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3,871 results for “quantitative”
Supplementary Movies and Source Data for: Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation
<p>Supplementary Movies and raw data for the manuscript: "Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation":</p> <p>Source_Data.zip: Supplementary Code, Supplementary Data and Weka Analysis</p> <p>Lan_supplementary_movies_AVI.zip: Supplementary movies as AVI</p> <p>Lan_supplementary_movies_MP4.zip: Supplementary movies as MP4</p> <p>Lan_raw_movies.zip: Raw TIFF stacks of the movies.</p> <p>Lan_supplementary_movies.zip: Old version of the movies.</p>
Quantitative results of the analysis of relevant components of the human scapholunate interosseous ligament (SLIL)
<p>This dataset corresponds to the quantification results carried out for the human scapholunate interosseous ligament (SLIL) and several control tissues analyzed in the manuscript entitled "Histological characterization of the human scapholunate ligament". The SLIL plays a fundamental role in stabilizing the wrist bones, and its disruption is a frequent cause of wrist arthrosis and disfunction. Traditionally, this structure is considered to be a variety of fibrocartilaginous tissue and consists of three regions: dorsal, membranous and palmar. Despite its functional relevance, the exact composition of the human SLIL is not well understood. In the present work, we have analyzed the human SLIL and control tissues from the human hand using an array of histological, histochemical and immunohistochemical methods to characterize each region of this structure. Results reveal that the SLIL is heterogeneous, and each region can be subdivided in two zones that are histologically different to the other zones. Analysis of collagen and elastic fibers, and several proteoglycans, glycoproteins and glycosaminoglycans confirmed that the different regions can be subdivided in two zones that have their own structure and composition. In general, all parts of the SLIL resemble the histological structure of the control articular cartilage, especially the first part of the membranous region (zone M1). Cells showing a chondrocyte-like phenotype as determined by S100 were more abundant in M1, whereas the zone containing more CD73-positive stem cells was D2. These results confirm the heterogeneity of the human SLIL and could contribute to explain why certain zones of this structure are more prone to structural damage and why other zones have specific regeneration potential. The original data obtained for the quantitative analyses of each component are shown in this dataset.</p>
Dataset for Quantitative description of metal center organization in single-atom catalysts
<p>Dataset for <strong>Quantitative description of metal center organization in single-atom catalysts </strong>by by K. Rossi, A. Ruiz-Ferrando, D. Faust Akl, V. Gimenez Abalos, J. Heras-Domingo, R. Graux, X. Hai, J. Lu, D. Garcia-Gasulla, N. López, J. Pérez-Ramírez, and S. Mitchell.</p> <p>The data is structured as follows:</p> <ul> <li>01_Micrographs: all micrographs employed in .tif and .png format. An <a href="https://imagej.net/">imageJ </a>macro to overlay coordinate files with images is attached.</li> <li>02_Ground_truth: contains the manually-labeled and predicted xy-coordinates of atomic positions including probabilities.</li> <li>03_All_detection_data: contains all automated predictions of atomic positions in the images of this study (uhd), and of Mitchell et. al in <em>JACS</em>, <strong>144</strong>, 8018-8029 (2022) (jacs_train, jacs_test). This folder further contains model weights and area segmentations needed to estimate the surface atomic densities.</li> <li>04_Trimetallic_analysis: Figures complementing Supplementary Figure S21.</li> </ul> <p> </p>
Dataset for demonstration of quantitative label-free imaging with phase and polarization
