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14,239 results for “STRUCTURE”
Above- and below-ground non-structural carbohydrates (NSC) in Spartina alterniflora from 6 permanant plots near the Georgia Coastal Ecosysterms LTER flux tower, on Sapelo Island in Georgia, USA
We studied the dynamics of four non-structural carbohydrates (glucose, fructose, sucrose, and starch) and biomass in 8 different above- and below-ground tissues in Spartina alterniflora over the course of a year in a salt marsh on Sapelo Island, Georgia, USA. Tissue parts sampled included green leaves, green stems, yellow leaves, yellow stems, brown leaves and stem, flowers, belowground biomass from 0-10cm depth and belowground biomass from 10-30cm depth. Samples were collected from tall form S. alterniflora plots near the Georgia Coastal Ecosystems LTER flux tower site monthly between September 2013 and August 2014. This study was conducted to support the development of predictive, mechanistic models of Spartina by providing information on below-ground biomass and its dynamics, and in particular the storage of resources that can be used for spring re-growth.
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Warming Effects on Microbial Structure and Decomposition at Harvard Forest 2011
Because microorganisms are sensitive to temperature, ongoing global warming is predicted to influence microbial community structure and function. We used large-scale warming experiments established at two sites near the northern and southern boundaries of US eastern deciduous forests to explore how microbial communities and their function respond to warming at sites with differing climatic regimes. Soil microbial community structure and function responded to warming at the southern but not the northern site. However, changes in microbial community structure and function at the southern site did not result in changes in cellulose decomposition rates. While most global change models rest on the assumption that taxa will respond similarly to warming across sites and their ranges, these results suggest that the responses of microorganisms to warming may be mediated by differences across the geographic boundaries of ecosystems.
Evaluation of Mask R-CNN Model for Counting Reproductive Structures of Six Plant Species 1895-2018
Phenology––the timing of life-history events––is a key trait for understanding responses of organisms to climate. The digitization and online mobilization of herbarium specimens is rapidly advancing our understanding of plant phenological response to climate and climatic change. The current common practice of manually harvesting data from individual specimens greatly restricts our ability to scale data collection to entire collections. Recent investigations have demonstrated that machine-learning models can facilitate data collection from herbarium specimens. However, present attempts have focused largely on simplistic binary coding of reproductive phenology (e.g., flowering or not). Here, we use crowd-sourced phenological data of numbers of buds, flowers, and fruits of more than 3000 specimens of six common wildflower species of the eastern United States (Anemone canadensis, A. hepatica, A. quinquefolia, Trillium erectum, T. grandiflorum, and T. undulatum} to train a model using Mask R-CNN to segment and count phenological features. A single global model was able to automate the binary coding of reproductive stage with greater than 90% accuracy. Segmenting and counting features were also successful, but accuracy varied with phenological stage and taxon. Counting buds was significantly more accurate than flowers or fruits. Moreover, botanical experts provided more reliable data than either crowd-sourcers or our Mask R-CNN model, highlighting the importance of high-quality human training data. Finally, we also demonstrated the transferability of our model to automated phenophase detection and counting of the three Trillium species, which have large and conspicuously-shaped reproductive organs. These results highlight the promise of our two-phase crowd-sourcing and machine-learning pipeline to segment and count reproductive features of herbarium specimens, providing high-quality data with which to study responses of plants to ongoing climatic change.
EEG: Improvisation and Musical Structures
Open the record for dataset details and reuse information.
Dataset of reports about MOF-based SERS substrates since 2011 until March 2023. Structure, characteristics, analytes, and performances.
