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111,247 results for “cells”

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zenodo48/100

PM_035426_B_Celles

File Name: PM_035426_B_Celles.jpg Sublocation: Celles-les-Dinant, L'Hermitage Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Abbaye (L'Hermitage Saint-Hadelin). L'église, les bâtiments et une statue. 19ème siècle ( ?). Description: Abbey (L'Hermitage Saint-Hadelin) The church, the buildings and a statue 19th century (?) Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Monuments, Namur, Neo-Romanesque, Romanesque, Styles Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

zenodo48/100

PM_035403_B_Celles

File Name: PM_035403_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Intérieur, la crypte Description: Parish church (Eglise Saint-Hadelin) Interior Crypt 7th century (?) Keywords: Belgium, Celles-les-Dinant (Houyet), Crypt, Cultural heritage, Europe, Houyet, Monuments, Namur, Romanesque, Styles Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

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PM_035385_B_Celles

File Name: PM_035385_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Vue de l'extérieur Description: Parish church (Eglise Saint-Hadelin) Exterior The tower 11th century (1040 ?) Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Monuments, Namur, Romanesque, Styles Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

zenodo48/100

PM_035419_B_Celles

File Name: PM_035419_B_Celles.jpg Sublocation: Celles-les-Dinant Location: Houyet Province: Namur Country: Belgium Header: L'Hermitage Saint-Hadelin. L'escalier ouvert. Description: L'Hermitage Saint-Hadelin The open staircase Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Namur Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

zenodo48/100

PM_035400_B_Celles

File Name: PM_035400_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Intérieur, fonts baptismaux Description: Parish church (Eglise Saint-Hadelin) Interior Font 14th century Detail A head Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Namur, Romanesque, Sculpture, Styles, Techniques Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

zenodo48/100

PM_035430_B_Celles

File Name: PM_035430_B_Celles.jpg Sublocation: Celles-les-Dinant, L'Hermitage Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Abbaye (L'Hermitage Saint-Hadelin). Façade ouest et entrée. 19ème siècle ( ?). Description: Abbey (L'Hermitage Saint-Hadelin) West facade and entrance 19th century (?) Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Monuments, Namur, Neo-Romanesque, Romanesque, Styles Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

zenodo48/100

PM_035397_B_Celles

File Name: PM_035397_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Intérieur, fonts baptismaux Description: Parish church (Eglise Saint-Hadelin) Interior Font 14th century Detail A head Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Namur, Romanesque, Sculpture, Styles, Techniques Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

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PM_035392_B_Celles

File Name: PM_035392_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Intérieur, fonts baptismaux Description: Parish church (Eglise Saint-Hadelin) Interior Font 14th century Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Namur, Romanesque, Sculpture, Styles, Techniques Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

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PM_035396_B_Celles

File Name: PM_035396_B_Celles.jpg Sublocation: Celles-les-Dinant, Eglise Saint-Hadelin Location: Houyet Province: Namur Country: Belgium Header: Intérieur, fonts baptismaux Description: Parish church (Eglise Saint-Hadelin) Interior Font 14th century Keywords: Belgium, Celles-les-Dinant (Houyet), Cultural heritage, Europe, Houyet, Namur, Romanesque, Sculpture, Styles, Techniques Author: Photo: Paul M.R. Maeyaert Copyright: Paul M.R. Maeyaert

opencc-by-sa-4.0Nov 2024View details →

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Inhibition of epithelial cell YAP-TEAD/LOX signaling attenuates pulmonary fibrosis "