<p>The QLIPP_Reconstruction_Resources_20x.zip file contains raw images of mouse brain slice and anisotropic glass target acquired with QLIPP. The file also contains the configuration files to reconstruct the phase, retardance, and orientation from this data with the recOrder pipeline. The tutorial slides for using this dataset for reconstruction can be found here (10.5281/zenodo.5135889).</p> <p> </p> <p>v1.1.0: Upload two zip files for automated testing of recOrder and waveOrder repositories.</p> <p>v1.2.0: add pycromanager dataset for testing the reader and converter in waveOrder.</p> <p>v1.3.0: reduce the size of recOrder test dataset</p> <p>v 1.4.0: add datasets for new data schema defined for recOrder 0.4.0 </p> <p>v1.5.0: add a dataset that shows images of an embryo </p>
Ayres 2019: Quantitative Guidelines for Establishing and Operating Soil Archives (repackaging of occurrences published by the NEON Biorepository Data Portal)
Ayres, E. 2019. Quantitative Guidelines for Establishing and Operating Soil Archives. Soil Science Society of America Journal, 83(4): 973-981. https://doi.org/10.2136/sssaj2019.02.0050
Supporting data for "In situ Quantitative Tensile Tests on Antigorite in a Transmission Electron Microscope"
<p>Abstract: The determination of the mechanical properties of serpentinites is essential towards the understanding of the mechanics of faulting and subduction. Here, we present the first in situ tensile tests on antigorite in a transmission electron microscope. A push-to-pull deformation device is used to perform quantitative tensile tests, during which force and displacement are measured, while the microstructure is imaged with the microscope. The experiments have been performed at room temperature on beams prepared by focused ion beam. The specimens are not single crystals despite their small sizes. Orientation mapping indicated that some grains were well-oriented for plastic slip. However, no dislocation activity has been observed even though engineering tensile stress went up to 700 MPa. We show also that antigorite does not exhibit an pure elastic-brittle behaviour since, despite the presence of defects, the specimens underwent plastic deformation and did not fail within the elastic regime. Instead, we observe that strain localizes at grain boundaries. All observations concur to show that under our experimental conditions, grain boundary sliding is the dominant deformation mechanism. This study sheds a new light on the mechanical properties of antigorite and calls for further studies on the structure and properties of grain boundaries in antigorite and more generally in phyllosilicates.</p>
Heatmaps of quantitative and qualitative phenotypes of zebrafish pronephroi upon compound exposure
<p>Heatmaps of quantitative and qualitative phenotypes of embryonic zebrafish pronephroi after exposure to compounds from the Prestwick library.</p> <p>For further details please see:</p> <p><em>Westhoff JH, Steenbergen PJ, Thomas LSV, Heigwer J, Bruckner T, Cooper L, Tönshoff B, Hoffmann GF and Gehrig J (2020) In vivo High-Content Screening in Zebrafish for Developmental Nephrotoxicity of Approved Drugs. Front. Cell Dev. Biol. 8:583. doi: 10.3389/fcell.2020.00583</em></p> <p>The images represent full resolution versions of the thumbnails presented in: </p> <ol> <li>Supplementary Figure 3 | Fully annotated heat map of quantitative features.</li> <li>Supplementary Figure 4 | Fully annotated heat map of qualitative features.</li> </ol> <p> </p> <p> </p>
Polish is quantitatively different on quartzite flakes used on different worked materials [R analysis]
<p>This upload includes the following files related to the R analysis:</p> <p>- Raw data as a CSV table (processing-quartzite-final.csv), i.e. results from the ConfoMap analysis (see <a href="https://doi.org/10.5281/zenodo.3979116">https://doi.org/10.5281/zenodo.3979116</a>)</p> <p>- RStudio project (Quantification quartzite final.Rproj)</p> <p>- R scripts as R Markdown files (*.Rmd)</p> <p>- R scripts knitted to HTML files (*.html)</p> <p>- An R script (RStudioVersion.R) to write the used version of RStudio to a text file (RStudioVersion.txt)</p> <p>- Output from script #1: processing-quartzite-final.Rbin and processing-quartzite-final.xlsx</p> <p>- Output from script #2: processing-quartzite-final_summary-stats.xlsx</p> <p>- Output from script #3: all plots as PDF files.</p> <p>Note that for running the scripts, the raw data files (processing-quartzite-final.csv, .Rbin and .xlsx) should be stored in a "Data" folder within the working directory.<br> Output (processing-quartzite-final_summary-stats.xlsx and PDF plots) were saved into "Summary-stats" and "Plots" folders, respectively.</p> <p>Zenodo does not allow sub-folders, so this folder structure had to be removed.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