<p>This dataset was generated to aid the creation of a review article addressing the use of Metal-Organic Frameworks (MOF)-based Surface Enhanced Raman Spectroscopy (SERS) platforms for the detection of Volatile Organic Compounds (VOCs).</p> <p>This dataset was generated employing the Web of Science database, encompassing manuscripts published up to March 2023. A literature search was initially conducted using a combination of keywords, including "MOF," "Metal-Organic Framework," "SERS," "Surface Enhanced Raman Spectroscopy," and "Surface Enhanced Raman Scattering." This search spanned the "Topic" category, enabling exploration across title, abstract, author keywords, and keyword-plus fields.</p> <p>From the initial pool of 238 documents, review articles and duplicates were systematically excluded, resulting in a refined collection of 182 articles. Subsequently, articles not concurrently addressing MOF and SERS or those utilizing MOF as sacrificial templates were further excluded, resulting in a final subset of 72 articles. From this curated set, relevant parameters were extracted, resulting in 229 entries for the dataset. </p> <p>Characteristics about the structure (in terms of MOF type and configuration; Plasmonic element type and configuration), target analyte (including type, phase, and incubation time), measurement specifications (in terms of laser, laser power, exposure time), and performance of the MOF-based SERS substrates were collected.</p> <p>Listed references 1-72 correspond with the manuscript number in the dataset.</p> <p>Listed references 73-80 correspond with references for selected examples of MOF pore diameters.</p>
Homologous membrane protein structures (HOMEP) version 1
<p><strong>Table 1</strong> = List of membrane protein structures in the <strong>HOMEP</strong> data set (version 1).<br> From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 1)<br> <a href="https://www.ncbi.nlm.nih.gov/pubmed/16648166">https://www.ncbi.nlm.nih.gov/pubmed/16648166</a></p> <p>Contains the following columns:<br> PDB-Code Protein-Name Source Res-(Å) Length (Num-TM) Number-of-TM-domains Family</p> <p><strong>Table 2</strong> = List of pairs of membrane protein structures in the <strong>HOMEP</strong> data set (version 1).<br> From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 2)</p> <p>Contains the following columns:<br> Model Family Query Template ID(%) RMS(Å) GDT_TS(%) TM-ID(%) TM-RMS(Å) TM GDT_TS(%)</p> <p><strong>Table 3 </strong>= Manually-defined transmembrane regions in the <strong>HOMEP</strong> data set (version 1), listed for each family by transmembrane segment number. From Forrest, Tang & Honig 2006 Biophysical Journal (Supplementary Table 3).</p> <p>Contains the columns defined as follows:<br> Protein chain identifier, start (-s) and end (-e) residues for each PDB structure in the family</p>
Helical dinuclear 3d metal complexes with bis(bidentate) [S,N] ligands: synthesis, structural and computational studies
<h1>Raw data for the publication entitled:</h1> <h2>Helical dinuclear 3d metal complexes with bis(bidentate)<br>[S,N] ligands: synthesis, structural and computational<br>studies</h2> <p><em>Dalton Transactions</em>, <strong>2024</strong>, DOI: 10.1039/D4DT02395A</p> <p>Authors:<br>Jamie Allen, Jörg Saßmannshausen, Kuldip Singh, Alexander F. R. Kilpatrick*</p> <p>These folders contain the raw data which were used to prepare the above publication.</p> <h1>Information regarding the raw files of the DFT calculations.</h1> <p>The zip-files in this section containing the raw-data of the DFT calculations leading to the Zn, Co and Fe calculated structures. As filenames are notoriously bad in handling special characters, the names of the folder appear different from what is being used in the final publication. We try to provide as much information as possible to facilitate the usage of these results.</p> <p>Thus:</p> <table> <tbody> <tr> <th>Abbreviation publication</th> <th>Abbreviation folder</th> <th>Abbreviation filename</th> </tr> </tbody> <tbody> <tr> <td>[Zn(<strong>3</strong>)<sub>2</sub>]</td> <td>Zn3-2</td> <td>SNdipp2Zn</td> </tr> <tr> <td>[Co(<strong>3</strong>) <sub>2</sub>]</td> <td>Co3-2</td> <td>SNdipp2Co</td> </tr> <tr> <td>[Fe(<strong>3</strong>) <sub>2</sub>]</td> <td>Fe3-2</td> <td>SNdipp2Fe</td> </tr> <tr> <td>[Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Zn2-2</td> <td>zn2</td> </tr> <tr> <td>[Co<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Co2-2</td> <td>co2</td> </tr> <tr> <td>[Fe<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Fe2-2</td> <td>fe2</td> </tr> </tbody> </table> <p>Some test calculations were performed as well utilizing Gaussian-09. They can be found in a folders with the suffix <em>-G09</em> or <em>-g09</em>.</p> <p>The closed shell compound [Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>] was investigated further. In order to look into the influence of the used Grimme dispersion correction, we re-calculated the final result without that correction. These files are in the Zn2-2-pbe0 folder. Furthermore, we used [Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>] and removed one of the Zn atoms and replaced the dangling bonds with H. We then fully optimized that structure. The results are in the Zn2-2-cut folder.</p> <h1> </h1> <h1>Information regarding the raw characterisation data</h1> <p>The raw characterisation data files for all nuclear magnetic resonance (NMR) spectroscopy, infrared (IR) spectroscopy, cyclic voltammetry (CV), single crystal X-ray diffraction (XRD) and solution magnetometry studies are enclosed in separate .zip files.</p>