<table> <tbody> <tr> <td> Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal disease characterized by excessive extracellular matrix (ECM) deposition. Current IPF therapies slow disease progression but do not stop or reverse it. The (myo)fibroblasts are thought to be the main cellular contributors to excessive ECM production in IPF. Here we report that fibrotic AT2 cells regulate production and crosslinking of ECM via the co-transcriptional activator YAP. YAP leads to increase expression of Lysyloxidase (LOX) and subsequent LOX mediated crosslinking by fibrotic AT2 cells. Pharmacological YAP inhibition reverses fibrotic AT2 cell reprogramming and LOX expression in experimental lung fibrosis in vivo and in human fibrotic tissue ex vivo. We thus identify YAP-TEAD/LOX inhibition in AT2 cells as a promising potential new therapy for IPF patients.  In </td> </tr> </tbody> </table>

opencc-by-4.0Nov 2024View details →

zenodo48/100

Training and test dataset of STED images of microtubules in fixed cells

Training and test dataset of microtubule used in the manuscript "Denoising diffusion models for high-resolution microscopy image restoration".

opencc-by-4.0Nov 2024View details →

zenodo48/100

Live-cell STED dataset of mitochondria containing ground truth and corresponding low intensity noisy images

The dataset was acquired as part of the manuscript "Denoising diffusion models for high-resolution microscopy image restoration". The dataset contains ground truth and low intensity STED images of mitochondria acquired in live U2-OS cells stably expressing TOM20 coupled to the dead mutant of HaloTag7 which was made fluorescent by using the exchangeable ligand Hy4 bound to the fluorophore SiR.

opencc-by-4.0Nov 2024View details →

zenodo48/100

Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture Prior

The datasets used in the paper "Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture Prior". A detailed description of these datasets is available at https://github.com/jaydu1/VITAE/tree/master/data.

opencc-by-4.0Dec 2020View details →

zenodo48/100

Clonal decomposition and DNA replication states defined by scaled single cell genome sequencing

