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.
33
datasets available to search
ShareScore release 0.9.0
Dataset results
33 results for “Multi-regional”
Multi-regional comparison of scarring and pigmentation patterns in Cuvier's beaked whales
<p>These files represent standardized appearance data from photos of individually-identified, known-sex, adult Cuvier's beaked whales (Ziphius cavirostris) from three distinct study regions. We provide both the original raw datasets and the filtered datasets that were ultimately used in analyses of scarring density and pigmentation patterns to determine the extent to which they are diagnostic of sex in all three regions. The R code used to analyze these files is provided along with detailed descriptions of the data in a README file.</p>
BCP/Bio-MRSUT 2015. Bio-economic Multi-regional Supply-Use Tables.
<p>BIOCLIMAPATHS is an AXIS-ERANET 2019 granted project, that aims to better understand the impacts of climate change in future societies that have adopted bioeconomy as a substantial pillar of their economies. The project’s main aim – and output – is to provide insights and recommendations for climate resilient and just bioeconomy transition paths for society and economy.</p> <p>The BIOCLIMAPATHS (BCP) consortium leverages on complementary expertise of research teams from Austria, Germany and Spain, developing an innovative, spatially explicit, modelling framework for risk assessments of bioeconomy transitions subject to climate extremes. The project’s main aim – and output – is to provide insights on climate resilient and just bioeconomy transition paths in society.</p> <p>A key tool to achieve this aim is the elaboration of a detailed multisectoral database with high disaggregation on bio-based sectors. For the elaboration of this database, called Bio-MRSUT (Bio-economic Multi-regional Supply-Use Tables) framework, we started from EXIOBASE (Stadler et al. 2018). From the EXIOBASE data to obtaining the series of multi-regional SUT monetary marks, some estimation is required. First, by adapting the initial tables from EXIOBASE to the sectoral structure proposed in BIOCLIMAPATHS. Subsequently, to complete the database with additional information on certain bioeconomy sectors (agriculture, livestock, and biofuels), the 2010 and 2015 BioSAMs (Mainar et al., 2021) carried out by the Joint Research Centre (JRC) of the European Commission have been used, building the pertinent extrapolations to complete the proposed time period. The result of these processes has given rise to multi-regional monetary SUT frameworks for the EU and its Member States with a very broad disaggregation of the bioeconomy sectors. These multiregional frameworks comprise, with reference to the year 2015, a total of 78 activities (44 of Bioeconomy) and 78 goods and services (44 of them bio-economics), for the 28 EU countries (including the United Kingdom) and the Rest of the World, (as well as the interrelationships and bilateral exchanges between all these territories). In addition, they contain the breakdown of final demand and added value, as well as taxes on activities and products and imports by origin (the resulting data matrix contains 4,529 rows and 4,669 columns).</p>
Multi-regional comparison of scarring and pigmentation patterns in Cuvier’s beaked whales
Open the record for dataset details and reuse information.
