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ShareScore release 0.9.0
Dataset results
202 results for “v7”
TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7 (TRMM_3B43) at GES DISC
TMPA (3B43) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERG/3B-MONTH/06).The 3B43 dataset is the monthly version of the 3B42 dataset.This product was created using TRMM-adjusted merged microwave-infrared precipitation rate (in mm/hr) and root-mean-square (RMS) precipitation-error estimates.It provides a "best" precipitation estimate in a latitude band covering 50o N to 50o S, an expansion of the TRMM region, from all global data sources, namely high-quality microwave data, infrared data, and analyses of rain gauges. The granule size is one month.
TRMM (TMPA) Rainfall Estimate L3 3 hour 0.25 degree x 0.25 degree V7 (TRMM_3B42) at GES DISC
TMPA (3B42) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERG/3B-HH/06).This dataset was the output from the TMPA (TRMM Multi-satellite Precipitation Analysis) Algorithm. It provides precipitation estimates in the TRMM regions that have the (nearly-zero) bias of the ”TRMM Combined Instrument” precipitation estimate and the dense sampling of high-quality microwave data with fill-in using microwave-calibrated infrared estimates. The granule temporal coverage is 3 hours.
RSS SSM/I OCEAN PRODUCT GRIDS WEEKLY AVERAGE FROM DMSP F13 NETCDF V7
The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F13 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data products produced as part of NASA's MEaSUREs Program. Remote Sensing Systems generates SSM/I and SSMIS binary data products using a unified, physically based algorithm to simultaneously retrieve ocean wind speed, water vapor, cloud water, and rain rate. The SSMIS data have been carefully intercalibrated to the brightness temperature level of the previous SSM/I and therefore extend this important time series of ocean winds, vapor, cloud and rain values. This algorithm is a product of 20 years of refinements, improvements, and verifications. The Global Hydrology Resource Center has reformatted the binary data into a netCDF data product for each temporal group for each satellite. The netCDF SSMI/SSMIS collection will be available for F13 for weekly averages.
TRMM (TMPA) Precipitation L3 1 day 0.25 degree x 0.25 degree V7 (TRMM_3B42_Daily) at GES DISC
TMPA (3B42_Daily) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERGDF/DAY/06).This daily accumulated precipitation product is generated from the research-quality 3-hourly TRMM Multi-Satellite Precipitation Analysis TMPA (3B42). It is produced at the NASA GES DISC, as a value added product. Simple summation of valid retrievals in a grid cell is applied for the data day. The result is given in (mm). The beginning and ending time for every daily granule are listed in the file global attributes, and are taken correspondingly from the first and the last 3-hourly granules participating in the aggregation. Thus the time period covered by one daily granule amounts to 24 hours, which can be inspected in the file global attributes. Counts of valid retrievals for the day are provided for every variable, making it possible to compute conditional and unconditional mean precipitation for grid cells where less than 8 retrievals for the day are available.Efforts have been made to make the format of this derived product as similar as possible to the new Global Precipitation Measurement CF-compliant file format.The information provided here on the TRMM mission, and on the original 3-hr 3B42 product, remain relevant for this derived product. Note, however, this product is in netCDF-4 format.The following describes the derivation in more details.The daily accumulation is derived by summing *valid* retrievals in a grid cell for the data day. Since the 3-hourly source data are in mm/hr, a factor of 3 is applied to the sum. Thus, for every grid cell we have Pdaily = 3 * SUM{Pi * 1[Pi valid]}, i=[1,Nf]Pdaily_cnt = SUM{1[Pi valid]}where:Pdaily - Daily accumulation (mm)Pi - 3-hourly input, in (mm/hr)Nf - Number of 3-hourly files per day, Nf=81[.] - Indicator