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30,948 results for “Profile”
Supplementary data for: Comparison of transcriptomic profiles between HFPO-DA and prototypical PPARa, PPARg, and cytotoxic agents in wild-type and PPARa knockout mouse hepatocytes
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Physics-informed neural networks (PINNs) with unsaturated water flow models for inverse analysis of soil hydraulic parameters of layered soil profiles
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Data from: Repetitive DNA profiles reveal evidence of rapid genome evolution and reflect species boundaries in ground beetles
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Data from: Whole blood transcriptional profiles and the pathogenesis of tuberculous meningitis
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Data from: Tissue-specific O-GlcNAcylation profiling identifies substrates in translational machinery in the Drosophila mushroom body contributing to olfactory learning
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Supplementary data for: Comparison of transcriptomic profiles between HFPO-DA and prototypical PPARa, PPARg, and cytotoxic agents in mouse, rat, and pooled human hepatocytes
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Data from: What goes in must come out? The metabolic profile of plants and caterpillars, frass, and adults of Asota (Erebidae: Aganainae) feeding on Ficus (Moraceae) in New Guinea
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Low-level updraft intensification in response to environmental wind profiles
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Synthetic bulk RNA-Seq transcriptomic profiles representing 10 Cancer hallmarks
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Data from: Turbulence organization and mean profile shapes in the stably stratified boundary layer: Zones of uniform momentum and air temperature
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Berkeley High Resolution (BEHR) OMI NO2 - Gridded pixels, daily profiles
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Berkeley High Resolution (BEHR) OMI NO2 - Native pixels, monthly profiles
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Berkeley High Resolution (BEHR) OMI NO2 - Gridded pixels, monthly profiles
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Berkeley High Resolution (BEHR) OMI NO2 - Native pixels, daily profiles
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University of Kansas Field Station: Water temperature profiles at Frank B. Cross Reservoir (Kansas, USA) 1993-2016
These vertical profiles of water temperature data are from Frank B. Cross Reservoir, a small freshwater impoundment in northeastern Kansas (USA). Cross Reservoir, located at the University of Kansas Field Station near Lawrence (KS), has a 3-ha surface area and a maximum depth of 12 m. Temperature data were collected at discrete depths in a vertical profile using a Water Quality Checker U-10 (Horiba Instruments, Kyoto, Japan). These temperature data were collected in conjunction with ecological studies at Cross Reservoir examining deep-dwelling, vertically-migrating phytoplankton communities that form a deep chlorophyll maxima, especially during times of thermal stratification. Therefore, the most frequent sampling dates occurred in July, August, September and October during thermal stratification when vertically migrating deep algae were most common (other months were sampled less frequently through the years). Cross Reservoir has high water clarity due to its watershed vegetation and physical (protected) setting. Thermal stratification begins each year in April, and complete mixing occurs during November. The bottom of the epilimnion is typically located at 3 m in July and usually deepens to approximately 9 m by late November. The bottom of the epilimnion is defined here as the bottom of the first 1 m depth interval that exhibited a >1 C temperature decrease per meter. The water column also consistently exhibits strong chemical stratification during the summer months. Sporadic ice cover can occur during December–February.
Dataset on sub-daily vertical profiles of physicochemical parameters and chlorophyll concentration in El Val reservoir, together with its daily meteorological data, storage state and downstream flow (2018-2022).
This dataset contains the physicochemical parameters and chlorophyll concentration of El Val reservoir (province of Zaragoza, Spain), together with its meteorological conditions, the water level, the stored volume and the flow rate of the effluent, the Queiles River, a few meters downstream of the dam. These data are useful to feed deterministic, data driven or hybrid hydrological models with different purposes, like the identification of the impact of meteorological conditions on the physicochemical properties of the reservoir, like the thermal stratification, as well as the assessment of different management strategies in the reservoir. The original data were collected by the Confederación Hidrográfica del Ebro (CHE) and were published in real time through the web page of the Ebro Automatic Water Quality Information System (SAICA Ebro by its initials in Spanish) and the Ebro Automatic Hydrographic Information System (SAIH Ebro by its initials in Spanish). Then, the CHE curated the data that are finally available to the citizens under request by variable and date. In order to facilitate their availability and reuse, these data have been gathered, pre-processed and packaged in the form of datasets. Specifically, they are structured in four data tables: vertical profiles of physicochemical data in the reservoir, meteorological data in the same basin, water level and stored water volume in the reservoir and water flow rate of the Queiles River downstream of the reservoir.
