Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
232
datasets available to search
ShareScore release 0.9.0
Dataset results
232 results for “cell membrane”
A role for myosin II cluster and membrane energy in cortex rupture for Dictyostelium discoideum cells
Open the record for dataset details and reuse information.
Data for: Exocytosis of the silicified cell wall of diatoms involves extensive membrane disintegration
Open the record for dataset details and reuse information.
Dataset for the paper "High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells", DOI:10.1038/s41929-022-00772-9
<p>The data in this spreadsheet was used to produce the figures in the paper </p> <p>Authors: Asad Mehmood, Mengjun Gong, Frédéric Jaouen, Aaron Roy, Andrea Zitolo, Anastassiya Khan, Moulay-Tahar Sougrati, Mathias Primbs, Alex Martinez Bonastre, Dash Fongalland, Goran Drazic, Peter Strasser, Anthony Kucernak</p> <p>Title: High Loading of Single Atomic Iron Sites in Pyrolysed Fe-NC Oxygen Reduction Catalysts for Proton Exchange Membrane Fuel Cells</p> <p>Journal: Nature Materials</p> <p>DOI: 10.1038/s41929-022-00772-9</p> <p>Please cite the above reference if you wish to use this data </p> <p> </p> <p>DOI of data: 10.5281/zenodo.6411262</p>
Membrane Fluctuation Model to Understand the Effect of the Receptor Nanoclustering on the Activation of Natural Killer Cells through Biomechanical Feedback
<p>Data for all the plots from original paper "Membrane Fluctuation Model to Understand the Effect of the Receptor Nanoclustering on the Activation of Natural Killer Cells through Biomechanical Feedback".</p>
Characterizing multidimensional cellular physiological states with quantitative three-dimensional shape descriptors for cell membranes
<h3>Supplementary dataset and code for the article "<em>Characterizing Cellular Physiological States with Three-Dimensional Shape Descriptors for Cell Membranes</em>"</h3> <p>CShaper Dataset.zip: The 3D cell regions reused from the previously published article <a href="https://doi.org/10.1038/s41467-020-19863-x">https://doi.org/10.1038/s41467-020-19863-x</a>.</p> <p>Cell Shape Descriptors - Code & Data.zip: The code (exemplifed by embryo Sample04) and data (including embryo Sample04-Sample20) of 12 3D shape descriptors for all 3D cell regions in the <em>CShaper</em> dataset.</p> <p>GUI.zip: The user-friendly software <em>Shape Descriptor Tool</em> is a Graphical User Interface based on <em>Matlab</em> for calculating 12 shape descriptors for a 3D cell region (exemplified by embryo Sample20, time point 14, ABpl cell in the <em>CShaper</em> dataset). The instruction guidebook is included in the Supplementary Material of the article.</p>
SN2N's 3D dataset of outer mitochondrial membrane network of live COS-7 cells labeled with Tom20-mCherry on SD-SIM sysytem.
Open the record for dataset details and reuse information.