OV2295 Tables ov2295_breakpoint_counts.csv.gz: Table of breakpoint counts per cell <ul> <li>prediction_id: identifier for the breakpoint</li> <li>cell_id: identifier for the cell</li> <li>read_count: number of reads</li> <li>library_id: identifier for the DNA library</li> <li>sample_id: identifier for the sequenced sample</li> <li>chromosome_1: chromosome of breakend 1</li> <li>strand_1: orientation of break end 1</li> <li>position_1: position of break end 1</li> <li>chromosome_2: chromosome of breakend 2</li> <li>strand_2: orientation of break end 2</li> <li>position_2: position of break end 2</li> </ul> ov2295_cell_cn.csv.gz: Table of cell specific copy number <ul> <li>cell_id: identifier for the cell</li> <li>sample_id: identifier for the sequenced sample</li> <li>library_id: identifier for the DNA library</li> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>reads: number of reads</li> <li>copy: raw normalized copy number</li> <li>state: copy number state</li> <li>gc: percent gc of the bin</li> <li>map: average mappability of the bin</li> </ul> ov2295_cell_metrics.csv.gz: Table of cell metrics <ul> <li>cell_id: identifier of the cell</li> <li>unpaired_mapped_reads: number of unpaired mapped reads</li> <li>paired_mapped_reads: number of mapped reads that were properly paired</li> <li>unpaired_duplicate_reads: number of unpaired duplicated reads</li> <li>paired_duplicate_reads: number of paired reads that were also marked as duplicate</li> <li>unmapped_reads: number of unmapped reads</li> <li>percent_duplicate_reads: percentage of duplicate reads</li> <li>estimated_library_size: scaled total number of mapped reads</li> <li>total_reads: total number of reads, regardless of mapping status</li> <li>total_mapped_reads: total number of mapped reads</li> <li>total_duplicate_reads: number of duplicate reads</li> <li>total_properly_paired: number of properly paired reads</li> <li>coverage_breadth: percentage of genome covered by some read</li> <li>coverage_depth: average reads per nucleotide position in the genome</li> <li>median_insert_size: median insert size between paired reads</li> <li>mean_insert_size: mean insert size between paired reads</li> <li>standard_deviation_insert_size: standard deviation of the insert size between paired reads</li> <li>index_sequence: index sequence of the adaptor sequence</li> <li>column: column of the cell on the nanowell chip</li> <li>img_col: column of the cell from the perspective of the microscope</li> <li>index_i5: id of the i5 index adapter sequence</li> <li>sample_type: type of the sample</li> <li>primer_i7: id of the i5 index primer sequence</li> <li>experimental_condition: experimental treatment of the cell, includes controls</li> <li>index_i7: id of the i7 index adapter sequence</li> <li>cell_call: living/dead classification of the cell based on staining usually, C1 == living, C2 == dead</li> <li>sample_id: name of the sample</li> <li>primer_i5: id of the i5 index primer sequence</li> <li>row: row of the cell on the nanowell chip</li> <li>library_id: identifier for the DNA library</li> <li>index: ignored</li> <li>multiplier: during parameter searching, the set [1..6] that was chosen</li> <li>MSRSI_non_integerness: median of segment residuals from segment integer copy number states</li> <li>MBRSI_dispersion_non_integerness: median of bin residuals from segment integer copy number states</li> <li>MBRSM_dispersion: median of bin residuals from segment median copy number values</li> <li>autocorrelation_hmmcopy: hmmcopy copy autocorrelation</li> <li>cv_hmmcopy: ignored</li> <li>empty_bins_hmmcopy: number of empty bins in hmmcopy</li> <li>mad_hmmcopy: median absolute deviation of hmmcopy copy</li> <li>mean_hmmcopy_reads_per_bin: mean reads per hmmcopy bin</li> <li>median_hmmcopy_reads_per_bin: median reads per hmmcopy bin</li> <li>std_hmmcopy_reads_per_bin: standard deviation value of reads in hmmcopy bins</li> <li>total_halfiness: summed halfiness penality score of the cell</li> <li>total_mapped_reads_hmmcopy: total mapped reads in all hmmcopy bins</li> <li>scaled_halfiness: summed scaled halfiness penalty score of the cell</li> <li>mean_state_mads: mean value for all median absolute deviation scores for each state</li> <li>mean_state_vars: variance value for all median absolute deviation scores for each state</li> <li>mad_neutral_state: median absolute