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240
datasets available to search
ShareScore release 0.9.0
Dataset results
240 results for “High resolution maps”
High-throughput single-base resolution mapping of 2’-O-Methylated residues
GEO Series GSE73065. Mus musculus; Homo sapiens. 15 samples. Type: Other.
High resolution mapping reveals links of HP1 with active and inactive chromatin components
GEO Series GSE6564. Drosophila melanogaster. 3 samples. Type: Genome binding/occupancy profiling by genome tiling array.
High resolution methylome map of rat reveals role of intragenic DNA methylation in identifying coding region and alternative splice site.
GEO Series GSE31571. Rattus norvegicus. 2 samples. Type: Methylation profiling by high throughput sequencing.
A high-resolution map of active promoters in the human genome
GEO Series GSE2672. Homo sapiens. 49 samples. Type: Expression profiling by array; Genome binding/occupancy profiling by genome tiling array.
High Resolution Mapping of DNA Copy Alterations in Human Chromosome 22 Using High Density Tiling Oligonucleotide Arrays
GEO Series GSE4240. Homo sapiens. 16 samples. Type: Genome variation profiling by genome tiling array.
[E-MTAB-341] Individual-nucleotide resolution CLIP using high throughput sequencing of human HeLa cells to enable precise mapping of protein-RNA interactions in intact cells
GEO Series GSE25681. Homo sapiens. 1 samples. Type: Other.
High-resolution, genome-wide mapping of positive supercoiling in chromosomes [RNA-seq]
GEO Series GSE152879. Escherichia coli str. K-12 substr. MG1655. 2 samples. Type: Expression profiling by high throughput sequencing.
High-Resolution Mapping of Building Material Stocks in Major Urban Agglomerations in China Based on Multiple Geospatial Data
Open the record for dataset details and reuse information.
High spatial resolution Fractional Vegetation Cover maps OAL-DE (Elbe river). Further details can be found in D4.5 of the OPERANDUM project.
<p>In order to reduce the risk posed by flooding, areas of woody vegetation have been removed along the riverbank of Elbe river in order to expedite the inflow and outflow of water from the main channel, and thus contribute to flattening the peak hydrographic response. Maintaining the effectiveness of this clearing requires that there is little or no regrowth of this woody vegetation. The NBS that have been implemented in OAL-Germany sees the use of various animals to graze these areas. NBS is devoted to prevent the re-growth of woody vegetation after an intervention which took place over a period from autumn 2014 to February 2015, when woody vegetation along the riverbank was cut back. Monitoring the effectiveness of the NBS is being performed by means of high spatial resolution remotely sensed data , i.e. Rapideye at 5 m spatial resolution. The preliminary analysis of this experiment consisted in the monitoring of the fractional vegetation cover over four of the seven NBS sites. </p> <p>The green fractional abundance (fc) was calculated by an algorithm based on scaling NDVI in-between the maximum and minimum NDVI values. A semi-empirical method based on the use of NDVI was used following Zeng et al, (2000), to calculate fc. </p> <p>The dataset contains layer stack of fractional abundance calculated for the images calculated by Rapideye images acquired on 18 April 2013, 15 April 2015, 17 March 2016, 9 April 2019. </p>
Very high resolution Land Cover maps OAL-UK (Catterline)
<p>Surface features are produced as a result of internal deformation of active landslides, and are continuously created and destroyed by the movement. The detailed mapping of the evolution of bare ground patches and vegetation cover pattern over time provides useful insights on the mass movements and the most vulnerable areas. Monitoring the evolution of the latter, in turn, could help to describe the benefits of NBS past their implementation by observing a reduction of vulnerable areas and the increase of the extent of stable vegetation as a result of the interventions.