Cross-phyla protein annotation by structural prediction and alignment
<p><strong>Background:</strong> Protein annotation is a major goal in molecular biology, yet experimentally determined knowledge is typically limited to a few model organisms. In non-model species, the sequence-based prediction of gene orthology can be used to infer protein identity, however this approach loses predictive power at longer evolutionary distances. Here we propose a workflow for protein annotation using structural similarity, exploiting the fact that similar protein structures often reflect homology and are more conserved than protein sequences.</p> <p><strong>Results:</strong> We propose a workflow of openly available tools for the functional annotation of proteins via structural similarity (MorF: <strong>Mor</strong>pholog<strong>F</strong>inder) and use it to annotate the complete proteome of a sponge. Sponges are highly relevant for inferring the early history of animals, yet their proteomes remain sparsely annotated. MorF accurately predicts the functions of proteins with known homology in >90% cases, and annotates an additional 50% of the proteome beyond standard sequence-based methods. We uncover new functions for sponge cell types, including extensive FGF, TGF and Ephrin signalling in sponge epithelia, and redox metabolism and control in myopeptidocytes. Notably, we also annotate genes specific to the enigmatic sponge mesocytes, proposing they function to digest cell walls.</p> <p><strong>Conclusions:</strong> Our work demonstrates that structural similarity is a powerful approach that complements and extends sequence similarity searches to identify homologous proteins over long evolutionary distances. We anticipate this to be a powerful approach that boosts discovery in numerous -omics datasets, especially for non-model organisms.</p>
Summer water chemistry; sediment phosphorus fluxes and sorption capacity; sedimentation and sediment resuspension dynamics; water column thermal structure; and zooplankton, macroinvertebrate, and macrophyte communities in eight shallow lakes in northwest Iowa, USA (2018-2020)
The primary aim of this data product is to characterize change in water chemistry, sediment-water interactions, and biological communities in shallow, eutrophic lakes undergoing a fishery biomanipulation. We studied eight glacial lakes located in northwest Iowa, USA, from 2018 to 2020 during the summer season (May to September). A subset of these lakes (n = 4; Center, Five Island, North Twin, and Silver Lakes) were part of a fishery biomanipulation in which the Iowa Department of Natural Resources (IDNR) incentivized commercial harvest of common carp (Cyprinus carpio) and bigmouth buffalo (Ictiobus cyprinellus). Harvests occurred in Center and Five Island Lakes during 2018-2019 and in North Twin and Silver Lakes during 2019-2020. Between 73 and 373 kg fish biomass per ha were removed each year. The other study lakes (n = 4; Blue, South Twin, Storm, and Swan Lakes) remained unmanipulated during the study period. Over the course of the biomanipulation, we quantified a suite of physical, chemical, and biological parameters across the study lakes. High frequency aquatic sensors were used to measure water column thermal structure, dissolved oxygen concentrations, and algal pigments. Manual water chemistry sampling further quantified suspended solids, total phosphorus and nitrogen, soluble reactive phosphorus, nitrate, and water clarity. We measured flux rates of phosphorus between bottom sediments and the overlying water using ex situ sediment core incubations under both oxic and anoxic conditions. We further quantified sediment phosphorus sorption capacity using equilibrium phosphorus concentration assays. Tiered sediment traps were used to measure sedimentation rates as well as sediment resuspension in bottom waters. We also measured change in zooplankton, macroinvertebrate, and macrophyte community composition and abundance. These data will be used to better understand the mechanisms of internal phosphorus loading in shallow lakes and the ecosystem effects of fisherie
Mangrove Coast Collaborative Project, Post-hurricane Irma mangrove forest structure data, Rookery Bay NERR, February 2022 - March 2023
