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Dataset results
486 results for “Hierarchical”
Data from: Selective pressures on MHC class II genes in the guppy (Poecilia reticulata) as inferred by hierarchical analysis of population structure.
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Data from: Geometric morphometrics of nested symmetries unravels hierarchical inter- and intra-individual variation in biological shapes
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Data from: Bridging inter- and intraspecific trait evolution with a hierarchical Bayesian approach
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Data from: Reconciling hierarchical taxonomy with molecular phylogenies
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Data from: Metacommunity structure of stream insects across three hierarchical spatial scales
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Hierarchical genetic structure and implications for conservation of the world’s largest salmonid, Hucho taimen
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Hierarchical Bayesian scaling of soil properties across urban, agricultural, and desert ecosystems in central Arizona-Phoenix
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Hierarchical spatial modeling of multiple soil nutrients and carbon in heterogeneous landuse patches of the central Arizona-Phoenix research area, from 1999 to 2006.
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International Satellite Cloud Climatology Project (ISCCP) Stage D1 3-Hourly Cloud Products - Revised Algorithm in Hierarchical Data Format
ISCCP_D1_1 is the International Satellite Cloud Climatology Project (ISCCP) Stage D1 3-Hourly Cloud Products - Revised Algorithm data set in Hierarchical Data Format. This data set contains 3-hourly, 280 KM equal-area grid data from various polar and geostationary satellites. The Gridded Cloud Product contents are spatial averages of DX quantities and statistical summaries, including properties of cloud types. Satellites are merged into a global grid. Atmosphere and surface properties from TOVS are appended. Data collection for this data set is complete. ISCCP, the first project of the World Climate Research Program (WCRP), was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to: produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. Starting in 1983 an international group of institutions collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onward) the analysis also concerns improving understanding of clouds in the global hydrological cycle. The ISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis was performed separately for each satellite radiance data set and the results were reported in the Stage DX data product, which had a nominal resolution of 30 km and 3 hours. The Stage D1 product was produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product was produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.
International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Products - Revised Algorithm in Hierarchical Data Format
The ISCCP_D2 data set contains monthly, 280 KM equal-area grid data from various polar and geostationary satellites. Climatological Summary Product contents contain monthly average of D1 quantities including mean diurnal cycle, distribution and properties of total cloudiness and cloud types.The International Satellite Cloud Climatology Project (ISCCP), the first project of the World Climate Research Program (WCRP), was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983): - To produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived. - To stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models. - To promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. The ISCCP analysis combines satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determines the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.
Hierarchical RNA processing is rate limiting for mitochondrial ribosome assembly
GEO Series GSE83471. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing; Other.
Hierarchical roles of mitochondrial PAPI and Zucchini in Bombyx germline piRNA biogenesis
GEO Series GSE107371. Bombyx mori. 8 samples. Type: Other; Non-coding RNA profiling by high throughput sequencing.
Chromatin architecture in hexaploid wheat is hierarchically organized around genome territories and transcription factories (Wheat_RNAseq)
GEO Series GSE133884. Triticum aestivum. 3 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide characterization of light-inducible responses reveals a hierarchical light-sensing cascade in N. crassa
GEO Series GSE8932. Neurospora crassa. 135 samples. Type: Expression profiling by array.
SND1 Transcription Factor-Directed Quantitative Functional Hierarchical Genetic Regulatory Network in Wood Formation in Populus trichocarpa
GEO Series GSE49911. Populus trichocarpa. 18 samples. Type: Expression profiling by high throughput sequencing.
HALO: Hierarchical Causal Modeling for Single Cell Multi-Omics Data
GEO Series GSE302151. Homo sapiens. 31 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
TADs emerge as a functionally, but not structurally privileged scale in the hierarchical folding of chromosomes
GEO Series GSE84724. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
A hierarchical regulatory network ensures stable albumin transcription under various pathophysiological conditions
GEO Series GSE181201. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Hierarchical mechanisms for transcription factor-mediated reprogramming of fibroblasts to neurons
GEO Series GSE43916. Mus musculus; Homo sapiens. 38 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition, based on hierarchical binding affinities
GEO Series GSE61348. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing; Other.
ScienceDex guides
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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.