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1,772 results for “Gels”
Sliding on slide-ring gels
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Coupling gel electrophoresis with photoluminescence imaging reveals biochrome complexes in modern and fossil shells
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Uncropped gel—nuclease data from: A nicking class 1 OLD family nuclease encoded by <em>Vibrio cholerae</em> inhibits virbiophage replication and is countered by a direct inhibitor
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A representative gel of ALAD following a restriction fragment length digestion
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Dynamic 3D X-ray micro-CT data of a tablet dissolution in a water-based gel with dynamic changes in the scanning geometry
<p><strong>Summary</strong></p> <p>This submission contains a dynamic tomographic X-ray data of a tablet dissolving in a water-based gel. The data is collected over a 5-minute period during which the sample is rotated rapidly as effervescent bubbles are formed and travelling to the surface of the gel.</p> <p>This is the second experiment detailed in Case Study 3 in [Coban 2020], and this submission can be treated as a follow up to [Coban&Lucka 2019]. </p> <p> </p> <p><strong>Apparatus</strong></p> <p>The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].</p> <p> </p> <p><strong>Sample Information</strong></p> <p>The setup consists of a store-bought denture cleaning tablet, placed at the bottom of a clear cylindrical plastic container. These tablets are typically designed to be fast-dissolving, and produce small and compact channels of bubbles. We use a denture cleaning tablet in particular as the dissolution time in water varies from 3 to 5 minutes, meaning the bubbles are produced at a slower rate. In addition, we use a store-bought water-based gel instead of water to slow down the bubble displacement during the experiment.</p> <p> </p> <p><strong>Experimental Plan</strong></p> <p>This experiment is performed such that 150 projections are collected over 360 degrees, for a total of 166 rotations, with exposure time 12 ms for each projection. This means that in total the submission contains 25000 projections. This experiment took 5 minutes of acquisition time, during which we (at user's command) zoom in onto the bottom of the sample holder (i.e. where the tablet rests). We later (again, at user's command) shift the view (i.e. the tube and the detector) upwards to the top of the sample to observe foaming on the surface. Finally, before the end of the 5-minute acquisition period, we zoom out to the original magnification. Every time the geometry undergoes a major change such as zooming in (which would affect the reconstruction), the system creates a new data settings file with the new geometrical information, appended by the projection number, therefore marking the change. However, since there is no major change created by the vertical shift of the tube and detector (as in no change in geometry that would affect the reconstructed images), there is no new data settings file for this event. </p> <p>The spatial resolution for this data is 193μm at the beginning (or end) of the experiment, which at an arbitrary point changes to 76μm. For a smooth data transfer, each projection image is binned down to the size of 486px-by-384px. No centrifugal force effect was observed on the bubbles travelling during the scan or in our test runs at the given rotational speed.</p> <p>All raw data (i.e. with no corrections) is made available in .tif format.</p> <p> </p> <p><strong>List of Contents</strong></p> <p>The contents of the submission is given below.</p> <ul> <li><strong>scan_1</strong>: A 5-minute dynamic CT data folder containing <ul> <li>dark-field (or closed-shutter) image, <em>di000000.tif,</em></li> <li>pre flat-field (or open-shutter before acquisition) image, <em>io000000.tif</em>,</li> <li>post flat-field (or open-shutter after acquisition) image, <em>io000001.tif</em>,</li> <li>raw (unprocessed or uncorrected) projections, <em>scan_*.tif</em> (25000 projections in total),</li> <li><em>data settings XRE.txt</em>, a text file with scanner metadata (this is the final geometry info file),</li> <li><em>data settings XRE_5220.txt</em> (geometry info recorded after the zoom-in)</li> <li><em>data settings XRE__22610.txt</em> (geometry info recorded after the zoom-out, same as <em>data settings XRE.txt</em>)</li> </ul> </li> </ul> <p> </p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the <a href="https://www.cwi.nl/research/groups/computational-imaging">Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> </ul> <p> </p> <p><strong>Acknowledgments</strong></p> <p>We thank Dr. Samuel McDonald and Prof. Philip Withers for the useful discussion, and Dr. Manuel Dierick for his advice in making this experiment possible.</p>