Cdc42 couples T cell receptor endocytosis to GRAF1-mediated tubular invaginations of the plasma membrane
<p>This Dataset contains primary data used for the publication "Cdc42 couples T cell receptor endocytosis to GRAF1-mediated tubular invaginations of the plasma membrane" published online on 04. November 2019<br> doi:10.3390/cells8111388</p> <p><strong>Abstract:</strong> T cell activation is immediately followed by internalization of the T cell receptor (TCR).<br> TCR endocytosis is required for T cell activation, but the mechanisms supporting removal of TCR<br> from the cell surface remain incompletely understood. Here we report that TCR endocytosis is<br> linked to the clathrin-independent carrier (CLIC) and GPI-enriched endocytic compartments<br> (GEEC) endocytic pathway. We show that unlike the canonical clathrin cargo transferrin or the<br> adaptor protein Lat, internalized TCR accumulates in tubules shaped by the small GTPase Cdc42<br> and the Bin/amphiphysin/Rvs (BAR) domain containing protein GRAF1 in T cells. Preventing<br> GRAF1-positive tubules to mature into endocytic vesicles by expressing a constitutively active<br> Cdc42 impairs the endocytosis of TCR, while having no consequence on the uptake of transferrin.<br> Together, our data reveal a link between TCR internalization and the CLIC/GEEC endocytic route<br> supported by Cdc42 and GRAF1.</p> <p> </p> <p>Data are organised in compressed (.zip) folders entitled as the corresponding Figures in the publication.</p> <p>Programs we recommend to view the files are:<br> .fcs files: FlowJo software v10 (Tree Star, Ashland, OR, USA)<br> .lif files: LAS X v3 (Leica Microsystems, Wetzlar, Germany)<br> .pzfx files: Prism v7 software (GraphPad, San Diego, CA, USA)</p> <p> </p> <p>In case this Dataset is updated, new version will be available with doi:10.5281/zenodo.3545842</p>
Membrane staining and segmentation of a developing mouse embryo from 4 to 26 cells
<h1>Intent</h1> <p>The role of this dataset is to provide an example of segmentable and trackable data using signal from cell membrane. This dataset contains one file with the pre-processed imaged embryo (imaging.zip -> imaging.tif) and one file with the outcome of a segmentation using Cellpose (segmentation.zip -> segmentation.tif).</p> <blockquote> <p>This embryo corresponds to the embryo "C1" in the <a href="https://doi.org/10.1126/science.adh1145" target="_blank" rel="noopener">original publication</a></p> </blockquote> <h1>Animal</h1> <p>This set of data represents a mouse embryo developing from the 4-cell stage. The embryo at the last processed timepoint has 26 cells. The mother and the father were both mTmG animals (tdTomato anchored at the membrane of the cells).</p> <blockquote> <p>Details can be found in the <a href="https://doi.org/10.1126/science.adh1145" target="_blank" rel="noopener">original publication</a></p> </blockquote> <h1>Culture conditions</h1> <p>The embryo was imaged in an inverted SPIM from Luxendo (now Bruker), laying at the bottom of a PFE imaging dish. The embryo developed in a small pocket made by deforming the PFE with a glass tip. We used approx. 150μL of KSOM-AA to cutlure the embryos at 37ºC ± 0.2ºC in 5% CO2 and 5% O2. The medium was covered with approx. 100μL of mineral oil.</p> <blockquote> <p>Details can be found in the <a href="https://doi.org/10.1126/science.adh1145" target="_blank" rel="noopener">original publication</a></p> </blockquote> <h1>Imaging conditions</h1> <p>The tdTomato was excited with a 561nm laser using as little intensity as possible (0% in the settings + a small fraction leaking through the shutter). We used a 561 LP filter to acquire the signal. Imaging was set with a lateral resolution of 0.208μm and a axial resolution of 1μm. Because of technical issues with the stage of the microscope at the time, the resulting axial resolution was ultimately 1.338μm. In total, 181 slices were acquired per time point. Two consecutive timepoints start with 15 minutes of interval.</p> <p>Although this embryo was imaged for a longer period of time, this dataset shows only the first 117 timepoints.</p> <blockquote> <p>Details can be found in the <a href="https://doi.org/10.1126/science.adh1145" target="_blank" rel="noopener">original publication</a></p> </blockquote> <h1>Processing conditions</h1> <table> <tbody> <tr> <td><strong>Operation</strong></td> <td><strong>Lateral resolution</strong></td> <td><strong>Axial resolution</strong></td> <td><strong>File</strong></td> </tr> <tr> <td><strong>Imaging</strong></td> <td>0.208 μm</td> <td>1.338 μm</td> <td>-</td> </tr> <tr> <td><strong>Cropping<br></strong></td> <td>0.208 μm</td> <td>1.338 μm</td> <td>-</td> </tr> <tr> <td><strong>Lateral binning (average)</strong></td> <td>0.416 μm</td> <td>1.338 μm</td> <td>-</td> </tr> <tr> <td><strong>Isotropic rescaling</strong></td> <td>0.416 μm</td> <td>0.416 μm</td> <td>-</td> </tr> <tr> <td><strong>Lateral binning (average)</strong></td> <td>0.832 μm</td> <td>0.832 μm</td> <td>imaging.tif</td> </tr> <tr> <td><strong>Segmentation (cellpose)</strong></td> <td>0.832 μm</td> <td>0.832 μm</td> <td>segmentation.tif</td> </tr> </tbody> </table>