deviation score of the neutral 2 copy state</li> <li>breakpoints: number of breakpoints, as indicated by state changes not at the ends of chromosomes</li> <li>mean_copy: mean hmmcopy copy value</li> <li>state_mode: the most commonly occuring state</li> <li>log_likelihood: hmmcopy log likelihood for the cell</li> <li>true_multiplier: the exact decimal value used to scale the copy number for segmentation</li> <li>order: order of the cell in the hierarchical clustering tree</li> <li>quality: random forest classifier proability score that cell is good</li> </ul> ov2295_clone_alleles.csv.gz: Table of clone specific allele data <ul> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>hap_label: haplotype block identifier</li> <li>clone_id: clone identifier</li> <li>allele_1_sum: number of reads for allele 1 of the haplotype block</li> <li>allele_2_sum: number of reads for allele 2 of the haplotype block</li> <li>total_counts_sum: total reads for the haplotype block</li> </ul> ov2295_clone_breakpoints.csv.gz: Table of breakpoints per clone for OV2295 samples. Columns: <ul> <li>prediction_id: identifier for the breakpoint</li> <li>chromosome_1: chromosome of breakend 1</li> <li>strand_1: orientation of break end 1</li> <li>position_1: position of break end 1</li> <li>chromosome_2: chromosome of breakend 2</li> <li>strand_2: orientation of break end 2</li> <li>position_2: position of break end 2</li> <li>clone_id: clone identifier</li> <li>read_count: number of reads</li> <li>is_present: presence=1, absent=0</li> </ul> ov2295_clone_clusters.csv.gz: Table of cell clusters as putative clones <ul> <li>cell_id: identifier for the cell</li> <li>clone_id: clone identifier</li> </ul> ov2295_clone_cn.csv.gz: Table of allele specific copy number per clone for OV2295 samples. Columns: <ul> <li>chr: chromosome of bin</li> <li>start: start of bin</li> <li>end: end of bin</li> <li>total_cn: HMMCopy predicted total copy number </li> <li>minor_cn: HMM predicted minor copy number </li> <li>major_cn: HMM predicted major copy number </li> <li>clone_id: clone identifier</li> </ul> ov2295_clone_snvs.csv.gz: Table of SNVs per clone for OV2295 samples.  Columns: <ul> <li>chrom: chromosome</li> <li>coord: genome position</li> <li>ref: reference nucleotide</li> <li>alt: alternate nucleotide</li> <li>clone_id: clone identifier</li> <li>ref_counts: number of reads at this position matching the reference nucleotide</li> <li>alt_counts: number of reads at this position matching the alternate nucleotide</li> <li>total_counts: total number of reads at this position</li> <li>is_present: presence=0, absent=1</li> <li>is_het: is heterozygous</li> <li>is_hom: is homozygous for the alternate</li> </ul> ov2295_nodes.csv.gz: Table of phylogenetic information for SNV evolution <ul> <li>variant_id: identifier for the SNV as chrom:coord:ref:alt</li> <li>node: node in the phylogenetic tree</li> <li>loss: probability the SNV was lost at this node</li> <li>origin: probability the SNV originated at this node</li> <li>presence: probability the SNV is present at this node</li> <li>ml_origin: binary indicator the SNV originated at this node</li> <li>ml_presence: binary indicator the SNV is present at this node</li> <li>ml_loss: binary indicator the SNV was lost at this node</li> </ul> ov2295_snv_counts.csv.gz: Table of SNV counts <ul> <li>chrom: chromosome</li> <li>coord: genome position</li> <li>ref: reference nucleotide</li> <li>alt: alternate nucleotide</li> <li>ref_counts: number of reads at this position matching the reference nucleotide</li> <li>alt_counts: number of reads at this position matching the alternate nucleotide</li> <li>cell_id: identifier for the cell</li> <li>total_counts: total number of reads at this position</li> <li>sample_id: identifier for the sequenced sample</li> </ul> ov2295_tree.pickle: Phylogenetic tree in python pickle format.  Requires installation of the stochastic dollo code at: https://bitbucket.org/dranew/dollo, version 0.4.2. Note the following sample mapping: ‘SA922’: ‘OV2295(R2)’, ‘SA921’: ‘TOV2295(R)’, ‘SA1090’: ‘OV2295’, Plots ov_supp_clone_allele_cn.png: Clone allele ratios for each OV2295 sample. ov_supp_clone_total_cn.png: Clone copy number for each OV2295 sample. ov_supp_sample_total_cn.png: Bulk copy number for each OV2295 sample. ov_supp_sample_allele_cn.png: Bulk allele ratios for each OV2295 sample.