Polish is quantitatively different on quartzite flakes used on different worked materials [ConfoMap analysis]
<p>Each surface has been processed with two templates:</p> <p>1) Extract two 50x50 µm sub-areas and extract topography layer from each sub-area. Export sub-areas as SUR files. File names start with "A35" or "VSH4".</p> <p>2) Process all extracted sub-areas for quantitative analysis. File names start with "processing-quartzite-final".</p> <p>All ConfoMap templates are saved in MNT format (including all original and processed surfaces, as well as results). Each template has also been exported to a PDF file.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p> <p>Additionally, the results of the second template are collated into "processing-quartzite-final.csv".</p>
A quantitative analysis of the interplay of environment, neighborhood and cell state in 3D spheroids - Dataset
<p>This is the umbrella archive that contains all the datasets and code associated with:</p> <p><strong>A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids</strong></p> <p> Vito RT Zanotelli<br> Matthias Leutenegger<br> Xiao‐Kang Lun<br> Fanny Georgi<br> Natalie de Souza<br> Bernd Bodenmiller</p> <p><em>Mol Syst Biol. (2020) 16: e9798</em><br> <a href="https://doi.org/10.15252/msb.20209798">https://doi.org/10.15252/msb.20209798</a></p> <p><em>Please cite this article if you re-use any of the data or code.</em></p> <p>Datasets:</p> <ul> <li>Brightfield plate images: Contains all plate acquisitions for the individual sphere plates before pooling <ul> <li>4 cellline experiment: <ul> <li>p173: <a href="http://doi.org/10.5281/zenodo.3991929">10.5281/zenodo.3991929</a></li> <li>p176: <a href="http://doi.org/10.5281/zenodo.3991931">10.5281/zenodo.3991931</a></li> </ul> </li> <li>Overexpression experiment: <ul> <li>p161: <a href="http://doi.org/10.5281/zenodo.3991925">10.5281/zenodo.3991925</a></li> <li>p165: <a href="http://doi.org/10.5281/zenodo.3991927">10.5281/zenodo.3991927</a><br> </li> </ul> </li> </ul> </li> <li>Slidescan images: Contains all fluorescent slidescan images of the cuts derived from the pooled spheroid sample blocks <ul> <li>4 cellline experiment: <ul> <li>p173: <a href="http://doi.org/10.5281/zenodo.3991921">10.5281/zenodo.3991921</a></li> <li>p176: <a href="http://doi.org/10.5281/zenodo.3991923">10.5281/zenodo.3991923</a></li> </ul> </li> <li>Overexpression experiment: <ul> <li>p161: <a href="http://doi.org/10.5281/zenodo.4066430">10.5281/zenodo.4066430</a></li> <li>p165: <a href="http://doi.org/10.5281/zenodo.3991919">10.5281/zenodo.3991919</a><br> </li> </ul> </li> </ul> </li> <li>Spillover acquisitions: Contains all spillover acquisitions associated with the two experiments: <ul> <li>4 cellline experiment: <ul> <li>p173/p176: <a href="http://doi.org/10.5281/zenodo.3991945">10.5281/zenodo.3991945</a></li> </ul> </li> <li>Overexpression experiment: <ul> <li>p161/p165: <a href="http://doi.org/10.5281/zenodo.3991947">10.5281/zenodo.3991947</a><br> </li> </ul> </li> </ul> </li> <li>Imaging mass cytometry acquisitions: <ul> <li>4 cellline experiment: <ul> <li>p173: <a href="http://doi.org/10.5281/zenodo.3991937">10.5281/zenodo.3991937</a></li> <li>p176: <a href="http://doi.org/10.5281/zenodo.3991939">10.5281/zenodo.3991939</a></li> </ul> </li> <li>Overexpression experiment: <ul> <li>p161: <a href="http://doi.org/10.5281/zenodo.3991933">10.5281/zenodo.3991933</a></li> <li>p165: <a href="http://doi.org/10.5281/zenodo.3991935">10.5281/zenodo.3991935</a><br> </li> </ul> </li> </ul> </li> <li>Processed data set: <ul> <li>4 cellline experiment: <a href="https://doi.org/10.5281/zenodo.3991942">10.5281/zenodo.3991942</a></li> <li>Overexpression experiment: <a href="http://doi.org/10.5281/zenodo.4271917">10.5281/zenodo.4271917</a></li> </ul> </li> </ul> <p>Code:</p> <p>A snakemake pipeline to reproduce the analyses from this raw data can be found at: <a href="http://github.com/BodenmillerGroup/SpheroidPublication">http://github.com/BodenmillerGroup/SpheroidPublication</a></p> <p>A version already containing all the containers can be found at: <a href="http://doi.org/10.5281/zenodo.4071861">10.5281/zenodo.4071861</a></p> <p> </p>