Input Data for "Assembly and Analysis of Cell-Scale Membrane Envelopes"
<p>Input structures for a manuscript, along with selected output data and structures. This directory structure contains a cut-down copy of the directories used to generate the simulation data and the analysis. In order to make this fit into the 50GB Zenodo limit, it was constructed with the following tar command: `tar -zcvf protocellmodeling.tar.gz --exclude="*BAK" --exclude="*#" --exclude="*xtc" --exclude="*gro" --exclude="*trr" --exclude="*js" --exclude="*[0-9].out" --exclude="*old" --exclude="*dcd" --exclude="*tmp" --exclude="*xst" --exclude="*edr" --exclude="*state_prev.cpt" --exclude="*.o[0-9]*" cgDracula`, which intentionally excludes large files. The full 4.8TB dataset that includes trajectories is available upon request.</p> <p>The data is split into multiple subdirectories and largely undocumented, however here are the highlights:</p> <ul> <li>The <strong>Analysis</strong> subdirectory is where the analysis in the paper lives. All other directories are related to building or running systems.</li> <li><strong>getsources.py</strong> in the main directory is the script that downloads the initial structure from MemProtMD.</li> <li><strong>transform.py</strong> builds the initial protein models from MemProtMD.</li> <li><strong>vesiclebuilder.py</strong> builds the lipid ball.</li> <li><strong>protpatchplacer.py</strong> sets up the ultra-coarse grained simulation, which is in the <strong>supercg</strong> directory.</li> <li><strong>movepatches.py</strong> takes the results from the ultra-coarse grained simulation, and builds the protein ball.</li> <li><strong>gendx.tcl</strong> generates the density maps from the protein ball.</li> <li>This is used in <strong>lipids/picklipids.py</strong>, which cuts out the pieces of the lipid that need to be removed.</li> <li>The water is added to the system with <strong>addwater/quicksolvate.sh</strong></li> <li>The system is ionized by <strong>ionize.py</strong></li> <li>And a topology is written by <strong>writetop.py</strong></li> </ul>
Dataset: Carbonate Regeneration Using a Membrane Electrochemical Cell for Efficient CO2 Capture
<p>Dataset for journal publication "Carbonate Regeneration Using a Membrane Electrochemical Cell for Efficient CO2 Capture," published in ACS Sustainable Chemistry & Engineering (DOI: 10.1021/acssuschemeng.2c04175). Data are organized according to figure number.</p>
Biomasses, starch content, cell membrane leakage and phenology of established diploids and tetraploids and synthetic neotetraploids of Jasione maritima var. maritima
<p>Polyploidy is a pervasive phenomenon in nature and has significantly contributed to the adaptive evolution of plants. The conditions necessary for the spread of neopolyploids in populations of the diploid progenitor are limited; however, the superior competitive ability of neopolyploids may promote its establishment. Here, we assess the contribution of polyploidisation to the divergence of plant traits affecting competitive response, which could explain the successful establishment and current geographic distribution of polyploids. We conducted an intraspecific competition experiment using diploids, neotetraploids and established tetraploids of Jasione maritima var. maritima to determine whether cytotypes differ in phenological, growth and physiological traits and competitive response. Cytotypes respond differently under different competition scenarios with implications for cytotype establishment and distribution. Competition impacted all cytotypes, but neotetraploids were least affected by competition, and the tetraploids were the most impacted. Thus, competitive advantage may have contributed to the displacement of diploid populations and colonisation of new areas by neotetraploids but might have been lost afterwards. Evolutionary changes after polyploidisation have also been detected, and tetraploids invested more in belowground biomass, suggesting that root development might also play a role in colonising southernmost locations. Interestingly, diploids and both tetraploids seem to have different life strategies, the first investing in growth while the latter investing in reserves for the next season. Overall, polyploidisation seems to provide immediate changes that confer an advantage under competition that, together with other factors, may have allowed the establishment of neotetraploids.</p>
Unit-cell-thick zeolitic imidazolate framework films for membrane application
<p>raw data for the manuscript with title of Unit-cell-thick zeolitic imidazolate framework films for membrane application</p>
Lithium extraction from brine through a decoupled and membrane-free electrochemical cell design
Open the record for dataset details and reuse information.