Dynamic 3D X-ray micro-CT data of a tablet dissolution in a water-based gel
<p><strong>Summary</strong></p> <p>This submission contains a dynamic tomographic X-ray data of a tablet dissolving in a water-based gel. The data is collected over a 5-minute period during which the sample is rotated rapidly as effervescent bubbles are formed and travelling to the surface of the gel.</p> <p>The data is made available as part of Case Study 3 in [Coban 2020].</p> <p> </p> <p><strong>Apparatus</strong></p> <p>The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].</p> <p> </p> <p><strong>Sample Information</strong></p> <p>The setup consists of a store-bought denture cleaning tablet, placed at the bottom of a clear cylindrical plastic container. These tablets are typically designed to be fast-dissolving, and produce small and compact channels of bubbles. We use a denture cleaning tablet in particular as the dissolution time in water varies from 3 to 5 minutes, meaning the bubbles are produced at a slower rate. In addition, we use a store-bought water-based gel instead of water to slow down the bubble displacement during the experiment.</p> <p> </p> <p><strong>Experimental Plan</strong></p> <p> </p> <p>This experiment is performed such that 120 projections are collected over 360 degrees, for a total of 83 rotations, with exposure time 30 ms for each projection. This means that in total the submission contains 10000 projections. This took a total of 5 minutes of acquisition time, during which the tablet moved due to saturation but did not completely dissolve. The spatial resolution is 95μm, and the field of view was cropped to the boundaries of the sample holder (each projection image is of size 647px×768px). Our experimental setup allowed the collection of open and closed shutter (flat- and dark-field) images before decanting the gel onto the tablet. No centrifugal force effect was observed on the bubbles travelling during the scan or in our test runs at the given rotational speed.</p> <p>All raw data (i.e. no corrections) is made available in .tif format.</p> <p> </p> <p><strong>List of Contents</strong></p> <p>The contents of the submission is given below.</p> <ul> <li><strong>scan</strong>: A 5-minute dynamic CT data folder containing <ul> <li>dark-field (or closed-shutter) image, <em>di000000.tif,</em></li> <li>pre flat-field (or open-shutter before acquisition) image, <em>io000000.tif</em>,</li> <li>post flat-field (or open-shutter after acquisition) image, <em>io000001.tif</em>,</li> <li>raw (unprocessed or uncorrected) projections, <em>scan_*.tif</em> (10000 projections in total),</li> <li><em>data settings XRE.txt</em>, a text file with scanner metadata,</li> <li><em>script.txt</em> and <em>script_executed.txt</em> are the text files containing the list of commands the apparatus has executed.</li> </ul> </li> </ul> <p> </p> <p><strong>Additional Links</strong></p> <p>These datasets are produced by the <a href="https://www.cwi.nl/research/groups/computational-imaging">Computational Imaging group</a> at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's <a href="http://github.com/cicwi">GitHub page</a>.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these dataset, please get in touch with </p> <ul> <li>s.b.coban [at] cwi.nl</li> </ul> <p> </p> <p><strong>Acknowledgments</strong></p> <p>We thank Dr. Samuel McDonald and Prof. Philip Withers for the useful discussion, and Dr. Manuel Dierick for his advice in making this experiment possible.</p> <p> </p>
256 DPPC Molecules bilayer in pure Water, simulated at 288K (gel) or 358K (fluid)
<p><strong>Publication:</strong> MLLPA: A Machine Learning-assisted Python module to study phase-specific events in lipid membranes</p> <p><strong>Published on:</strong> 08 April 2021</p> <p><strong>Journal</strong>: <em><a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.26508">J Comp Chem</a>, </em>2021, DOI: 10.1002/jcc.26508</p> <p><strong>Description</strong>: Simulation files used to train our Python module to identify the thermodynamic phase of individual lipid molecules in a bilayer, as well as the simulation files analysed by the machine learning models. More information on the module can be found on <a href="https://vivien-walter.github.io/mllpa/">its website</a>.</p> <p>The training files are named dppc_gel.gro and dppc_fluid.gro. They respectively correspond to the final frame of the systems simulated at 288K and 358K. All other files are the files analysed by the module.</p> <p><strong>System composition:</strong></p> <ul> <li>DPPC molecules: 256 with 130 atoms each</li> <li>Water molecules: 42,492 with 3 atoms each </li> <li>Simulation box dimensions (approx.): 9 x 9 x 20 nm</li> </ul> <p><strong>Simulation details:</strong></p> <ul> <li>Software: Gromacs (v. 2020)</li> <li>Forcefield: Charmm36 (v. June 2015) - Water: TIP3P</li> <li>Thermostat: Nose-hoover (0.4ps, 2 groups)</li> <li>Barostat: Parrinello-Rahman semi-isotropic (2.0ps, 1.0 bar on each axis, 4.5e-5 bar-1)</li> <li>Duration: 25 ns (after stabilisation)</li> </ul>