Data set for "Quantitative and Qualitative bibliometric scope toward the Synthesis of Rose Oxide as a Natural Product in perfumery"
<p>This is the bibliometric data for "Quantitative and Qualitative bibliometric scope toward the Synthesis of Rose Oxide as a Natural Product in perfumery" study which were derived from SCOPUS database, on 23<sup>rd</sup> September 2019, based on title search.</p>
Research data supporting "Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy"
<p>Research data supporting the publication:</p> <p>M. Bergholt, 2017, Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy, Biomaterials, Volume 140, September 2017, Pages 128–137, DOI: 10.1016/j.biomaterials.2017.06.015</p>
Orientation anisotropy of quantitative MRI relaxation parameters in ordered tissue
<p>This dataset contains all the raw source data and MATLAB analysis functions that comprise the study:</p> <p><br> <strong>Orientation anisotropy of quantitative MRI relaxation parameters in ordered tissue</strong></p> <p>Scientific Reports | DOI:10.1038/s41598-017-10053-2</p> <p>Hänninen Nina(1,2), Rautiainen Jari(1), Rieppo Lassi(2,3), Saarakkala Simo(2,3,4) and Nissi Mikko Johannes(1*)</p> <ol> <li>Department of Applied Physics, University of Eastern Finland, POB 1627, FI-70211 Kuopio, Finland</li> <li>Research Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, FI-90014 Oulu, Finland</li> <li>Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland</li> <li>Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland</li> </ol> <p> </p> <p>*Corresponding author:<br> Mikko J. Nissi<br> Department of Applied Physics,<br> University of Eastern Finland<br> POB 1627<br> FI-70211, Kuopio, Finland<br> mikko.nissi@uef.fi<br> +358-50-5955517</p> <p><br> Keywords: relaxation anisotropy, orientation, cartilage, MRI, quantitative</p> <p> </p> <p><br> Included folders and files are:</p> <ul> <li>article_figures: all figures published in the manuscript</li> <li>data: MRI measurement data and pre-processed PLM measurement data</li> <li>matlab_functions: matlab functions used in data analysis with subfolders: <ul> <li>aedes_plugins: plugins for aedes (http://aedes.uef.fi) for calculation of relaxation time maps</li> <li>fitting_functions: miscellaneous functions for fitting relaxation times etc, used by the functions in above folder</li> <li>miscellaneous_functions: small helper functions for a number of small tasks utilized by the other scripts and functions</li> </ul> </li> <li>plm_new_data: histological data measured by quantitative polarized light microscopy.</li> <li>sample_holder_3D_model: .stl files for the 3-D printable sample-holder which allows rotation of the specimen</li> <li>carbon_data_collector_ROT_for_publication.m: master data collection and analysis script that reads in all the data and performs all the calculations to produce the images of the study. This function relies on all the matlab-functions in the subfolder (i.e. the subfolders need to be indexable by matlab) and Aedes analysis software (http://aedes.uef.fi) and matlab R2013b or later.</li> <li>README.txt: this file</li> </ul> <p><br> Notes for setting up Aedes correctly for this dataset:<br> Run Aedes -> Tools -> Edit VNMR Defaults:</p> <ul> <li>Return: FT + K-space</li> <li>DC: off</li> <li>Zeropadding: off</li> <li>Sorting & fastread: on</li> <li>Precision: single</li> <li>Read_fcn: readfid (old)</li> <li>Orient: no</li> </ul> <p>See more info in separate readme files included in each folder.</p> <p><br> (Mikko Nissi, Aug 15, 2017)</p> <p> </p>
StageIV-IRC – A High-resolution Dataset of Extreme Orographic Quantitative Precipitation Estimates (QPE) Constrained to Water Budget Closure for Historical Floods in the Appalachian Mountains