The dataset describes the structure, composition, and condition of mangrove forests in Rookery Bay National Estuarine Research Reserve (NERR) assessed Feb 2022 - Mar 2023, approximately 5 years post Hurricane Irma (2017) and concurrent with Hurricane Ian (Sep 2022). The dataset includes information on each stem greater than or equal to 1 cm DBH (diameter at breast height) rooted within 69 100 m2 circular plots. Information collected includes site ID, location, species, DBH, status (live or dead), damage associated with the hurricane, presence/absence of regrowth, presence/absence of adventitious roots, whether or not stem is part of a multi-stemmed individual, and the canopy conditions (whether the tree has a canopy or is only sprouting at the base of the tree or trunk). This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Mangrove Coast Collaborative Project, Post-hurricane Maria mangrove forest structure data, Jobos Bay NERR, March 2022 - August 2022
The dataset describes the structure, composition, and condition of mangrove forests in Jobos Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Maria (2017). The dataset includes information on each stem greater than or equal to 1 cm DBH (diameter at breast height) rooted within 64 100 m2 circular plots. Information collected includes site ID, location, species, DBH, status (live or dead), damage associated with the hurricane, presence/absence of regrowth, presence/absence of adventitious roots, whether or not stem is part of a multi-stemmed individual, and the canopy conditions (whether the stem has a leafed canopy or is only sprouting at the base if live). This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Woody vegetation composition and structure at long-term monitoring plots on the Stevenson-Hamilton Research Supersite, Kruger National Park, South Africa (2012)
This dataset contains measurements of woody vegetation composition and structural attributes collected in 2012 from long-term ecological monitoring plots located on the Stevenson-Hamilton Research Supersite in the Kruger National Park, South Africa. The study region is characterized by granitic soils, broad-leaved savanna vegetation, and a long history of fire, herbivory, and climate-driven ecological dynamics. Vegetation surveys were conducted in sixteen 0.25-ha sampling plots to quantify woody species composition, stem density, and size structure. Additional measurements of vegetation structure were collected, including grass biomass, canopy cover, canopy height, and canopy diversity, providing a broader assessment of both woody and herbaceous layers. These data establish an important baseline for monitoring ecological change, evaluating woody vegetation dynamics under variable fire and herbivore regimes, and supporting ongoing research on savanna ecosystem functioning within the Kruger National Park.
Riparian Woody Vegetation Composition and Structure in Long-Term Monitoring Plots Along the Sabie River, Kruger National Park (2011-2012)
This dataset contains measurements of woody vegetation composition and structural attributes collected in 2009 and 2010 from 15 long-term riparian monitoring plots located along the Sabie River in the southern region of the Kruger National Park, South Africa. The Sabie River is the park’s most perennial river system and supports diverse riparian plant communities influenced by hydrological variability, flooding dynamics, sediment deposition, herbivory, and climate-driven disturbance. Within each monitoring plot, field teams recorded woody species identity, stem density, plant height, and stem diameter. Additional structural and condition indicators were collected, including canopy breakage, evidence of bark stripping, resprouting status, and whether individuals were toppled or alive at the time of sampling. These structural attributes provide detailed assessments of disturbance impacts and vegetation condition within riparian zones. Data collection followed the same standardized protocols as the Southern Granites long-term vegetation monitoring program, allowing for cross-site comparisons between upland savanna and riparian systems. This dataset provides a baseline for evaluating long-term ecological change in riparian woody plant communities and supports ongoing research on the ecological functioning and resilience of river corridors in Kruger National Park.
Forest structural diversity at NEON sites in the continuous USA that experienced recent moderate disturbance
Disturbances can change the structural diversity of forests through time, which can be measured from three-dimensional data provided by LiDAR. Discrete-return LiDAR was used to measure a suite of 19 structural diversity metrics that describe the height, cover and openness, vegetation density, and internal and external heterogeneity of forest vegetation at NEON base plots. Discrete-return LiDAR point clouds from the NEON Aerial Observation Platform (DP1.30003.001) were downloaded September of 2020 and used to estimate the metrics within 40 x 40 m base plots. Metrics were estimated from base plots at 15 NEON forested sites from provisional LiDAR data available from 2014 to 2020. The workflow that produced the data was developed in the program R.
