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358
datasets available to search
ShareScore release 0.9.0
Dataset results
358 results for “dataset generation”
Transcriptome analysis of wildtype elmo2+/+ and homozygous elmo2-/- knockout zebrafish larvae at 120 hpf through next generation RNA sequencing [dataset 2]
GEO Series GSE197825. Danio rerio. 12 samples. Type: Expression profiling by high throughput sequencing.
Generation of CNS neural stem cells and PNS derivatives from neural crest derived peripheral stem cells [Dataset 2]
GEO Series GSE57001. Mus musculus. 6 samples. Type: Expression profiling by array.
Supplementary Information datasets: Evaporation Reduction and Energy Generation Potential using Floating Photovoltaic Power Plants on the Aswan High Dam Reservoir
<p>These files contain supplementary information regarding the "Evaporation Reduction and Energy Generation Potential using Floating Photovoltaic Power Plants on the Aswan High Dam Reservoir"</p>
Datasets for the article "Redox melting of garnet lherzolite: Generation of carbonated silicate and sulfide melts and implications for OIB formation from chalcophile and redox-sensitive elements"
Open the record for dataset details and reuse information.
Generation of CNS neural stem cells and PNS derivatives from neural crest derived peripheral stem cells [Dataset 1]
GEO Series GSE56999. Mus musculus. 9 samples. Type: Expression profiling by array.
Generation of multi-omic datasets using high-throughput molecular profiling of DNA methylation human data
GEO Series GSE281305. Homo sapiens. 40 samples. Type: Methylation profiling by genome tiling array.
Dataset related to the article:"Generation of the Becker muscular dystrophy patient derived induced pluripotent stem cell line carrying the DMD splicing mutation c.1705-8 T>C."
<p>This record contains raw data related to the article: "Generation of the Becker muscular dystrophy patient derived induced pluripotent stem cell line carrying the DMD splicing mutation c.1705-8 T>C."</p> <p>Abstract:</p> <p>Becker Muscular dystrophy (BMD) is an X-linked syndrome characterized by progressive muscle weakness. BMD is generally less severe than Duchenne Muscular<br> Dystrophy. BMD is caused by mutations in the dystrophin gene that normally give rise to the production of a truncated but partially functional dystrophin protein. We<br> generated an induced pluripotent cell line from dermal fibroblasts of a BMD patient carrying a splice mutation in the dystrophin gene (c.1705-8 T>C). The iPSC cellline<br> displayed the characteristic pluripotent-like morphology, expressed pluripotency markers, differentiated into cells of the three germ layers and had a normal<br> karyotype.</p>
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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2017-2018)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2011-2012)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2009-2010)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2007-2008)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2005-2006)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2019-2020)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2003-2004)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (Samples)
<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>
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2015-2016)
<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>
A Dataset of Questionnaire on the Domestic Image of China and Media Use for China's Post-90s Generation
<p><a name="OLE_LINK1"></a><span>The dataset consists of 5 files:</span></p> <p><span><span>(1) Readme-China-Post90s.pdf</span></span></p> <p><span><span>(2) Questionnaire-China-Post90s.pdf</span></span></p> <p><span><span>(3) Questionnaire-China-Post90s-CN.pdf</span></span></p> <p><span><span>(4) SurveyData-China-Post90s.csv</span></span></p> <p><span><span>(5) SurveyData-China-Post90s.xlsx</span></span></p> <p>Please see Readme file “Readme-China-Post90s.pdf”.</p>
dataset relate to article "A hypothesis for the role of axon demyelination in seizure generation"
<p>Dataset contains raw data underlying figures 1,2 and 3 included in the publication mentioned at title</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.