<h2>Quantitative Flood Estimation (QFE) in complex terrain remains a grand challenge in operational hydrology due to the lack of accurate high-resolution Quantitative Precipitation Estimates (QPE) at spatial and temporal resolutions needed to capture the variability of orographic precipitation, and where radar-based QPE are available there are significant biases due to the geometry and constraints of radar operations. Here, we present a high-resolution (i.e. 250m, 5minute-hourly) QPE dataset for the most extreme (flood-producing) events from 2008 to 2024 for 26 gauged basins (in total 215 events) in the Appalachian mountains constrained to meet basin-scale water budget closure through inverse rainfall-runoff modeling to correct the Next Generation Weather Radar (NEXRAD) Stage IV analysis (4km resolution, hourly) using a fully-distributed uncalibrated hydrological model that leverages recent advances in hydrologic modeling in mountainous regions (e.g. improved river routing and initial soil moisture estimation) (Liao and Barros, 2024a and 2024b). The corrected Stage IV analysis is referred to as StageIV-IRC (Inverse Rainfall Correction). Previously, a subset of this dataset informed the construction of a generalized QPE error model (Liao and Barros, 2023), supporting the development of water budget closure constrained QPE and providing physics insights into orographic QPE uncertainties for various radar-based products at high resolution in complex terrain. The unique advantage of the StageIV-IRC QPE is that it achieves water budget closure at the storm-flood event scale within observational uncertainty of streamflow observations, that is the golden standard in hydrological modeling. The QPE dataset is publicly available at: <a href="https://doi.org/10.5281/zenodo.14028867">https://doi.org/10.5281/zenodo.14028867</a></h2> <p><strong> </strong></p>
Placental Expression Quantitative Trait Loci In An East Asian Population
<p>Analysis script, full eQTL summary statistics, and fine-mapping statistics of article "Placental Expression Quantitative Trait Loci In An East Asian Population". This data contains workflow and result of 102 East Asian placental expression quantitative trait loci analysis.</p><p>Genotype from 102 cord blood used in the analysis is also included. Variants with minor allele frequencies less than 0.01 was filtered out to prevent personnel identification.</p>
Dataset for publication "Multi-phase quantitative compositional mapping by LA-ICP-MS: analytical approach and data reduction protocol implemented in XMapTools"
<p>Datasets for the publication "Multi-phase quantitative compositional mapping by LA-ICP-MS: analytical approach and data reduction in XMapTools"</p>
Single cell analysis by Quantitative image-based cytometry (QIBC)
<p>Quantitative image-based cytometry (QIBC): Employing automated multichannel wild-field microscopy using the Olympus ScanR screening system. This system includes an inverted motorized Olympus IX83 microscope, a motorized stage, IR-laser hardware autofocus, a fast emission filter wheel with single band emission filters. </p> <p>Images were analyzed and processed using ScanR analysis software and TIBCOSpotfire software was used to plot total nuclear pixel intensities and mean (total pixel intensities divided by nuclear area) nuclear intensities.</p>
Quantitative results of the analysis of relevant components of artificial bilayered substitutes developed by tissue engineering
<p>This dataset corresponds to the quantification results carried out for artificial bilayered substitutes developed by tissue engineering and control tissues analyzed in the manuscript entitled "<span>Spatiotemporal characterization of extracellular matrix maturation in human artificial stromal-epithelial tissue substitutes</span>". Tissue engineering techniques offer new strategies to understand complex processes in a controlled and reproducible system. In this study, we generated bilayered human tissue substitutes consisting of a cellular connective tissue with a suprajacent epithelium (full-thickness stromal-epithelial substitutes or SESS), and human tissue substitutes with an epithelial layer generated on top of an acellular biomaterial (epithelial substitutes or ESS). Both types of artificial tissues were studied at sequential time periods to analyze the maturation process of the extracellular matrix (ECM) using histochemical and immunohistochemical techniques. Results showed that both models were able to exhibit a partial development of the epithelial layer. ESS cells showed active proliferation, positive expression of KRT5 