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.
1,454
datasets available to search
ShareScore release 0.9.0
Dataset results
1,454 results for “large scale”
Development of a panel of SNP loci in the emblematic southern damselfly (Coenagrion mercuriale) using a hybrid method: Pitfalls and recommendations for large-scale SNP genotyping in a non-model endangered species
Open the record for dataset details and reuse information.
Data from: Large-scale variation in biodiversity–ecosystem functioning (BEF) relationships in aquatic metacommunities on terrestrial islands
Open the record for dataset details and reuse information.
Data from: Large-scale metabarcoding analysis of epipelagic and mesopelagic copepods in the Pacific
Open the record for dataset details and reuse information.
Data from: Large scale variation in birth timing and synchrony of a large herbivore along the latitudinal and altitudinal gradients
Open the record for dataset details and reuse information.
Large-scale exploration of nitrogen utilization efficiency in Asia region for rice crop: variation patterns and determinants
Open the record for dataset details and reuse information.
Unraveling the cavity-nesting network at large spatial scales: The biogeographic role of woodpeckers as ecosystem engineers
Open the record for dataset details and reuse information.
Qualitative survey instruments for a study on equity from a large-scale private-sector healthcare intervention in Ghana and Kenya: the African Health Markets for Equity (AHME) study
Open the record for dataset details and reuse information.
Data from: Temporal scale of habitat selection for large carnivores: Balancing energetics, risk and finding prey
Open the record for dataset details and reuse information.
Ecosystem functions of plant diversity: Comparisons from a large-scale marsh restoration experiment in California, USA
Open the record for dataset details and reuse information.
Impacts of large-scale atmospheric-ocean variability on Alaskan fire season severity
Fire is the keystone disturbance in the Alaskan boreal forest and is highly influenced by summer weather patterns. Records from the last fifty-three years reveal high variability in the annual area burned in Alaska and corresponding high variability in weather occurring at multiple spatial and temporal scales. Here we use multiple linear regression (MLR) to systematically explore the relationships between weather variables and the annual area burned in Alaska. Variation in the seasonality of the atmospheric circulation-fire linkage is addressed through an evaluation of both the East Pacific teleconnection field and a Pacific Decadal Oscillation index keyed to an annual fire index. In the MLR, seven explanatory variables and an interaction term collectively explain 79% of the variability in the natural logarithm of the number of hectares burned annually by lightning-caused fires in Alaska from 1950-2003. Average June temperature alone explains one-third of the variability in the logarithm of annual area burned. The results of this work suggest that the Pacific Decadal Oscillation and the East Pacific teleconnection indices can be useful in determining a priori an estimate of the number of hectares that will burn in an upcoming season. This information also provides insight into the link between ocean-atmosphere interactions and the fire disturbance regime in Alaska.
Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologie
<p>This file contains the sources that were used to create the feature comparison in "Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologies".</p>
PacBio Simulation CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 2 of 2)
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
PacBio Simulation CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 1 of 2)
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
10XG CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 1 of 2)
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
Illumina CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 2 of 2)
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
Illumina CRAM files for "Characterization of large-scale structural variants using Linked-Reads" (Part 1 of 2)
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
Data file for paper: Javier Rubio-Garcia; Anthony R J Kucernak, Rutao Liu and Barun K Chakrabarti "Hydrogen/functionalized benzoquinone for a high-performance regenerative fuel cell as a potential large-scale energy storage platform"
<p>The data in this spreadsheet was used to produce the figures in the paperJavier Rubio-Garcia; Anthony R J Kucernak, Rutao Liu and Barun K Chakrabarti "Hydrogen/functionalized benzoquinone for a high-performance regenerative fuel cell as a potential large-scale energy storage platform"Journal of Materials Chemistry A, 2020, DOI: 10.1039/C9TA12396B</p> <p>Please cite the above reference if you wish to use this data</p>
Dataset for Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study
<p>This dataset contains all the spectra used in "Surface Enhanced Raman Spectroscopy for quantitative analysis: results of a large-scale European multi-instrument interlaboratory study". Data are available in 2 different formats:</p> <p>- a compressed archive with 1 folder ("Dataset”) cointaining all the 3516 TXT files (1 file = 1 spectrum) uploaded by all participants (all spectra of the Interlaboratory study);</p> <p>- 1 single CSV file (“ILSspectra.csv”) with all the 3516 spectra uploaded by all participants in the form of a table. The data are structured as follow, with each row being 1 spectrum, preceded by metadata: "labcode", "substrate", "laser", "method", "sample", "type", "conc", "batch", "replica". Note that for those spectra starting after 400 cm-1 and/or ending before 2000 cm-1 missing values were expressed as NAs.</p>
Characterization of large-scale structural variants using Linked-Reads
<p>Here we propose novel algorithms to characterize large (>40 Kbp) interspersed segmental duplications, (> 80 Kbp) inversions, (> 100 Kbp) deletions, and (> 100 Kbp) translocations using Linked-Read sequencing data. Linked-Read sequencing provides long range information, where Illumina reads are tagged with barcodes that can be used to assign short reads to pools of larger (30-50 Kbp) molecules.</p> <p><br> Our methods rely on split molecule sequence signature that we have previously described. Similar to the split read, split molecules refer to large segments of DNA that span an SV breakpoint. Therefore, when mapped to the reference genome, the mapping of these segments would be discontinuous.</p> <p><br> We redesign our earlier algorithm, VALOR, to specifically leverage Linked-Read sequencing data to discover large <br> structural variation. We implement our new algorithms in a new software package, called VALOR2. </p>
Dataset - Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies
<p>Models developed for the manuscript “Large-scale kinetic metabolic models of<em> Pseudomonas putida</em> for consistent design of metabolic engineering strategies" by M. Tokic, V. Hatzimanikatis, and L. Miskovic.</p> <ul> <li>Thermodynamically curated and gap-filled genome-scale model of <em>P. putida</em> iJN1411, iJN1411cur. <ul> <li>CuratediJN1411GEM.mat</li> </ul> </li> <li>Three systematically reduced stoichiometric models of <em>P. putida</em>: <ul> <li>D1 model, RedModelD1SminP2.mat</li> <li>D2 model, RedModelD2SminP2.mat - used for the studies performed in the manuscript</li> <li>D3 model, RedModelD3SminP2.mat</li> </ul> </li> </ul> <p> </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.