opencc-by-4.0Sep 2019View details →

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bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses - Melanoma tutorial

Downsampled version of the melanoma dataset originally published by <a href="https://genome.cshlp.org/content/28/9/1353">Ho et al </a>(1). The dataset is composed by cells from the 451Lu cell line. There are two samples available: <table> <tbody> <tr> <td>Name</td> <td>Description</td> <td>R1/R2</td> </tr> <tr> <td>451LU</td> <td>Parental cell line</td> <td>2500K_451LU_L003_R*_001.fastq.gz</td> </tr> <tr> <td>451LUBR3</td> <td>Vemurafenib-resistant sample treated with targeted BRAF inhibitors</td> <td>500K_451LUBR3_L004_R*_001.fastq.gz</td> </tr> </tbody> </table> (1) Ho YJ, Anaparthy N, Molik D, et al. Single-cell RNA-seq analysis identifies markers of resistance to targeted BRAF inhibitors in melanoma cell populations. Genome Res. 2018;28(9):1353-1363. doi:10.1101/gr.234062.117

opencc-by-4.0Feb 2022View details →

zenodo48/100

Mechanical characterisation of the developing cell wall layers of tension wood fibres by Atomic Force Microscopy

This dataset corresponds to the Arnould et al. (2022) paper (available at https://www.biorxiv.org/content/10.1101/2021.09.23.461481v1.full) on the mechanical characterization of developing cell wall layers of tension wood fibers by Atomic Force Microscopy. It contains all raw AFM files (Bruker format .spm, readable by the free software Gwyddion for example) corresponding to mechanical measurements of poplar reaction wood cells (clone 717-1B4) along 3 radial lines/rows, starting from the cambium. Each cell is identified by its "macroscopic" distance from the cambium (value in µm in the name of each file corresponding to the displacement of the sample in the AFM) which was corrected after using the AFM optical image captures. Some files, with a -z extension after the distance value, correspond to a zoom into the cell wall. The data also contain measurements made for mechanical calibration on epoxy embedded Kevlar fibers, controlled measurements in the embedding resin between each radial line and measurements in normal wood cells. Two csv files containing final data extracted from AFM measurements that give the value of the indentation modulus and the relative thickness to cell diameter ratio (by AFM and by phase contrast optical microscopy) in each cell wall layer as a function of cambium distance are also provided.

opencc-by-4.0Jan 2022View details →

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Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics

Full-resolution representative data sufficient to repeat analyses for the work of: AE Wolf, MA Heinrich, IB Breinyn, TJ Zajdel, and DJ Cohen in "Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics". Please see the _README2.0.0.txt file for explanations on contents in this Zenodo repository. Relevant codes used in our analyses are available on Github (github.com/CohenLabPrinceton/ElectrotaxisSupracellularMemory).

opencc-by-4.0Mar 2021View details →

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Data: DEAE-Dextran enhances the lentiviral transduction of primary human mesenchymal stromal cells from all major tissue sources without affecting their proliferation and phenotype

This data set includes all the raw data collected for the following article: "DEAE-Dextran enhances the lentiviral transduction of primary human mesenchymal stromal cells from all major tissue sources without affecting their proliferation and phenotype"

opencc-by-4.0Sep 2022View details →

zenodo48/100

Protein structure files for the paper "Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth" in Nature Cell Biology by Tang et al.

This archive contains models of HRAS, KRAS, and NRAS homo- and heterodimers with various mutations discussed in the paper,  "Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth" in Nature Cell Biology by Tang et al. as well as crystallographic dimers of these proteins as identified by the ProtCAD database, http://dunbrack2.fccc.edu/ProtCAD/Results/PfamArchClusterInfo.aspx?GroupId=8 (cluster 5). Several of the models are shown in Supp. Figure 11b and the crystallographic dimers of RAS that provide evidence for the possible biological relevance of these models are shown in Supp. Figure 11a. The crystallographic dimers were identified by clustering all possible interfaces generated by symmetry operators in crystals of HRAS, KRAS, and NRAS as described in the paper: Xu, Q., Dunbrack, R.L. ProtCID: a data resource for structural information on protein interactions. Nat Commun 11, 711 (2020). https://doi.org/10.1038/s41467-020-14301-4. The models were created by superposing monomers of HRAS, KRAS, or NRAS onto the alpha4-alpha5 dimer present in the crystal of PDB entry 3k8y. Mutations were made in PyMOL. The structures were relaxed with the FastRelax protocol and the Ref2015 scoring function in the program Rosetta, which uses the backbone-dependent rotamer library of Shapovalov and Dunbrack to repack side chains. The crystallographic dimers are contained in a zipped PyMOL session. The mmCIF format for all the structures is present in a zip file, Tang_et_al_crystallographic_and_modeled_RAS_dimer_ciffiles.zip. The PyMOL session and zip file contains 87 HRAS dimers, 14 KRAS dimers, and 1 NRAS dimer, all having the interface consisting of the alpha4 and alpha5 helices. The PyMOL session also contains the modeled structures. Only Mg ions and GTP/GNP/GDP ligands are shown. Others are present but hidden and may be displayed by PyMOL ("show sticks, het").

opencc-by-4.0Sep 2022View details →

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Supporting data for: Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

