cell RNA-sequencing data'.
<p>This repository holds the additional raw data used to generate figures in the publication "<strong><em>Cell-type-specific co-expression inference from single cell RNA-sequencing data</em></strong>" (preprint version: <a href="http://source%20code%20repo%20for%20%60cell-type-specific%20co-expression%20inference%20from%20single%20cell%20rna-sequencing%20data%27./">https://www.biorxiv.org/content/10.1101/2022.12.13.520181v1</a>).</p> <p>Table of contents:</p> <ul> <li>Figure_1B.rds: <ul> <li>raw data of Figure 1B </li> <li>co-expression estimates of 500*499/2 gene pairs across 100 replicates for 7 methods under two settings of sequencing detph variations</li> </ul> </li> <li>Supplementary_Figure_1B.rds: <ul> <li>raw data of Supplementary Figure 1B </li> <li>co-expression estimates of 500*499/2 gene pairs across 100 replicates for 7 methods under two settings of sequencing detph variations</li> </ul> </li> <li>Supplementary_Figure_2.rds: <ul> <li>raw data of Supplementary Figure 2 </li> <li>empirical power evaluated for 4999 gene pairs and 6 methods</li> </ul> </li> <li>Figure_3B.rds: <ul> <li>raw data of Figure 3B</li> <li>co-expression estimates of a network of 500 genes for 9 methods across 100 replicates</li> </ul> </li> <li>Additional_Raw_Data.xlsx <ul> <li>raw data of Figure 3A: (geometric mean expression levels, co-expression estimates) for 4999 gene pairs and 11 methods</li> <li>raw data of Figure 3C: running times for 11 methods</li> <li>raw data of Supplementary Figure 3: (geometric mean expression levels, co-expression estimates) for 4999 gene pairs and 11 methods under two settings of sequencing detph variations</li> </ul> </li> </ul>
Data from: Three-dimensional nanoimaging of fuel cell catalyst layers
<p>The folders contain data and code source files associated with the article "Three-dimensional nanoimaging of fuel cell catalyst layers" published in Nature Catalysis, 6 (2023) 383-391</p> <p>Content:<br> - Data.zip: contains raw and processed data (reconstructed, denoised, segmented, thickness distributions) for samples LSC7 and HSC7. Data is organized to enable the reproduction of training models for denoising and segmentation using the notebooks in "Code and Scripts.zip".<br> - Code and Scripts.zip: contains jupyter notebooks for training and application of the segmentation models and for analysis of the segmented reconstructions; FIJI/imageJ script for semi-manual alignment of tilt-series</p>
Dataset - Fast mechanical and biochemical cell wall dynamics underlie plant nutation
<p>Dataset and codes (Python and Matlab) used to produce the figures in the article "Fast mechanical and biochemical cell wall dynamics underlie plant nutation".</p>
Epithelial Micro-Invasion Events by Streptococcus pneumoniae Drives Unique Epithelial Cell Responses
<p>RNA Sequencing dataset for Weight et al Manuscript.</p>
Imaging Data for: Enabling oxygen-controlled microfluidic cultures for spatiotemporal microbial single-cell analysis
<p>This dataset contains the microfluidic microscopy time-lapse data for the publication <a href="https://www.frontiersin.org/articles/10.3389/fmicb.2023.1198170/">"Enabling oxygen-controlled microfluidic cultures for spatiotemporal microbial single-cell analysis"</a>.</p> <p>The imaging data is recorded as raw 16-bit tif-stacks. The sequences <span>17406 - 17410 and 17411 - </span><span>17415 contain the aerobic and anaerobic conditions, respectively. For details about cultivation conditions and image processing please have a look into our <a href="http://www.frontiersin.org/articles/10.3389/fmicb.2023.1198170/">paper</a> or the public code repository <a href="https://github.com/JuBiotech/Supplement-to-Kasahara-et-al.-2023a">Supplement-to-Kasahara-et-al.-2023a</a>.</span></p>
Data for "Spatial consistency of cell growth direction during organ morphogenesis requires CELLULOSE-SYNTHASE INTERACTIVE1"
<p>This is the data associated with the following publication : "Spatial consistency of cell growth direction during organ morphogenesis requires CELLULOSE-SYNTHASE INTERACTIVE1"</p>
Microscopy-based assessment of RNA polymerase II clusters during differentiation of cultured mouse embryonic stem cells