Future Projection of Solar Energy Over China Based on Multi-Regional Climate Model Simulations
<p>Data for article "Future Projection of Solar Energy Over China Based on Multi-Regional Climate Model Simulations"</p>
Multi-regional Input–output Table for the Global Emerging Economies (EMERGING)
<p><strong>EMERGING</strong>: Up-to-date and full-scale MRIO tables covering 135 sector code (the actual number of sectors is 134) in 245 economies. The EMERGING database is also designed to incorporate more official and publicly available data from national statistical institutes to ensure a high level of data quality, especially for these economies. </p> <p>Please see the steps in the development of the database and reconciliation and validation of bilateral trade data and national statistics in: <strong>Huo, J., Chen, P., Hubacek, K., Zheng, H., Meng, J., & Guan, D. (2022). Full-scale, near real-time multi-regional input–output table for the global emerging economies (EMERGING). Journal of Industrial Ecology, 1– 15. </strong><a href="https://doi.org/10.1111/jiec.13264"><strong>https://doi.org/10.1111/jiec.13264</strong></a></p> <p><strong>EMERGING CO<sub>2</sub> Inventory</strong>: CO<sub>2</sub> emissions (Mt CO<sub>2</sub>eq) from fossil fuel combustion and energy consumption at the sectoral level in each region are available from the IEA database and CEADs emission inventory data. The EMERGING CO<sub>2</sub> Inventory includes a total of 7 energy types: 1. Coal; 2. Natural gas; 3. Oil products; 4. Crude, NGL, Ref Feeds.; 5. Other; 6. Oil shale & oil sands; 7. Peat & Peat products.</p> <div><strong>End year: </strong>The current version of the time series for EMERGING MRIO data is from 2010, 2015 to 2019. We have completed a full update for the period of 2020 to 2022 and the relevant new MRIO table is currently in the testing phase. It will be publicly shared online soon.</div> <div> </div> <p><strong>Announcements</strong></p> <p>These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights. The availability of these data does not constitute publication of the data. The data providers rely on the ethics and integrity of the user to ensure that they receive fair credit for their work. If the data are obtained for potential use in a publication or presentation, we kindly ask you to cite them properly according to the instructions on the website.</p> <p>Queries about the EMERGING database and further collaboration can be addressed to: jing.j.meng@ucl.ac.uk or huojw20@mails.tsinghua.edu.cn </p>
Supplementary Material: MyPyPSA-Ger: Introducing CO2 taxes on a multi-regional myopic roadmap of the German electricity system towards achieving the 1.5 °C target by 2050
<p>Supplementary Material to run the open-source model MyPyPSA-Ger</p>
Chinese Provincial Multi-Regional Input-Output database for 2012, 2015, and 2017
<p>Please note that the tables are constructed by CEADs. More information and the latest updated can be found in the CEADs website (https://www.ceads.net/data/input_output_tables/)</p> <p>If any question, please contact Heran Zheng (zhengheran@foxmail.com)</p> <p> </p> <p> </p> <p> </p>
Multi-region sequencing with spatial information enables accurate heterogeneity estimation and risk stratification in liver cancer
<p>We performed multi-region sampling and sequencing on 14 patients with HCC, collecting a total of 75 tumor samples with spatial information and molecular data. In addition, 21 matched adjacent liver samples were also collected. All samples were subjected to RNA sequencing (RNA-seq). RNA sequencing was performed on Illumina NovaSeq 6000 platform with 40M pair-end 150bp reads per sample. Whole-exome sequencing (WES) was performed on 36 samples from patients T10, T13 and T18 (n = 26) as well as adjacent non-tumor tissues (n = 10). Paired end, 150bp read-length sequencing was then performed on Illumina NovaSeq 6000 platform with a mean sequencing coverage of 100X. Raw sequencing data has been deposited at the National Omics Data Encyclopedia (NODE) under the accession code OEP002956 ( <a href="http://www.biosino.org/node/project/detail/OEP002956">http://www.biosino.org/node/project/detail/OEP002956</a>).</p>
A Multi-center, Multi-regional Observational Study to Test the Responsiveness of the Validated MusiQoL (Multiple Sclerosis International Quality of Life Questionnaire) Instrument to EDSS Status Change
ClinicalTrials.gov study NCT00702065. IPD Sharing: Not stated. Countries: 12. Publications: 2.
JSS Data from Function-specific Scheduling Policies in Cloud-Edge, Multi-Region Serverless Systems
Open the record for dataset details and reuse information.
Updated JSS Data from Function-specific Scheduling Policies in Cloud-Edge, Multi-Region Serverless Systems
Open the record for dataset details and reuse information.