SUMMARY OF THE STUDY We combined functional genomics and human genetics to investigate processes that affect type 1 diabetes (T1D) risk by mediating beta-cell survival in response to proinflammatory cytokines. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) in beta-cells using ATAC-seq and snATAC-seq and linked them to target genes using co-accessibility and HiChIP. Using a genome-wide CRISPR screen in EndoC-βH1 cells we identified 867 genes affecting cytokine-induced survival, and genes promoting survival and up-regulated in cytokines were enriched at T1D risk loci. Using SNP-SELEX, we identified 2,229 variants in cytokine-responsive cCREs altering transcription factor (TF) binding, and variants altering binding of TFs regulating stress, inflammation and apoptosis were enriched for T1D risk.  At the 16p13 locus, a fine-mapped T1D variant altering TF binding in a cytokine-induced cCRE interacted with SOCS1, which promoted survival in cytokine exposure. Our findings reveal processes and genes acting in beta-cells during inflammation that modulate T1D risk. DESCRIPTION OF FILES: <ul> <li>Supplementary Data 1. List of islet cCREs annotated with cell type and cytokine response  - also in GSE205853</li> <li>Supplementary Data 2. Coaccessible sites in untreated beta cells and promoter annotations - also in GSE205853</li> <li>Supplementary Data 3. Coaccessible sites in cytokine-treated beta cells and promoter annotations - also in GSE205853</li> <li>Supplementary Data 4. Coaccessible sites in cytokine treated and untreated beta cells and promoter annotations - also in GSE205853</li> <li>Supplementary Data 5. Chromatin interactions in EndoC-BH1 cells - also in GSE205853</li> <li>Supplementary Data 6. Variants selected for SNP-SELEX assay </li> <li>Supplementary Data 7. Variants with TF binding and allelic binding results from SNP-SELEX</li> <li>Supplementary Data 8. snATAC-seq barcodes and metadata - also in GSE205853</li> <li>Supplementary Data 9. CRISPR-KO screen results - also in GSE205853</li> <li>Supplementary Data 10. Bulk ATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 11. Bulk RNA-seq count matrix - also in GSE205853</li> <li>Supplementary Data 12. Alpha cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 13. Acinar cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 14. Beta cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 15. Stellate cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 16. Endothelial cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 17. Delta cells snATAC-seq count matrix - also in GSE205853</li> <li>Supplementary Data 18. Luciferase assay rs10483809</li> <li>Supplementary Data 19. SOCS1 knockdown qPCR results</li> <li>Supplementary Data 20. SOCS1 knockdown Apotracker (flow-cytometry)results</li> </ul> Raw data deposited at GEO, accessions GSE205853 and GSE118725. Please refer to publication and GEO for details on methods.

opencc-by-4.0Dec 2021View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record

Find research datasets worth reusing

Dataset results

PM_035426_B_Celles

PM_035403_B_Celles

PM_035385_B_Celles

PM_035419_B_Celles

PM_035400_B_Celles

PM_035430_B_Celles

PM_035397_B_Celles

PM_035392_B_Celles

PM_035396_B_Celles

Inhibition of epithelial cell YAP-TEAD/LOX signaling attenuates pulmonary fibrosis "

Training and test dataset of STED images of microtubules in fixed cells

Live-cell STED dataset of mitochondria containing ground truth and corresponding low intensity noisy images

Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture Prior

Clonal decomposition and DNA replication states defined by scaled single cell genome sequencing

bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses - Melanoma tutorial

Mechanical characterisation of the developing cell wall layers of tension wood fibres by Atomic Force Microscopy

Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics

Data: DEAE-Dextran enhances the lentiviral transduction of primary human mesenchymal stromal cells from all major tissue sources without affecting their proliferation and phenotype

Protein structure files for the paper "Multiplexed identification of RAS paralog imbalance as a driver of lung cancer growth" in Nature Cell Biology by Tang et al.

Supporting data for: Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines

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