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1,574
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ShareScore release 0.9.0
Dataset results
1,574 results for “atmospheres”
The alteration of gene expression in fulvestrant resistant breast cancer cell by cold atmospheric plasma (CAP)
GEO Series GSE300391. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Effect of Cold Atmospheric Microwave Plasma (CAMP) on wound healing in canine keratinocytes
GEO Series GSE222898. Canis lupus familiaris. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of iPSC and ESC challenged with atmospheric or physiological oxygen
GEO Series GSE126785. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
High Concentrations of Atmospheric Ammonia Induce Alterations of Gene Expression in the Breast Muscle of Broilers (Gallus gallus) Based on RNA-Seq
GEO Series GSE84099. Gallus gallus. 6 samples. Type: Expression profiling by high throughput sequencing.
Cold atmospheric plasma affects stem cell renewal and differentiation and is associated with a regeneration process in an intestinal organoid culture model
GEO Series GSE178148. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis to underly the heterogeneity between 4 cellular models derived from patients diagnosed with pediatric high-grade gliomas under controlled atmosphere (modulation of oxygen level
GEO Series GSE101799. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Effect of cold atmospheric plasma (CAP) in MCF-7
GEO Series GSE131480. Homo sapiens. 7 samples. Type: Expression profiling by array.
Cold atmospheric plasma reprograms the drug sensitivity of Tamoxifen-resistant MCF-7 breast cancer cell
GEO Series GSE95208. Homo sapiens. 3 samples. Type: Expression profiling by array.
Impact of heavy atmospheric pollution on the transcriptome of Escherichia coli BW25113 and the adapted E. coli strain T56-1
GEO Series GSE115330. Escherichia coli BW25113. 12 samples. Type: Expression profiling by high throughput sequencing.
Effect of cold atmospheric plasma (CAP) in MCF-7 breast cancer cells [dataset 1]
GEO Series GSE131477. Homo sapiens. 3 samples. Type: Expression profiling by array.
RNA sequencing analysis of gene expression in non-thermal atmospheric pressure plasma (NTAPP)-exposed and -unexposed human adipose tissue-derived stem cells (ASC) [Ex.2]
GEO Series GSE131385. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Effect of cold atmospheric plasma (CAP) in MCF-7 breast cancer cell [dataset 3]
GEO Series GSE131479. Homo sapiens. 2 samples. Type: Expression profiling by array.
Effects of atmospheric ammonia on the production performance, serum biochemical indices, and liver RNA-seq data of laying ducks
GEO Series GSE144924. Anas platyrhynchos. 6 samples. Type: Expression profiling by high throughput sequencing.
Atmospheric forcing dataset for Numerical study of the seasonal thermal and gas regimes of the large artificial lake in Western Europe using LAKE2.0
<p>Input dataset for the LAKE2.0 model (http://tesla.parallel.ru/Viktor/LAKE/wikis/LAKE-model) that was used for the experiments in the "Numerical study of the seasonal thermal and gas regimes of the large artificial lake in Western Europe using LAKE2.0" article. Archive contains the atmospheric forcing file itself, file with the header description, and the setup and driver files for the LAKE2.0 model.</p> <p>Source code of the current version of the LAKE2.0 model used in the work mentioned above, pre-compiled exec of the FLake model as well as its source code (freely available under the terms of the MIT license) are also provided as separate archive files.</p> <p> </p>
GOES-16 cloud-motion wind and ASCAT ocean surface wind data for the article "Evolution of an atmospheric Kármán vortex street from high-resolution satellite winds: Guadalupe Island case study"
<p>This repository contains GOES-16 cloud-motion winds and ASCAT ocean surface winds derived for and analysed in the article "Evolution of an atmospheric Kármán vortex street from high-resolution satellite winds: Guadalupe Island case study".</p> <p> </p> <p><strong>GOES-16 Local Cloud-Motion Vectors</strong></p> <p>Data in two ASCII text files: <em>raw5x5g16b2_2018d129_1437z_2232z_north.txt</em> and <em>raw5x5g16b2_2018d129_1437z_2232z_south.txt</em>, with the former containing data for the upper half and the latter for the lower half of the study domain between ~26<sup>o</sup>N and ~29.5<sup>o</sup>N. Both files include 96 records, each record corresponding to a specific 5-minute time interval between 14:37 UTC and 22:32 UTC on 9 May 2018—9 May is day of year 129. The start and end times are given at the beginning of each record in YYYYDDDHHMM format, where Y is year, D is day of year, H is hour, and M is minute. For example, the first record contains data between 14:37 UTC and 14:42 UTC, as indicated by the start and end times of 20181291437 and 20181291442. Then follows the four column headers LAT LON SPD DIR, corresponding to latitude (degree), longitude (degree), wind speed (m/s), and wind direction (meteorological convention, degree north), respectively—note that no cloud-top height/pressure value was calculated for the wind vectors. Each subsequent line is a single GOES-16 local cloud-motion vector, derived from 5x5-pixel band 2 (0.64 micron visible red band) image templates, which represent an area of ~2.5x2.5 km<sup>2</sup> at the subsatellite point.