function; 1 when Pi is valid, 0 otherwisePdaily_cnt - Number of valid retrievals in a grid cell per day.Grid cells for which Pdaily_cnt=0, are set to fill value in the Daily files.Note that Pi=0 is a valid value.On occasion, the 3-hourly source data have fill values for Pi in a very few grid cells. The total accumulation for such grid cells is still issued, inspite of the likelihood that thus resulting accumulation has a larger uncertainty in representing the "true" daily total. These events are easily detectable using "counts" variables that contain Pdaily_cnt, whereby users can screen out any grid cells for which Pdaily_cnt less than Nf.There are various ways the accumulated daily error could be estimated from the source 3-hourly error. In this release, the daily error provided in the data files is calculated as follows. First, squared 3-hourly errors are summed, and then square root of the sum is taken. Similarly to the precipitation, a factor of 3 is finally applied:Perr_daily = 3 * { SUM[ (Perr_i * 1[Perr_i valid])^2 ] }^0.5 , i=[1,Nf]Ncnt_err = SUM( 1[Perr_i valid] )where:Perr_daily - Magnitude of the daily accumulated error power, (mm)Ncnt_err - The counts for the error variableThus computed Perr_daily represents the worst case scenario that assumes the error in the 3-hourly source data, which is given in mm/hr, accumulates first within the 3-hour period of the source data, and then continues to accumulate during the day. These values, however, can easily be converted to root mean square error estimate of the rainfall rate:rms_err = { (Perr_daily/3) ^2 / Ncnt_err }^0.5 (mm/hr)This estimate assumes that the error given in the 3-hourly files is representative of the error of the rainfall rate (mm/hr) within the 3-hour window of the files, and it is random throughout the day. Note, this should be interpreted as the error of the rainfall rate (mm/hr) for the day, not the daily accumulation.
RSS SSM/I OCEAN PRODUCT GRIDS MONTHLY AVERAGE FROM DMSP F14 NETCDF V7
The RSS SSM/I Ocean Product Grids Monthly Average from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data products produced as part of NASA's MEaSUREs Program. Remote Sensing Systems generates SSM/I and SSMIS binary data products using a unified, physically based algorithm to simultaneously retrieve ocean wind speed, water vapor, cloud water, and rain rate. The SSMIS data have been carefully intercalibrated to the brightness temperature level of the previous SSM/I and therefore extend this important time series of ocean winds, vapor, cloud and rain values. This algorithm is a product of 20 years of refinements, improvements, and verifications. The Global Hydrology Resource Center has reformatted the binary data into a netCDF data product for each temporal group for each satellite. The netCDF SSMI/SSMIS collection will be available for F14 for a monthly average.
TRMM (TMPA-RT) Near Real-Time Precipitation L3 3 hour 0.25 degree x 0.25 degree V7 (TRMM_3B42RT) at GES DISC
TMPA (3B42RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream. The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product.Each file is a snapshot considered to represent the three-hour period centered on the "nominal" file time. So, e.g., 00 UTC nominally represents the period from 2230 UTC of the previous day to 0130 UTC of the current day. Estimates outside the band 50 degree N-S are considered highly experimental. GES DISC initially receives these data from the Precipitation Processing System (PPS) in binary format. However, before archiving, the data are scaled to real numbers, and re-arranged to a standard grid so that the first grid cell is at 180W, 60S. Thus formatted, data are stored into CF-1.6 compliant netCDF-4 files and archived. This format is machine-independent, self-explanatory, provides extremely efficient seamless compression, and gives various options for previewing the data without downloading it.Apart from these technical differences, all other science content details remain the same, and users are strongly encouraged to read the provider's documentation that is linked to from here.