<br> The preliminary analysis of satellite data on OAL-UK was devoted to the analysis of a time series of very high resolution multispectral satellite data (<1 m) in the period prior to the implementation of NBS. The goal was to explore the potential of remote sensing to describe the pattern and extent of vegetation cover and plant cover regeneration, as well as to observe the self-organisation of landslide scars - i.e. re-distribution of bare ground patches over time.</p> <p>The dataset includes Land Cover maps obtained by Worldview 2 satellite images acquired between 2011 and 2016 in different seasons, notably on 29 Jun 2011, 22 April 2014, 08 June 2014 and 22 Feb 2016.</p> <p>After the pre-processing phase, Principal Component Analysis (PCA) was applied on the pansharpened multispectral bands to reduce the dimensionality of each dataset (pansharpened multispectral bands), while retaining as much as possible its information content. (Richardson, 2009).</p> <p>A machine learning unsupervised classification (K-means) was applied to the first three PC found by PCA. K-means is an unsupervised classification algorithm that groups objects into k groups based on their characteristics. The mean spectral reflectance values of the samples assigned to each cluster was analyzed to identify typical spectral profiles of land features as well as eventual similarities between the classes and successively used to assign labels to the unsupervised classes. In cases of spectral similarity between two or three clusters, thy were merged in a unique class. </p> <p>The results of k-means classification were analyzed to define typical spectral profiles of land cover features found in OAL-UK. First, the mean and standard deviation of the spectral bands of each cluster and image were calculated and compared with spectral libraries of land features. This led to identify 11 land cover classes with typical and recurrent spectral profiles within the OAL: </p> <p>1. Bare soil</p> <p>2. urban materials and sea foam (uniform spectra)</p> <p>3. water saturated soil</p> <p>4. water logged soil/vegetation</p> <p>5. vegetation (grass)</p> <p>6. dense vegetation (shrubs)</p> <p>7. vegetation with exposed soil</p> <p>8. soil with sparse vegetation</p> <p>9. mixed wet soil/vegetation</p> <p>10. Water</p> <p>11. Turbid Water</p>
Typical and Atypical AVNRT High-resolution Mapping
ClinicalTrials.gov study NCT04764123. IPD Sharing: Not stated. Countries: 0. Publications: 0.
A Study on the Relationship Between Individualized Low Voltage Regions in Left Atrium and the Mechanism of Atrial Fibrillation in Persistent Atrial Fibrillation Under Ultra-High-Resolution Mapping
ClinicalTrials.gov study NCT06694610. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
High Resolution Mapping of H1 Linker Histone Variants in Embryonic Stem Cells
GEO Series GSE46134. Mus musculus. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
A high-resolution transcriptome map of Ectocarpus siliculosus
GEO Series GSE19912. Ectocarpus siliculosus. 16 samples. Type: Expression profiling by genome tiling array.
Genome-Wide High-Resolution Mapping of Exosome Substrates Reveals Hidden Features in the Arabidopsis Transcriptome
GEO Series GSE9317. Arabidopsis thaliana. 32 samples. Type: Expression profiling by genome tiling array.
High Resolution Mapping and Functional Analysis of the Methylome in Arabidopsis (mCIP, MBD)
GEO Series GSE5094. Arabidopsis thaliana. 24 samples. Type: Methylation profiling by genome tiling array.
High-resolution mapping of the pCAR1 plasmid transcriptomes in Pseudomonas
GEO Series GSE10862. Pseudomonas; Pseudomonas putida; Metapseudomonas resinovorans. 4 samples. Type: Expression profiling by array.
High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias.[RNA-Seq]
GEO Series GSE213684. Homo sapiens. 17 samples. Type: Expression profiling by high throughput sequencing.
High-resolution mapping of transcribing RNAPIII by CRAC upon mutation or depletion of Sen1 [Experiment 1]
GEO Series GSE174698. Saccharomyces cerevisiae. 9 samples. Type: Other.
High-resolution mapping of transcribing RNAPII by CRAC in the presence of different Sen1 variants
GEO Series GSE138448. Saccharomyces cerevisiae. 8 samples. Type: Other.
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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.