Comparative study on photocatalytic activity of transition metals (Ag and Ni doped ZnO) nanomaterials synthesised via sol-gel method
Ag and Ni/ZnO photocatalyst nanostructures were successfully synthesized by a sol-gel method. In this work, the photocatalyst sample was systematically studied based on several factors affecting the performance of photocatalyst which are size, morphology, band gap, textural properties and the number of active sites presence on the surface of the nanocatalyst. X-ray Diffraction (XRD) revealed that Ag/ZnO nanomaterials experienced multiple phases, meanwhile for Ni/ZnO the phase of nanomaterials were pure and single phase for stochiometry less than 5%. Field emission scanning electron microscope (FESEM) showed almost all of the synthesised nanomaterials possessed a mixture of nanorods and spherical-like shape morphology. The Ag/ZnO showed high photocatalytic activity, producing at least 14th trials of nanocatalyst reusability on the degradation of Methyl Orange under UV irradiation. Interestingly this phenomenon was not observed in larger surface area of Ni/ZnO nanomaterials which supposedly favour photocatalytic activity, but instead producing poor photocatalytic performance. The main reason were studied and exposed by temperature-programmed desorption of carbon dioxide (TPD–CO2) which showed that incorporation of Ag into ZnO lattice has enhanced the number of active sites on the surface of the nanocatalyst. Whereas incorporation of Ni in ZnO has lowered the number of active sites with respect to undoped ZnO. Active sites measurement is effective and significant, providing opportunities in developing an intensive study as an additional factor.
Source gels for TECprobe validation experiments
<p>Raw source gels for validation experiments performed during the development of the Transcription Elongation Complex RNA structure probing (TECprobe) method.</p>
Supplementary material (uncropped gels and original blots) for doi: 10.1093/nar/gkac1249
<p><a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Williams+HM&cauthor_id=36651274">Harry M Williams</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Thorkelsson+SR&cauthor_id=36651274">Sigurdur R Thorkelsson</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Vogel+D&cauthor_id=36651274">Dominik Vogel</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Milewski+M&cauthor_id=36651274">Morlin Milewski</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Busch+C&cauthor_id=36651274">Carola Busch</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Cusack+S&cauthor_id=36651274">Stephen Cusack</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Gr%C3%BCnewald+K&cauthor_id=36651274">Kay Grünewald</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Quemin+ERJ&cauthor_id=36651274">Emmanuelle R J Quemin</a>, <a href="https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Rosenthal+M&cauthor_id=36651274">Maria Rosenthal</a></p><p><strong>Structural insights into viral genome replication by the severe fever with thrombocytopenia syndrome virus L protein</strong></p>
Dataset for Disulfide-Crosslinked Tetra-PEG Gels
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Raw gel and membrane figures associated with the publication "Iron-loaded deferiprone can support full hemoglobinization of cultured red blood cells"
<p>Raw gel and membrane figures associated with the publication <strong>Iron-loaded deferiprone can support full hemoglobinization of cultured red blood cells</strong>.</p> <p> </p> <p><strong>For Figure 1a:</strong></p> <p>Raw uncropped image of the gel run with samples combining apotransferrin with iron chelators. After staining with Coomassie, gel was scanned in an Epson V500 scanner (full color, 1200 dpi, bit depth = 24).</p> <p> </p> <p><strong>For Figure 3:</strong></p> <p>Raw uncropped images of the membranes obtained from western blots of cultured erythroblasts derived from three different donors, showing the expression level of proteins involved in iron metabolism regulation (ferritin, transferrin receptor, total EIF2, phospho-EIF2). Actin was used as housekeeping protein for relative quantification of protein abundance for further analysis.</p> <p>After staining, membranes were scanned in an Epson V500 scanner (full color, 1200 dpi, bit depth = 24).