<p>This repository contains the data and MatLab analysis scripts of the analysis of RNA polymerase II clusters over the course of differentiation of cultured mouse embryonic stem cells (mESCs). The cells were induced towards differentiation by either withdrawal of lineage-inhibiting factors (-LIF) or by RHB treatment. Both treatments were carried out in duplicate in independent experiments. Time course data were obtained by collection of cells at 3, 6, 12, 24, and 48 hours following the beginning of induction. Control data from unindexed cells were obtained at 24 and 48 hours. Cells were cultured, treated, collected, and fixed at University Medical Center Göttingen by Yomna Gohar, Priya Kumar, and Carmelo Ferrai. Fixed cells were fluorescently labeled and microscopy images were recorded and analyzed at Karlsruhe Institute of Technology by Lennart Hilbert. </p> <p>To analyse date data, the raw image data are first extracted into MatLab-native files using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/MultiPosition_extraction_nd2.m">MultiPosition_extraction_nd2.m</a> script. The actual analysis is then carried out using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ClusterAnalysis.m">ClusterAnalysis.m</a> script. Example microscopy images were produced using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ExampleImages.m">ExampleImages.m</a> script. The extracted data can be reviewed using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ReviewExtractedStacks.m">ReviewExtractedStacks.m</a> script.</p> <p>This is the main repository, containing the image analysis scripts alongside the links to the raw image data used in the analysis. The raw data are too large to be stored within this single repository, and therefore can be found at the following additional addresses.</p> <p>Differentiation by withdrawal of lineage-inhibiting factors (-LIF): <a href="https://doi.org/10.5281/zenodo.8013281">10.5281/zenodo.8013281</a></p> <p>Differentiation with addition of RHB for neuronal fate induction (RHB): <a href="https://doi.org/10.5281/zenodo.8013307">10.5281/zenodo.8013307</a></p>
Rational Modification of Human Gut Microbial Metabolites by Dietary Resistant Starch in Patients After Allogeneic Hematopoietic Stem Cell Transplantation: A Prospective Feasibility Study
<p>We conducted a prospective longitudinal feasibility study in patients undergoing allo-HCT for hematological malignancies to test the hypothesis that defined and consistent administration of resistant starch will rationally modify intestinal microbiota dependent metabolites, particularly the short chain fatty acids (SCFA), such as butyrate. Ten adults undergoing human leukocyte antigen-matched, related-donor myeloablative allo-HCT were enrolled and received resistant potato starch (RPS) daily from day -7 to day 100 after allo-HCT. </p>
Long read isoforms with A-to-I edits for H1975 cell line
<p>FLAIR2 was used to determine isoform models sequenced from H1975 cells using R2C2 cDNA nanopore sequencing. RNA sequence variants observed in the data were called with longshot and integrated into FLAIR2 isoform models.</p>
Data for: A Modular Double Electrode Flow Cell with Exchangeable Generator and Detector Electrodes
<p>Raw data and processed data shown in figures of the publication titled:</p> <p>"A Modular Double Electrode Flow Cell with Exchangeable Generator and Detector Electrodes"</p> <p>DOI: <a href="https://doi.org/10.1002/celc.202300126">10.1002/celc.202300126</a></p> <p>by</p> <p>Frederik J. Stender<sup>[a]</sup>, Keisuke Obata<sup>[b]</sup>, Max Baumung<sup>[a,c]</sup>, Fatwa F. Abdi<sup>[b]</sup>, Marcel Risch<sup>[a,c]</sup></p> <p>[a] Frederik Johannes Stender, Max Baumung, Dr. Marcel Risch<br> Institut für Material Physik<br> Georg-August-Universität Göttingen<br> Friedrich-Hund-Platz 1, 37085 Göttingen<br> E-mail: mrisch@material.physik.uni-goettingen.de</p> <p>[b] Dr. Keisuke Obata, Dr. Fatwa Firdaus Abdi<br> Institut für Solare Brennstoffe<br> Helmholtz-Zentrum Berlin für Materialien und Energie GmbH<br> Hahn-Meitner-Platz 1, 14109 Berlin</p> <p>[c] Dr. Marcel Risch<br> Nachwuchsgruppe Gestaltung des Sauerstoffentwicklungsmechanismus<br> Helmholtz-Zentrum Berlin für Materialien und Energie GmbH<br> Hahn-Meitner-Platz 1, 14109 Berlin<br> E-mail: marcel.risch@helmholtz-berlin.de</p>
