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411
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ShareScore release 0.7.1
Dataset results
411 results for “spatial variation”
Spatial and Temporal Variation in the Skin Transcriptome of Atopic Dermatitis Assessed by 1.5 mm Mini Punch Biopsies
GEO Series GSE193309. Homo sapiens. 339 samples. Type: Expression profiling by high throughput sequencing.
Subtype-Specific and Structure Variation-Induced Chromatin Spatial Reorganization in Acute Myeloid Leukemia [WGBS]
GEO Series GSE152099. Homo sapiens. 20 samples. Type: Methylation profiling by high throughput sequencing.
Subtype-Specific and Structure Variation-Induced Chromatin Spatial Reorganization in Acute Myeloid Leukemia [Hi-C]
GEO Series GSE152135. Homo sapiens. 32 samples. Type: Other.
Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization
GEO Series GSE107051. Homo sapiens. 4 samples. Type: Other.
FIG. 5 in Phenotypic Variation in Brook Trout Salvelinus fontinalis (Mitchill) at Broad Spatial Scales Makes Morphology an Insufficient Basis for Taxonomic Reclassification of the Species
FIG. 5. Representative examples of diverse morphology, particularly in mouth shape and position, observed within a single stream-dwelling Brook Trout population. Fish on the first row display more inferior mouth positions, whereas fish on the last row show more isognathous and prognathic jaws with a terminal/superior mouth position. All fish were captured from Crabtree Creek in the Savage River Watershed of western Maryland (39827047.2500 N, 79812036.0800W). Fish total length is noted in the upper right corner of each photograph. A full description of collection and photography protocols is provided in Kazyak et al. (2015).
FIG. 3 in Phenotypic Variation in Brook Trout Salvelinus fontinalis (Mitchill) at Broad Spatial Scales Makes Morphology an Insufficient Basis for Taxonomic Reclassification of the Species
FIG. 3. Comparison of pored lateral-line scale counts for specimens collected from (A) 38 streams in the Great Smoky Mountains National Park (GSMNP) by Weathers et al. (2019) and (B) three streams surveyed by Stauffer (2020) and three populations described by Stauffer and King (2014) in Long Island, NY. Individual-level data collected by Weathers et al. (2019) are displayed with violin plots, with the width of the violin plot for each stream demonstrating the density of the distribution for a given value and the minimum and maximum values indicated by the tails of the distribution. Due to discrepancies between published and raw data, values from Stauffer (2020) and Stauffer and King (2014) are shown using two methods. Data from the publication appear as the mode(s) (circle) and range (lines), and the raw, individual-level data appear as violin plots. Streams appear on the x-axis by ascending average trait value, and streams included in both Weathers et al. (2019) and Stauffer (2020) are plotted with the same color (Cosby Creek [CS]: yellow; Greenbrier Creek [GB]: green; Indian Camp Creek [ICC]: blue). Data from populations in NY are shown in red and all other sites from GSMNP, TN in gray.
Gingival spatial analysis reveals geographic immunological variation in a microbiota-dependent and -independent manner [scRNA-seq]
GEO Series GSE269575. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
FIGURES 22.—25 in Complementary description of three species of Steneotarsonemus (Acari: Tarsonemidae) from rice agroecosystems of Eastern India with notes on their taxonomic status, spatial distribution, intraspecific variation and species composition
FIGURES 22.—25. Steneotarsonemus furcatus (male). 22.—leg I, 23.—leg II, 24.—leg III, 25.—leg IV.
FIGURES 2, 3 in Complementary description of three species of Steneotarsonemus (Acari: Tarsonemidae) from rice agroecosystems of Eastern India with notes on their taxonomic status, spatial distribution, intraspecific variation and species composition
FIGURES 2, 3. Steneotarsonemus spinki (female). 2. Dorsal surface. 3. Ventral surface.
Spatial and Temporal Variation of Erosion Rate of the Lohit Bomi-Chayu Batholith of Eastern Himalayan Syntaxis
<p>This contains dataset for manuscript entitled - "Spatial and Temporal Variation of Erosion Rate of the Lohit Bomi-Chayu Batholith of Eastern Himalayan Syntaxis"</p>
Example simulation showing spatial and temporal variations in surface carbon biomass of plankton functional groups during a Spring bloom as shown by a 3D hydrodynamic-biogeochemical model (FVCOM-ERSEM), with and without integration of the mixoplankton paradigm.