Quantifying Growth and Structure along Forest Edges in the Northeastern USA 2010-2021
Fragmentation transforms the environment along forest edges. The prevailing narrative, driven by tropical research, suggests that edge environments increase tree mortality and structural degradation resulting in net decreases in ecosystem productivity. We show that temperate forest edges exhibit increased forest growth (basal area increment; BAI) and biomass (basal area; BA) with no change in total mortality relative to the forest interior. To assess forest edges, we analyzed more than 48,000 forest inventory plots (USDA FIA) across the north-eastern US using a quasi-experimental matching design. At forest edges adjacent to anthropogenic land covers, we report increases of 36.3% and 24.1% in forest growth and biomass, respectively. We then scale the edge impacts on growth (along anthropogenic edges only) across our study area using maps of land-cover and forest type. We find large variability in the effect of including edges on estimates of total forest growth, largely driven by differences in the prevalence of fragmentation. Estimated increases in forest growth range from a 23% increase in the agricultural-dominated western areas, a 2% increase in the least-fragmented northern regions, and a 15% increase within the metropolitan east coast. Finally, we also quantify forest fragmentation globally, at 30-m resolution, showing that temperate forests contain 52% more edge forest area than tropical forests. We provide two tables containing the post-matched dataset of FIA subplots, including subplot BA, BAI, and edge status. We include the associated environmental covariates, extracted from gridded raster data, and used in our matching and statistical analyses. Due to plot confidentiality restrictions we do not provide spatial locations of the FIA subplots, but we do provide unique plot identifiers that allow users to link each record to the publically-available data provided by the USDA FIA database (https://apps.fs.usda.gov/fia/datamart/). This dataset can be used to re
Structure of Ant Communities in Declining Hemlock Stands at Harvard Forest 2003
In biomass and ecological dominance, ants are the most important invertebrate taxon in terrestrial ecosystems and they can alter significantly fundamental processes and dynamics of soil ecosystems. Relative to deciduous stands, hemlock stands are depauperate in ant species that are linked to differences in rates of soil turnover and nutrient mineralization between these forest types. In both hemlock and deciduous stands, we will document ant species richness and abundance; assess their role in soil nutrient cycling; determine temporal trajectories of ant community assembly as hemlock declines following woolly adelgid infestation, and is subsequently replaced by birch; and discover how these trajectories influence nutrient availability during this transition. For more details see: Ellison, A. M., J. Chen, D. Dz, C. Kammerer-Burnham, and M. Lau. 2005. Changes in ant community structure and composition associated with hemlock decline in New England. Pages 280-289 in B. Onken and R. Reardon, editors. Proceedings of the 3rd Symposium on Hemlock Woolly Adelgid in the Eastern United States. US Department of Agriculgure - US Forest Service - Forest Health Technology Enterprise Team, Morgantown, West Virginia.
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Lake thermal structure drives inter-annual variability in summer anoxia dynamics in a eutrophic lake over 37 years
Dataset to run a 37-year simulation (1979-2015) of the Lake Mendota lake ecosystem using the vertical 1D GLM-AED2 model. The focus of this modeling study is on determining the drivers of year-to-year variability in the spatial and temporal extent of hypolimnetic anoxia.
Dataset of "Electronic structure and defect states in bismuth and antimony sulphides identified by energy-resolved electrochemical impedance spectroscopy"
Understanding the nature of the defects in the absorber materials, namely point defects, their formation mechanism and the contribution to the properties is essential for the photovoltaic device performance improvement. They are one the reasons why chalcogenide-based solar cells do not yet meet expected high power conversion efficiencies. Here we identify and present energy distribution of defects in Bi2S3 and Sb2S3, and their (SbxBi(100-x))2S3 alloys (with x = 0, 10, 33, 50, 67, 90, 100 at% Sb content) chalcogenides, being explored for emerging photovoltaic applications as they are earth-abundant and highly absorbing in the visible light range. We show that their density of states (DOS) and related parameters can be obtained experimentally by energy-resolved electrochemical impedance spectroscopy (ER-EIS) in a technically simple and quick way, where ER-EIS data are well correlated with theoretical DFT calculations. ER-EIS reveals that in Bi2S3 there are only shallow defects at CBM. In Sb2S3, ER-EIS reveals also midgap states which can be the cause of low electrical conductivity of Sb2S3. We also explain the discrepancy in the reported values of ionisation potentials and the bandgaps of the Bi- and Sb-chalcogenides. Dominant sulphur vacancy defect was identified in Bi- and Sb-chalcogenides whereas in ternary (SbxBi(100-x))2S3 system, merely 10 at.% of Bi transforms the midgap sulphur defects to shallow ones. This provides novel strategy for healing the midgap defects in Sb2S3, which is crucial for boosting the PV performance and tuning the electrical conductivity in Sb2S3.
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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.