</p> <p>For all membranes, the loading order is the same:</p> <p>- <strong>Day 0:</strong> 1000 μg/mL holotransferrin</p> <p>- <strong>Day 0:</strong> 100 μg/mL holotransferrin</p> <p>- <strong>Day 0:</strong> 100 μg/mL holotransferrin + 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 1:</strong> 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 1:</strong> 1000 μg/mL apotransferrin</p> <p>- <strong>(empty lane)</strong></p> <p>- <strong>Day 1:</strong> 1000 μg/mL holotransferrin</p> <p>- <strong>Day 1:</strong> 100 μg/mL holotransferrin</p> <p>- <strong>Day 1:</strong> 100 μg/mL holotransferrin + 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 1:</strong> 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 1:</strong> 1000 μg/mL apotransferrin</p> <p>- <strong>(empty lane)</strong></p> <p>- <strong>Day 2:</strong> 1000 μg/mL holotransferrin</p> <p>- <strong>Day 2:</strong> 100 μg/mL holotransferrin</p> <p>- <strong>Day 2:</strong> 100 μg/mL holotransferrin + 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 2:</strong> 52 μM iron-loaded deferiprone</p> <p>- <strong>Day 2:</strong> 1000 μg/mL apotransferrin</p> <p>More details on the protocol for western blot available in the manuscript at https://doi.org/10.1101/2021.08.02.454758</p> <p> </p> <p><strong>For Figure 4:</strong></p> <p>Raw uncropped images of the membranes obtained from western blots of cultured erythroblasts derived from two different donors with different iron supplementations (no hTf or Def, 52 μM iron-loaded deferiprone, or 300 μg/mL holotransferrin), showing the phosphorylation level of STAT5 upon withdrawal of erythropoietin (Epo) (3 hours) and restimulation with 0.2 or 1.0 U/mL Epo.</p> <p>After staining, membranes were scanned in an Epson V500 scanner (full color, 1200 dpi, bit depth = 24).</p> <p>For both membranes, the loading order is the same:</p> <p>- <strong>Lane 1:</strong> cells cultured without hTf nor Def, and no Epo restimulation</p> <p>- <strong>Lane 2:</strong> cells cultured with 52 μM iron-loaded deferiprone, and no Epo restimulation</p> <p>- <strong>Lane 3:</strong> cells cultured with 300 μg/mL holotransferrin, and no Epo restimulation</p> <p>- <strong>Lane 4:</strong> cells cultured without hTf nor Def, and restimulation with 0.2 U/mL Epo.</p> <p>- <strong>Lane 5:</strong> cells cultured with 52 μM iron-loaded deferiprone, and restimulation with 0.2 U/mL Epo.</p> <p>- <strong>Lane 6:</strong> cells cultured with 300 μg/mL holotransferrin, and restimulation with 0.2 U/mL Epo.</p> <p>- <strong>Lane 7:</strong> cells cultured without hTf nor Def, and restimulation with 1.0 U/mL Epo.</p> <p>- <strong>Lane 8:</strong> cells cultured with 52 μM iron-loaded deferiprone, and restimulation with 1.0 U/mL Epo.</p> <p>- <strong>Lane 9:</strong> cells cultured with 300 μg/mL holotransferrin, and restimulation with 1.0 U/mL Epo.</p>
Stiffness of Fluid and Gel Phase Lipid Nanovesicles: Weighting the Contributions of Membrane Bending Modulus and Luminal Pressurization
<p>In the manuscript, Atomic Force Microscopy (AFM) is employed for characterizing the mechanical response of nanosized lipid vesicles presenting membranes with different physical state. Results suggest that the mechanical response of lipid vesicles can be ascribed to two main contributions, i) the luminal pressure and ii) the intrinsic membrane rigidity. By developing a spring-based model, authors were able to rationalize the apparent disagrement between the two most commonly employed models for describing vesicle mechanics.</p>
Realisation of solid-state electrochromic devices based on gel electrolyte
<p><strong>Background:</strong> Since the last decade, there has been much interest in solid polymer electrolyte (SPE) to address the issues of electrolyte leakage and evaporation in electrochromic devices (ECD). ECD is a state-of-the-art technology having the ability to change from transparent state to opaque state under the influence of a small applied voltage for energy saving applications.</p> <p><strong>Methods:</strong> In this work, tungsten oxide (WO<sub>3</sub>) films were fabricated via the sol-gel spin-coating method. Subsequently, ECDs were assembled based on SPE and liquid polymer electrolyte (LPE) respectively, using indium doped tin oxide (ITO) coated glass as conducting electrodes and WO<sub>3</sub> films as working electrode.</p> <p><strong>Results:</strong> Cyclic voltammetry (CV) results revealed reduced ionic conductivity of conducting ions in SPE based ECD (SECD) owing to increased viscosity by addition of PMMA. However, lesser time was required for the colouration process. LPE based ECD (LECD) showed higher colouration efficiency (CE) compared to its SECD counterpart. This is attributed to its larger optical modulation.</p> <p><strong>Conclusions:</strong> This work presents a comparison between the performance of LECD and SECD in terms of electrochromic (EC) and optical properties. They were analyzed through CV, chronoamperometry (CA) and ultraviolet-visible (UV-Vis) spectrophotometer. Furthermore, this work provides an insight on the employment of solid-state electrolytes in ECDs in view of the persistent leakage and evaporation problems in ECD implementation.</p>