Aqua/AIRS L2 Support Retrieval (AIRS+AMSU) V7.0 at GES DISC
The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU), AIRS constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The Support Product includes higher vertical resolution profiles of the quantities found in the Standard Product plus intermediate output (e.g., microwave-only retrieval), research products such as the abundance of trace gases, and detailed quality assessment information. The Support Product profiles contain 100 pressure levels between 1100 and .016 mb; this higher resolution simplifies the generation of radiances using forward models, though the vertical information content is no greater than in the Standard Product profiles. The horizontal resolution is 50 km. The intended users of the Support Product are researchers interested in generating forward radiance, or in examining research products, and the AIRS algorithm development team. The Support Product is generated at all locations as Standard Products. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
Aqua/AIRS L2 Near Real Time (NRT) Standard Physical Retrieval (AIRS-only) V7.0 at GES DISC
The Atmospheric Infrared Sounder (AIRS) Level 2 Near Real Time (NRT) Standard Physical Retrieval (AIRS-only) product (AIRS2RET_NRT_7.0) differs from the routine product (AIRS2RET_7.0) in four ways to meet the three hour latency requirements of the Land Atmosphere NRT Capability Earth Observing System (LANCE): (1) The NRT granules are produced without previous or subsequent granules if those granules are not available within 5 minutes, (2) the predictive ephemeris/attitude data are used rather than the definitive ephemeris/attitude, (3) if the forecast surface pressure is unavailable, a surface climatology is used, and (4) no ice cloud properties retrievals are performed. The consequences of these differences are described in the AIRS Near Real Time (NRT) data products document. The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. This product is produced using AIRS IR only because the radiometric noise in several AMSU channels started to increase significantly (since June 2007). The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. Estimates of the errors associated with these quantities is also part of the Standard Product. The temperature profile vertical resolution is 28 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at 14 atmospheric layers between 1100 mb and 50 mb. The horizontal resolution is 50 km. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
Expression profiling by RNA-seq of LNCaP cells expressing wild-type androgen receptor (AR-WT), AR-V7 splice variant or mutant AR-Q641X
GEO Series GSE158557. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Androgen Receptor splice variant V7 (AR-V7) mediates AR signalling in castration resistant prostate cancer (CRPC) [RNA-seq]
GEO Series GSE143905. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Diverse AR-V7 cistromes in castration-resistant prostate cancer are governed by HoxB13
GEO Series GSE99378. Homo sapiens. 40 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
A Novel Peptide Encoded by circSRCAP Confers Resistance to Enzalutamide by Inhibiting the Ubiquitin-Dependent Degradation of AR-V7 in Castration-Resistant Prostate Cancer
GEO Series GSE264133. Homo sapiens. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Heterogeneity of Androgen Receptor Splice Variant-7 (AR-V7) Protein Expression and Response to Therapy in Castration Resistant Prostate Cancer (CRPC)
GEO Series GSE118435. Homo sapiens. 41 samples. Type: Expression profiling by high throughput sequencing.
AR-V7 targets the oncogenic genes in castration resistant prostate cancer. [RNA]
GEO Series GSE122923. Homo sapiens. 21 samples. Type: Expression profiling by high throughput sequencing.
KIF15 promotes AR and AR-V7 protein stabilization in contribution to enzalutamide resistance of prostate cancers
GEO Series GSE150896. Homo sapiens. 8 samples. Type: Expression profiling by array; Expression profiling by high throughput sequencing.
Transcriptome analyses of AR-V7 and ARv567es
GEO Series GSE221141. Homo sapiens. 28 samples. Type: Expression profiling by high throughput sequencing.
Role of androgen receptor splice variant 7 (AR-v7) in prostate cancer resistance to 2nd generation androgen receptor signaling inhibitors
GEO Series GSE149433. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome profiling of castration-resistant prostate cancer cells treated with novel androgen receptor (AR) and AR-V7 inhibitors
GEO Series GSE158556. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Comparison of gene expression by microarray in diabetes antigen specific (NRP-V7), LCMV antigen specific (GP33), and CD8+ T cells of similar phenotype from NOD mice
GEO Series GSE79200. Mus musculus; Mus sp.. 11 samples. Type: Expression profiling by array.
Cabazitaxel in mCRPC Patients With AR-V7 Positive Circulating Tumor Cells (CTCs)
ClinicalTrials.gov study NCT03050866. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
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.