Mono Lake, California water temperature depth profiles (0.5-m depth intervals) collected at multiple stations from 1991-2022 with conductivity-temperature-depth profilers.
Water temperature profiles collected at buoyed stations in Mono Lake with conductivity-temperature-depth (CTD) profiles from 1991 to 2022. Data from 1991 to June 2012 collected and archived by Jellison & Melack (UCSB). Data from July 2012 to 2022 collected by the Los Angeles Department of Water and Power and are available in annual compliance reports submitted to the California State Water Resources Control Board.
Proprietary Sub Bottom Profiler Data for Lake Mendota
This study aims to create a three-dimensional sediment profile map of Lake Mendota, located in Dane County, WI, using subbottom profiling (SBP). Knowing the location, quantity, and relative composition of the sediments will give us lake-wide relative deposition rates and spatial differences in deposition, as well as what from the sediment phosphorus pool is available for recycling. Furthermore, knowing the significance of phosphorous sediment flux will aid in creating more accurate models, which can help in creating better policies that affect the lake such as land management practices.
Phospholipid Fatty Acid Profiles of Bacteria and Fungi in Peat Exposed to Experimentally Increased N Deposition, 2015
Development of the oil sands has led to increasing atmospheric N deposition, with values as high as 17 kg N ha-1 yr-1; regional background levels <2 kg N ha-1 yr-1. Bogs, being ombrotrophic, may be especially susceptible to increasing N deposition. To examine responses to N deposition, over five years, we experimentally applied N (as NH4NO3) to a bog near Mariana Lakes, Alberta, at rates of 0, 5, 10, 15, 20, and 25 kg N ha-1 yr-1, plus controls (no water or N addition). In July of 2015 we measured PLFA markers in two depths in each plot. For the most part, microbial group abundances were not affected by increasing N input (Fig. 16). However, actinomycete abundance decreased with increasing N deposition at rates that were similar in 0-5 and 5-10 cm peat. Gram-negative bacteria increased slightly with increasing N input and were more abundant in 0-5 cm than in 5-10 cm peat; correspondingly the Gram-positive to Gram-negative bacterial ratio decreased with increasing N input and was lower in 0-5 cm than in 5-10 cm peat. Total microbial abundance and total bacterial abundance were significantly higher in 0-5 cm peat than in 5-10 cm peat. It may be that more sensitive/targeted techniques, such as high-throughput pyrosequencing, 16s RNA clone library analysis and rRNA-targeted fluorescence in situ hybridization (FISH) or whole genome shotgun sequencing may be required to reveal bog microbial community responses to N loading.
Phospholipid Fatty Acid Profiles of Bacteria and Fungi in Poor Fen Peat Exposed to Experimentally Increased N Deposition, 2015
Development of the oil sands has led to increasing atmospheric N deposition, with values as high as 17 kg N ha-1 yr-1; regional background levels <2 kg N ha-1 yr-1. To examine responses to N deposition, over five years, we experimentally applied N (as NH4NO3) to a poor fen near Mariana Lake, Alberta, at rates of 0, 5, 10, 15, 20, and 25 kg N ha-1 yr-1, plus controls (no water or N addition). In July of 2015 we measured PLFA markers in two depths in each plot. Fungal abundance increased at N addition levels above 16.6 kg N ha-1 yr-1 and total bacterial abundance also increased at N addition levels above 17.1 kg N ha-1 yr-1, such that the fungal:bacterial ratio was not significantly affected by N addition. Total microbial, gram-negative bacterial, and actinomycete abundance also showed an apparent threshold responses to N addition at 16-17 kg N ha-1 yr-1 addition levels.It may be that more sensitive/targeted techniques, such as high-throughput pyrosequencing, 16s RNA clone library analysis and rRNA-targeted fluorescence in situ hybridization (FISH) or whole genome shotgun sequencing may be required to reveal detailed fen microbial community responses to N loading.
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.