and low expression of differentiation markers, whereas SESS epithelium showed higher differentiation levels, with a progressive positive expression of KRT10 and claudin, although the differentiation levels of control native tissues were not reached. Despite the typical rete-ridges and papillae of native tissues were not found, stromal cells in SESS tended to accumulate and actively synthetize ECM components such as collagens and proteoglycans in the stromal area in direct contact with the epithelium (Z1 zone), whereas these components were very scarce in ESS. Regarding the basement membrane (BM), ESS showed a partially-differentiated structure containing fibronectin-1 (FN1) and perlecan (HSPG2), although the PAS staining signal was significantly lower than control native tissues. However, SESS showed higher BM differentiation, with positive expression of FN1, HSPG2, nidogen 1 (NID1), chondroitin-6-sulfate proteoglycans (CH6S), agrin (AGRN), and collagens types IV (COL-IV) and VII (COL-VII), although this structure was negative for lumican (LUM). These results confirm the relevance of epithelial-stromal interaction for ECM development and differentiation, especially regarding BM components, and suggest the usefulness of bilayered artificial tissue substitutes to reproduce ex vivo the ECM maturation and development process of human tissues. The original data obtained for the quantitative analyses of each component are shown in this dataset.</p> <p> </p>
Main model fits and substitution rate predictions for: A quantitative genetic model of background selection in humans
<p>Across the human genome, there are large-scale fluctuations in genetic diversity caused by the indirect effects of selection. This can be thought of as a "linked selection signal" that reflects the impact of selection varying according to the placement of functional regions and recombination rates along the genome. Previous work has shown that negative selection against the steady influx of new deleterious mutations into conserved regions is the predominant mode of selection in humans. However, the theoretic model that underpins these results, classic Background Selection theory, is only applicable when new mutations are so deleterious that they cannot fix in the population. Here, we develop a statistical method based on a quantitative genetics view of the linked selection, which models the effects of weak draft created according to how polygenic additive fitness variance is distributed along the genome. We use a recent model that jointly predicts the equilibrium fitness variance and substitution rates due to both strong and weakly deleterious mutations, we estimate the distribution of fitness effects (DFE) and mutation rate across three human populations. While our model can accommodate weaker selection, we initially find evidence across three human populations of very strong selection against deleterious mutations consistent with previous work. However, the corollary predicted substitution rates for conserved regions are unreasonably low, and in disagreement with observed rates. We hypothesize this could be due to selected sites experiencing a further diminished population size due to selective interference. When we account for this in our method, we find evidence of weakly deleterious mutations in conserved regions which brings the predicted substitution rate into agreement with observations. However, these models lead to implausibly large mutation rate estimates. Overall, while our model of the genomic linked selection signal brings us a step towards uniting population and quantitative genetic selection models with the substitution process, our work suggests considerable uncertainty remains about the processes generating fitness variance in humans.</p>
Images supporting: Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation
<p>Two image datasets (as zip files) including all images analyzed in the manuscript Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation. Images are of pancreatic adenocarcinoma (PDAC) cystic spheroid samples grown in either BME or Matrigel. Some images have background noise in the form of iron oxide nanoparticles introduced to them.</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.