<p>The outputs are from simulations from using the FVCOM hydrodynamic model coupled to two different versions of ERSEM – (i) ERSEM and (ii) ERSEM-PB (the latter includes the implementation of the mixoplankton paradigm through integration of the 'Perfect Beast' PB model; Flynn and Mitra 2009 <em>Journal of Plankton Research</em>).</p> <p>The FVCOM domain was configured to represent Lyme Bay: a protected bay on the South Coast of England. This region is an important area for shellfish aquaculture. The domain was configured at 350 m – 5 km high-resolution, resolving sub-km scale dynamics in the area. A nested modelling approach of increasing model resolution was set up using two model domains. For the coupled hydrodynamic-biogeochemical model, a parent domain of 1.5 km – 10 km resolution was used to drive Lyme Bay model domain. The atmospheric forcing was provided by a 3-step downscaling of GFS global datasets to reach the 3 km of the final model domain using the Weather Research Forecast (WRF) model. Hydrodynamic boundary conditions are extracted from the European Copernicus Marine System North West European Shelf Forecast system. River flows were extracted from a National scale hydrology model run by the Center for Hydrology and Ecology in the UK. Simulations were initialised at Jan 1<sup>st</sup> 2005, and spun up for 3 months prior to the output of the data visualised in these videos. </p> <p>The 6 videos portray spatial and temporal variation of daily averaged surface carbon biomass (μgC L<sup>-1</sup>) during the month of April 2005 for the different plankton functional types (FTs) as follows:</p> <ul> <li>Video 1: all phytoplankton FTs in standard ERSEM grouped together. These thus include diatoms, nano-, pico- and micro- plankton; i.e., these simulations do not discriminate between phytoplankton and constitutive mixoplankton (CM).</li> <li>Video 2: phytoplankton FT in ERSEM-PB now considering only diatoms and picoplankton (i.e., cyanobacteria) only; CM are now included in Video 3 outputs.</li> <li>Video 3: all mixoplankton FTs grouped together in ERSEM-PB. These outputs thus include biomasses of micro-CM, nano-CM and NCM.</li> <li>Video 4: all zooplankton FTs grouped together in standard ERSEM. Thus, these include nanoflagellates, meso- and micro- zooplankton and thus includes the primary producing non-constitutive mixoplankton</li> <li>Video 5: zooplankton FT representing only the heterotrophic nano- and micro- zooplankton in ERSEM-PB.</li> <li>Video 6: spatio-temporal variability between the constitutive and non-constitutive mixoplankton functional groupings within FVCOM-ERSEM-PB. </li> </ul> <p>For further information about the mixoplankton paradigm, please see the following open access publications and references there in:</p> <p>Mitra A, Caron DA, Faure E, Flynn KJ, Leles SG, Hansen PJ, McManus GB, Not F, Gomes HR, Santoferrara L, Stoecker DK, Tillmann U (2023) <strong>The Mixoplankton Database – diversity of photo-phago-trophic plankton in form, function and distribution across the global ocean</strong>. <em>Journal of Eukaryotic Microbiology</em>, e12972. <a href="https://doi.org/10.1111/jeu.12972">https://doi.org/10.1111/jeu.12972</a></p> <p>Glibert PM, Mitra A (2022) <strong>From webs, loops, shunts, and pumps to microbial multitasking: evolving concepts of marine microbial ecology, the mixoplankton paradigm, and implications for a future ocean</strong>. <em>Limnology and Oceanography</em> 67: 585-597 <a href="https://doi.org.10.1002/lno.12018">https://doi.org.10.1002/lno.12018</a> </p> <p>Mitra A, Irigoien X (2022) <strong>Mixoplankton – Marine Organisms that break the rules</strong>. EU Researcher. <a href="https://issuu.com/euresearcher/docs/mixitin_eur28_h_res">https://issuu.com/euresearcher/docs/mixitin_eur28_h_res</a> </p> <p>Flynn KJ, Mitra A, Anestis K, Anschütz AA, Calbet A, et al. (2019) <strong>Mixotrophic protists and a new paradigm for marine ecology: where does plankton research go now?</strong> <em>Journal of Plankton Research</em> 41: 375-391 <a href="https://doi.org/10.1093/plankt/fbz026">https://doi.org/10.1093/plankt/fbz026</a></p>
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.