Single cell analysis of human mesenchymal stem cells
<p>This dataset including the RDS files, including meta data, labeled assays, and reduction map information in order to ensure the reproducibility of the scRNA-seq data of human MSCs.</p> <p>The research "Multi-omics analysis of human mesenchymal stem cells shows cell aging that alters immunomodulatory activity through the downregulation of PD-L1" has been published on Nature Communications (https://doi.org/10.1038/s41467-023-39958-5).</p>
snATAC-seq and snRNA-seq in the chromatin landscape of healthy and injured cell types in the human kidney
<p>Isolated nuclei were immediately processed using the Chromium Next GEM Single Cell Multiome ATAC + Gene Expression (v1.0) kit, following the step-by-step protocol provided online [https://dx.doi.org/10.17504/protocols.io.5qpvoby69l4o/v2].<br>The RNA and ATAC libraries were separately sequenced on the NovaSeq 6000 system (Illumina) using the NovaSeq Control Software versions 1.7.0 and 1.7.5. Sample demultiplexing, barcode processing, gene expression quantification, and open chromatin peak quantification were performed using the Cell Ranger Arc software (version 2.0.0) with the GRCh38 (hg38) reference genome. </p> <p>Published in: <span><span>DOI: </span> <a href="https://doi.org/10.1038/s41467-023-44467-6" target="_blank" rel="noopener"> 10.1038/s41467-023-44467-6 </a> </span></p>
[Data S10] Microbiota dictate T cell clonal selection to promote graft-vs-host disease after stem cell transplantation
<p>Data S10. 10x genomics sequencing data files for Figure 5. Matrix file "sample_filtered_feature_bc_matrix.h5" and V(D)J annotations "filtered_contig_annotations.csv" are included below. Accompanying code can be found at https://github.com/acyeh-lab/2023/tree/main/scseq.</p>
Preprocessed dataset of the Spatially Resolved Single-cell Translatomics at Molecular Resolution
<p>Here are the pre-processed image datasets of RIBOmap included in "<strong>Spatially Resolved Single-cell Translatomics at Molecular Resolution</strong>" from Zeng et al. Please refer to the README file for more detailed information. </p> <p> </p> <p><strong>Abstract</strong></p> <p>The precise control of mRNA translation is a crucial step in post-transcriptional gene regulation of cellular physiology. However, it remains a major challenge to systematically study mRNA translation at the transcriptomic scale with spatial and single-cell resolution. Here, we report the development of RIBOmap, a three-dimensional (3D) in situ profiling method to detect mRNA translation of thousands of genes simultaneously in intact cells and tissues. By applying RIBOmap to 981 genes in HeLa cells, we revealed a remarkable dependency of translation on cell-cycle stages and subcellular localization. Furthermore, we profiled single-cell translatomes of 5,413 genes in adult mouse brain tissues yielding a spatial cell atlas of 119,173 cells. The pairwise spatial mapping of single-cell translatome and transcriptome in two adjacent mouse brain slices revealed cell-type and brain-region-dependent translational regulation and suggested a translation remodeling during oligodendrocyte lineage maturation. The spatial translatome profiling detected widespread patterns of localized translation in neuronal and glial cells in intact brain tissue networks. Together, RIBOmap presents the first spatially resolved single-cell translatomics technology, accelerating our understanding of protein synthesis in the context of subcellular architecture, cell types, and tissue anatomy.</p>
Inferring phenotypes of single cells based on the expression profiles of phenotype-associated marker genes in bulks and single cells
<p>The datasets analysed in the manuscript "Inferring phenotypes of single cells based on the expression profiles of phenotype-associated marker genes in bulks and single cells".</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.