Dataset for "Decoupling elasticity and electrical conductivity of carbon black gels filled with insulating non-Brownian grains"
<p>A unique bistable transition has been identified in granular/colloidal gel-composites, resulting from shear-induced phase separation of the gel phase into dense blobs. In energy applications, it is critical to understand how this transition influences electrical performance. Mixing conductive colloids with conductive inclusions, we find the conductivity and elasticity move in concert, both decreasing in the collapsed phase-separated state. Surprisingly, with insulating inclusions these properties can become decoupled, with the conductivity instead increasing despite the collapse of the gel structure.</p>
Chemistry and Mass Density of Aluminum Hydroxide Gel in Eco- Cements by Ptychographic X‑ray Computed Tomography
<p>Raw data for: Chemistry and Mass Density of Aluminum Hydroxide Gel in Eco- Cements by Ptychographic X‑ray Computed Tomography </p> <p>doi: http://dx.doi.org/10.1021/acs.jpcc.6b10048</p> <p> </p> <p>Eco-cements are a desirable alternative to ordinary Portland cements because of their lower CO<sub>2</sub> footprints. Ye'elimite-based eco-cements are attracting a lot of interest but most of them exhibit relatively poor mechanical properties. Understanding the reasons for the low performances requires the characterization of features such as mass density of the hydrated mineralogical phases, including the amorphous gel, on the sub-micrometer scale which is very challenging. Here we use ptychographic X-ray computed tomography to provide 3D mass density and attenuation coefficient distributions of eco-cement pastes with an isotropic resolution close to 100 nm allowing to distinguish between mineralogical phases with very similar contrast. In combination with laboratory techniques such as the Rietveld method, <sup>27</sup>Al MAS-NMR and electron microscopies, we report compositions and densities of key components. The ettringite and gel volume distributions have been mapped out in the segmented tomograms. Moreover, we discriminate between an aluminum hydroxide gel and calcium aluminum monosulfate, which have close electron density values. Specifically, the composition and mass density of two aluminum hydroxide gels have been determined: (CaO)<sub>0.04</sub>Al(OH)<sub>3</sub>·2.3H2O with 1.48(3) g∙cm<sup>-3</sup> and (CaO)<sub>0.12</sub>Al(OH)<sub>3</sub> with 2.05(3) g∙cm<sup>-3</sup>, which was a long standing challenge.</p>
Raw western blots and agarose gels for "Isoginkgetin and Madrasin are poor splicing inhibitors" manuscript
<p>Raw western blots and agarose gels for "Isoginkgetin and Madrasin are poor splicing inhibitors" manuscript</p>
In Situ-Forming Gels Loaded with Stimuli-Responsive Gated Mesoporous Silica Nanoparticles for Local Sustained Drug Delivery
<p>A novel combination of in situ-forming hydrogels of hyaluronic acid with gated mesoporous materials was developed to design depots for local sustained release of chemotherapeutics. The depot consists of a hyaluronic-based gel loaded with redox-responsive mesoporous silica nanoparticles loaded with safranin O or doxorubicin and capped with polyethylene glycol chains containing a disulfide bond. The nanoparticles are able to deliver the payload in the presence of the reducing agent, glutathione (GSH), that promotes the cleavage of the disulfide bonds and the consequent pore opening and cargo delivery. Release studies and cellular assays demonstrated that the depot can successfully liberate the nanoparticles to the media and, subsequently, that the nanoparticles are internalized into the cells where the high concentration of GSH induces cargo delivery. When the nanoparticles were loaded with doxorubicin, a significant reduction in cell viability was observed. Our research opens the way to the development of new depots that enhance the local controlled release of chemotherapeutics by combining the tunable properties of hyaluronic gels with a wide range of gated materials.</p>
Raw data for the article "In vitro culture of leukemic cells in collagen scaffolds and carboxymethylcellulose-polyethylene glycol gel"
<p>Uncropped original micrographs and raw numerical data of figures and tables from the article submitted to PeerJ. </p>
Microscopy and UV agarose gel images
<p>Fluorescent microscopy images and UV agarose gel photos</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.