</p> <p> </p> <p><strong>MODIS–GOES-16 3D Cloud-Motion Vectors</strong></p> <p>Data in two netCDF files: <em>MOD.A2018129.1810-75_ABI_CONUS_band_02_goes16.nc</em> and <em>MYD.A2018129.2120-75_ABI_CONUS_band_02_goes16.nc</em>, which correspond to the MODIS Terra and MODIS Aqua overpasses, respectively. These joint MODIS–GOES-16 wind retrievals were derived using ~8x8 km<sup>2</sup> red band image templates sampled every 2 km. The data files are self-explanatory, but the variables "lat", "lon", "V_3D", and "H_3D" provide the latitude (degree), longitude (degree), the [east-west, north-south] wind components (m/s), and the geometric stereo height (m) for each wind retrieval.</p> <p> </p> <p><strong>ASCAT Ocean Surface Wind Vectors</strong></p> <p>Data in two netCDF files: <em>ascat_20180509_030000_metopa_59945_srv_o_063_ovw_new.nc</em> and <em>ascat_20180509_040000_metopb_29259_srv_o_063_ovw_new.nc</em>, which correspond to the MetOp-A and MetOp-B overpasses, respectively. These ASCAT ocean surface retrievals are stress-equivalent winds at 10 m height, given on a 6.25-km grid. The data files are self-explanatory, but the variables "lat", "lon", "wind_speed", and "wind_dir" provide the latitude (degree), longitude (degree), the wind speed (m/s), and the wind direction (oceanographic convention, degree north) for each wind retrieval. <em>Note that wind direction follows the oceanographic convention and refers to the direction towards which the wind blows (equivalent to meteorological wind direction minus 180<sup>o</sup>)!</em></p>
Supporting Data for "Disentangling the coupled atmosphere-ocean-ice interactions driving Arctic sea ice response to CO2 increases"
<p>Supporting data for "Disentangling the coupled atmosphere-ocean-ice interactions driving Arctic sea ice response to CO2 increases", submitted to Journal of Advances in modelling Earth system</p> <p>Monthly averaged sea ice variables for the 100 and 150 year fully coupled (b.e11.B1850C5CN.f09_g16.abrupt4xco2.full.ice.100101_110012.nc) and partially coupled experiments (b.e11.B1850C5CN.f09_g16.abrupt4xco2.partial.ice.100101_115012.nc)</p> <p>ocean surface temperature and the melt and growth ocean-ice heat fluxes and their surface- and circulation-driven components are available at https://doi.org/10.5281/zenodo.3593507</p> <p>Control experiment data is available on the NCAR HPSS /CCSM/csm/b.e11.B1850C5CN.f09_g16.005</p>
Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model"
<p>Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model" in JGR-Atmospheres (2020). </p> <p>Output are NetCDF files containing annual means (named 'yearmean', 2007-2013), or multi-annual monthly means ('ymonmean', 2007-2012) of various variables that are of interest and/or used for analysis in this study. The file name starts with the variable name. Fields are global, at a resolution of 0.9 x 1.25 degrees latitude/longitude.</p> <p>The test simulations are named (as discussed in the paper):</p> <p>cam4_clm5<br> cam5_clm5<br> cam6_noicenucl_clm5<br> cam6_noclubb_clm5<br> cam6_mg1_clm5<br> cam6</p>
Supplementary data for: "The Venusian atmospheric oxygen ion escape: Extrapolation to the early Solar System"
<p>Supplementary data for paper "The Venusian atmospheric oxygen ion escape: Extrapolation to the early Solar System", submitted to Journal of Geophysical Research: Planets. See README file for description of the data in each file.</p>
Data for "Abrupt transitions in an atmospheric single-column model with weak temperature gradient approximation"
<p>These are the main output files for the experiment studied in the paper "Abrupt transitions in a single-column model with weak temperature gradient approximation". File names and descriptions are as follows:</p> <ol> <li>hysteresis.mat: A MATLAB file that contains WRF output from the hysteresis test used to create Figure 5 of the paper. The variable names should be straightforward to someone familiar with WRF. (Full WRF output was not saved for these runs.)</li> <li>input_soil: surface initial conditions for WRF SCM, same for all experiments</li> <li>input_sounding: initial sounding, same for all experiments</li> <li>main_fls1: a WTG SST-ramping experiment showing <span class="math-tex">\(f_{\rm LS}\to 1\)</span> as described in the paper.</li> <li>main_rce_ramp: a SST-ramping experiment without the weak temperature gradient approximation</li> <li>namelist.input.rce: the namelist input file for the "rce_run" experiment</li> <li>namelist.input.wtg: the namelist input files for the "wtg_ramp_run1" experiment</li> <li>rce_run: the main RCE experiment used to create the background WTG profile for the wtg_ramp_run1 experiment and the wtg_noramp experiment</li> <li>wtg_noramp: a 180-day experiment with WTG but no ramping, for comparison</li> <li>wtg_ramp_run1: the main WTG ramping experiment showing the abrupt transitions</li> </ol> <p> </p>
New evidence for atmospheric mercury transformations in the marine boundary layer
<p>including Isotopic and concentration measurement results, QA/QC, measurement results of Hg and Br on particles, and GIS files for mapping.</p>
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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.