Maintaining local alkalinity of CO-electroreduction full cell by silica-confined electrocatalysts in membrane electrode assembly
Open the record for dataset details and reuse information.
Data from: Conditional requirement for dimerization of the membrane-binding module for BTK signaling in lymphocyte cell lines
Open the record for dataset details and reuse information.
Data from: Elucidating the impact of red blood cell membrane components on melittin-induced pore formation with molecular dynamics simulations
Open the record for dataset details and reuse information.
Biomasses, starch content, cell membrane leakage and phenology of established diploids and tetraploids and synthetic neotetraploids of Jasione maritima var. maritima
Open the record for dataset details and reuse information.
Results from: Angiogenic property of silk fibroin scaffolds with adipose-derived stem cells on chick chorioallantoic membrane
<p>Angiogenesis is a key step in tissue regeneration and repair. Biomaterials that allow or promote angiogenesis are thus beneficial. In this study, angiogenic properties of salt-leached silk fibroin (SF) scaffolds seeded with human adipose stem cells (hADSCs) were studied using chick chorioallantoic membrane (CAM) as a model. The hADSC-seeded SF scaffolds (SF-hADSC) with porosity of 77.34 ± 6.96 % and pore diameter of 513.95 ± 4.99 µm were implanted on CAM of chick embryos that were on embryonic day 8 (E8) of development. The SF-hADSC scaffolds induced a spoke-wheel pattern of capillary network indicative of angiogenesis, which was evident since E11. Moreover, ingrowth of blood vessels into the scaffolds was seen in histological sections. The unseeded scaffolds induced the same extent of angiogenesis later on E14. In contrast, the control group could not induce angiogenesis to the same extent even as late. <i>In vitro</i> cytotoxicity tests and <i>in vivo</i> angioirritative study reaffirmed the biocompatibility of the scaffolds. This work highlighted that the biocompatible SF-hADSC scaffolds accelerates angiogenesis, and hence they can be a promising biomaterial for regeneration of tissues that require angiogenesis.</p>
3D Cryo Soft X-ray Transmission Microscopy data of Intact Thick Cells for Membrane Segmentation and Quantification
<p>The datasets used for evaluation of the proposed method in R. Cárdenes and C. Zhang et al. "3D Membrane Segmentation and Quantification of Intact Thick Cells using Cryo Soft X-ray Transmission Microscopy: A Pilot Study", PloS One, 2017. (DOI: 10.1371/journal.pone.0174324)</p>
Dataset for the paper "Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance" published in ACS Appl. Energy Mater.
<p>The data in this spreadsheet was used to produce the figures in the paper</p><p>Authors:</p><p>Colleen Jackson, Michalis Metaxas, Jack Dawson, Anthony Kucernak</p><p>Title:</p><p>Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance</p><p>Journal:</p><p>ACS Appl. Energy Mater. </p><p>DOI:</p><p>10.1021/acsaem.3c01987</p><p>Please cite the above reference if you wish to use this data</p><p>DOI of data:</p><p>10.5281/zenodo.10256698</p>
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.