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.
1,868
datasets available to search
ShareScore release 0.9.0
Dataset results
1,868 results for “Spatial Data”
Spatial transcriptomic data of a lymph node from an individual with Multicentric Castleman Disease
GEO Series GSE240843. Homo sapiens. 1 samples. Type: Other.
SpotClean adjusts for spot swapping in spatial transcriptomics data
GEO Series GSE178221. Homo sapiens; Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Expression data from spatially separated samples of different ccRCC patients
GEO Series GSE53000. Homo sapiens. 62 samples. Type: Expression profiling by array.
Spatial transcriptomics data of RM9-hSTEAP1 tumor tissues treated with CAR-T cells
GEO Series GSE300750. Mus musculus. 36 samples. Type: Other.
Investigative needle core biopsies support multimodal deep-data generation in glioblastoma [Spatial Transcriptomics]
GEO Series GSE287631. Homo sapiens. 16 samples. Type: Other.
Data for the article titled "Multi-omics analysis characterizes the spatial architecture of glioblastoma ecosystems"
<p>Data archive for the article titled "Multi-omics analysis characterizes the spatial architecture of glioblastoma ecosystems"</p>
Data of experiments for "A Spatially Layered DNA Disk for Data Storage"
<p>Data generated or analyzed during our experiments on DNA disk. The first color film “Becky Sharp” (53.59 MB) was encoded into ~10.08 million DNA strands. Simultaneous sequencing and real-time readout were achieved. (<span>Given the value of this film as the first color film, it’s only used to verify the performance of the proposed DNA storage method and does not contain the specific content. Therefore, there are no copyright issues involved.</span>)</p>
SMMGCL: A novel multi-scale graph contrastive learning framework for integrating spatial multi-omics data
Open the record for dataset details and reuse information.
Data associated with spatial profiling of residual breast cancer after neoadjuvant chemotherapy
<p>This dataset contains all the CosMx data associated with Seo <em>et al</em>. <em>In-depth spatial and genomic profiling of residual breast cancer after neoadjuvant chemotherapy unveils divergent fates for each breast cancer subtype, 2024. </em></p> <p>The zip file contains:</p> <ul> <li>Raw CosMx data</li> <li>Processed CosMx data</li> </ul>
Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition across Europe in 2010, link to research data and scientific software
<p>Research data and scientific software related to a study investigating the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites.</p>
Plant species and water chemistry data for "Inference of future bog succession trajectory from spatial chronosequence of changing aapa mires"
<p>These files consist of whole plant species and water chemistry data examined in our paper "Inference of future bog succession trajectory from spatial chronosequence of changing aapa mires" (Ecology and Evolution). Species data sets for phytosociological relevés and nested subplots (size of 0.25 m<sup>2</sup>) consist of abundances of all vascular plant, bryophyte, and lichen species in the studied fen, transition, and bog zones of boreal aapa mires. Subplot data includes groupings of species into aerenchymatous and non-aerenchymatous species, and into shallow- and deep-rooted aerenchymatous species. Water chemistry data consist of pH and concentrations of dissolved organic carbon (DOC), Ca, Mg, Fe, Al, Si, and Mn, as well as water-table depth (WTD) for each sampling point.</p>
Raw data and R code: A major spatial reorganization of the North Atlantic Oscillation around 4000 BP
<p>The raw data as well as the R code from the study 'A major spatial reorganization of the North Atlantic Oscillation around 4000 BP' by J. Schirrmacher and M. Weinelt in review at Nature Communications Earth & Environment is archived. The final plots presented in the paper have beenmade with Grapher16 and QGIS 3.10.</p>
Molecular Profiling of COVID-19 Autopsies Uncovers Novel Disease Mechanisms [Digital Spatial Profiling data]
GEO Series GSE183356. Homo sapiens. 120 samples. Type: Expression profiling by array.
SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS
SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS GOO JUN * AND JOYDEEP GHOSH* Abstract. A semi-supervised learning algorithm for the classification of hyperspectral data, Gaussian process expectation maximization (GP-EM), is proposed. Model parameters for each land cover class is first estimated by a supervised algorithm using Gaussian process regressions to find spatially adaptive parameters, and the estimated parameters are then used to initialize a spatially adaptive mixture-of-Gaussians model. The mixture model is updated by expectationmaximization iterations using the unlabeled data, and the spatially adaptive parameters for unlabeled instances are obtained by Gaussian process regressions with soft assignments. Two sets of hyperspectral data taken from the Botswana area by the NASA EO-1 satellite are used for experiments. Empirical evaluations show that the proposed framework performs significantly better than baseline algorithms that do not use spatial information, and the results are also better than any previously reported results by other algorithms on the same data.
spaTransfer: transfer learning for single-cell and spatial transcriptomics data using non-negative matrix factorization
GEO Series GSE317379. Homo sapiens. 2 samples. Type: Other.
Comprehensive immune profiling reveals IFN-γ signaling in T cells mediates parasite phagocytosis in a rodent malaria model : Spatial transcriptomics data
GEO Series GSE283333. Mus musculus. 2 samples. Type: Other.
Spatial RNA-seq data comparing lesional (papules) and non-lesional skin biopsies of acne patients
GEO Series GSE175856. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
Spatial transcriptomic data from longitudinal tumor samples from one patient undergoing neoadjuvant BO-112 and hypofractionated radiation therapy in soft tissue carcoma
GEO Series GSE313858. Homo sapiens. 4 samples. Type: Other.
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multisource data (2001-2002)
<p>The dataset presents the daily near surface air temperature of China with 1km spatial resolution, including daily average air temperature, maximum temperature and minimum air temperature. The dataset was generated using machine learning and multiple variables, the accuracy was:<span>T<sub>ave</sub>, </span><span>R<sup>2</sup> = 0.97, RMSE = 1.61℃ and rRMSE = 13.24%</span><span>; T<sub>max</sub>, </span><span>R<sup>2</sup> = 0.94, RMSE = 2.35℃ and rRMSE = 13.02%</span><span>; T<sub>min</sub>, </span><span>R<sup>2</sup> = 0.95, RMSE = 2.04℃ and rRMSE = 27.09%</span><span>).</span></p>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2013-2014)
<div> <p>The dataset presents the daily near surface air temperature of China with 1km spatial resolution, including daily average air temperature, maximum temperature and minimum air temperature. The dataset was generated using machine learning and multiple variables, the accuracy was:T<sub>ave</sub>, R<sup>2</sup> = 0.97, RMSE = 1.61℃ and rRMSE = 13.24%; T<sub>max</sub>, R<sup>2</sup> = 0.94, RMSE = 2.35℃ and rRMSE = 13.02%; T<sub>min</sub>, R<sup>2</sup> = 0.95, RMSE = 2.04℃ and rRMSE = 27.09%).</p> </div>
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.