Understanding tumor heterogeneity in melanoma brain metastasis using spatial transcriptomics and multi-regional bulk sequencing
<p>Melanoma brain metastasis (MBM) exhibits extensive inter- and intra-tumor heterogeneity, driven by a complex tumor microenvironment (TME). The aim with this study was to profile the MBMs by using a multi-omics approach, integrating spatial transcriptomics with bulk exome, proteome, and transcriptome profiling. We identified significant patient-specific variations in immune cell infiltration, particularly in B/plasma cells, myeloid cells, and cancer-associated fibroblasts (CAFs). Notably, immunotherapy-treated patients showed enrichedpathways related to EMT, IFN-γ signaling, oxidative phosphorylation, T-cell signaling, inflammation and DNA damage, which aligned with distinct cellular compositions observed in the spatial analysis. We also uncovered considerable intra-tumor heterogeneity, especially at the protein level, revealing differential expression patterns of key tumor and immune-related markers. The correlation between mRNA and protein data highlighted consistent enrichment of critical pathways across multi-omics layers. These findings provide a comprehensive view of MBM's molecular and cellular landscape, emphasizing the importance of addressing tumor heterogeneity in developing effective therapeutic strategies.</p>
Spatially preserved multi-region transcriptomic subtyping and biomarkers of outcome with chemoimmunotherapy in extensive-stage small cell lung cancer [IMfirst_DSP cohort]
GEO Series GSE261348. Homo sapiens. 175 samples. Type: Other.
Spatially preserved multi-region transcriptomic subtyping and biomarkers of outcome with chemoimmunotherapy in extensive-stage small cell lung cancer [CANTABRICO_DSP cohort]
GEO Series GSE261345. Homo sapiens. 121 samples. Type: Other.
A tumor multi-region query reveals novel DNA methylation targets linked to ccRCC poor outcome and metastasis
GEO Series GSE206049. Homo sapiens. 169 samples. Type: Methylation profiling by array.
Multi-region spatial transcriptome analysis reveals cellular networks and pathways associated with hepatocellular carcinoma recurrence after surgical resection
GEO Series GSE281759. Homo sapiens. 17 samples. Type: Other.
Esophageal cancer intratumor heterogeneity revealed by multi-region whole exome sequencing and aCGH
GEO Series GSE60625. Homo sapiens. 11 samples. Type: Genome variation profiling by genome tiling array.
Single-cell multi-omic and multi-region atlas of the Human Alzheimer's Disease Brain
GEO Series GSE308132. Homo sapiens. 0 samples. Type: Methylation profiling by high throughput sequencing; Other.
Multi-region spatial transcriptomics reveals region specific differences in response to amyloid beta (Aβ) plaque induced changes in Alzheimer’s Disease (AD)
GEO Series GSE304497. Homo sapiens. 8 samples. Type: Other.
Multi-regional Input–output Table for the Global Emerging Economies (EMERGING V2.5)
<p><strong>EMERGING V2.5</strong>: This version removes the 27th sector, totaling 133 sectors, compared to EMERGING1.0. It has been optimized and calibrated to improve the intermediate input matrix (Z matrix), trade volumes (imports and exports), and total output for the electricity, transportation, and energy sectors across 245 economies, with a particular focus on small and medium-sized emerging economies.</p> <p><strong>EMERGING CO<sub>2</sub> Inventory</strong>: CO<sub>2</sub> emissions (Mt CO<sub>2</sub>eq) from fossil fuel combustion and energy consumption at the sectoral level in each region are available from the IEA database and CEADs emission inventory data. The EMERGING CO<sub>2</sub> Inventory includes a total of 7 energy types: 1. Coal; 2. Natural gas; 3. Oil products; 4. Crude, NGL, Ref Feeds.; 5. Other; 6. Oil shale & oil sands; 7. Peat & Peat products.</p> <p><strong>Announcements</strong></p> <p>These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights. The availability of these data does not constitute publication of the data. The data providers rely on the ethics and integrity of the user to ensure that they receive fair credit for their work. If the data are obtained for potential use in a publication or presentation, we kindly ask you to cite them properly according to the instructions on the website.</p> <p>Queries about the EMERGING database and further collaboration can be addressed to: huojw20@hotmail.com</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.