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2,113 results for “High resolution”
High‐resolution genomic analysis of four local Vietnamese chicken breeds
<p>A total of 96 individuals were sampled from four populations of Vietnamese local chickens (28 Ho, 32 Dong Tao, 18 Mong, and 18 Mia) distributed in four provinces (Bac Ninh, Hung Yen, Ha Nam, and Hanoi, respectively) in the North of Vietnam. All individuals were from the same conservation program in Vietnam, originating from either private farms or public institutions involved in this program. Neither pedigree nor phenotypic information was available. We used stratified sampling for flocks, ensuring a distance of at least 500 m between the selected flocks and random sampling of one or two individuals in each selected flock. Genomic DNA was extracted from the blood samples of all chickens. The HD array for chickens allows for the simultaneous genotyping of approximately 580,000 SNPs. This array comprises SNPs on 28 autosomal chromosomes, two sex chromosomes (Z and W for poultry), and two linkage groups (LGE64 and LGE 22C19W28). Only SNPs on the 28 autosomes were considered in the present study. The SNPs with more than 10% missing genotypes or minor allele frequencies lower than 1% were removed, yielding a consensus panel of 454,297 autosomal SNPs for the analysis of population genetic structure.</p> <p>We applied a second quality control within each breed. Specifically, SNPs with within-breed minor allelic frequencies lower than 0.05 or SNPs with significant (P < 0.0001) deviation from the Hardy-Weinberg equilibrium were filtered out. This second filter led to 368,652, 383,792, 405,535, and 432,631 SNPs for Ho, Dong Tao, Mong, and Mia breeds, respectively. Of note, removing monomorphic SNPs within breeds may lead to the elimination of SNPs that are polymorphic across breeds. Due to the large number of available SNPs, we did not consider the potential effect of these filtered markers as important for subsequent analyses. Genetic diversity analyses were performed on the remaining 308,307 SNPs shared by all four breeds.</p>
Raw Data for the article: High-Resolution Secretome Analysis of Chemical Hypoxia Treated Cells Identifies Putative Biomarkers of Chondrosarcoma
<p>Chondrosarcoma is the second most common bone tumor, accounting for 20% of all cases. Little is known about the pathology and molecular mechanisms involved in the development and in the metastatic process of chondrosarcoma. As a consequence, there are no approved therapies for this tumor and surgical resection is the only treatment currently available. Moreover, there are no available biomarkers for this type of tumor, and chondrosarcoma classification relies on operator-dependent histopathological assessment. Reliable biomarkers of chondrosarcoma are urgently needed, as well as greater understanding of the molecular mechanisms of its development for translational purposes. Hypoxia is a central feature of chondrosarcoma progression. The hypoxic tumor microenvironment of chondrosarcoma triggers a number of cellular events, culminating in increased invasiveness and migratory capability. Herein, we analyzed the effects of chemically-induced hypoxia on the secretome of SW 1353, a human chondrosarcoma cell line, using high-resolution quantitative proteomics. We found that hypoxia induced unconventional protein secretion and the release of proteins associated to exosomes. Among these proteins, which may be used to monitor chondrosarcoma development, we validated the increased secretion in response to hypoxia of glyceraldehyde 3-phosphate dehydrogenase (GAPDH), a glycolytic enzyme well-known for its different functional roles in a wide range of tumors. In conclusion, by analyzing the changes induced by hypoxia in the secretome of chondrosarcoma cells, we identified molecular mechanisms that can play a role in chondrosarcoma progression and pinpointed proteins, including GAPDH, that may be developed as potential biomarkers for the diagnosis and therapeutic management of chondrosarcoma.</p>
High Resolution Phragmites Australis Classification in Delaware Estuaries
<p>This dataset provides a high resolution (1-m) land cover map for Estuarine wetlands in the State of Delaware in the United States of America during the summer of 2017. This dataset was created to identify populations of the invasive marsh species <em>Phragmites australis</em>.</p> <p><strong>Input data:</strong></p> <p>This classification is derived from National Agriculture Imagery Program (NAIP) 1-m aerial imagery captured in the State of Delaware during June of 2017. NAIP imagery includes a blue, green, red, and near infrared band. To improve classification accuracy, a Normalized Difference Vegetation Index (NDVI) was calculated from NAIP imagery using the near infrared and red bands. A principal component analysis (PCA) was used on the four NAIP bands and the NDVI band to create five new PCA bands. The five PCA bands were used as input into a random forest classification.</p> <p>NDVI = (Near infrared - Red) / (Near infrared + Red)</p> <p><strong>Classification methods:</strong></p> <p>We classified the input data using a Random Forest classifier with 100 trees. Data was classified into three coded land cover classes:</p> <p>1 - Phragmites</p> <p>2 - Other Vegetation</p> <p>3 - Open Water</p> <p>1,050 land cover reference points were collected with 70% used to train and 30% to test the classifier.</p> <p><strong>Accuracy:</strong></p> <p>Measures of accuracy including overall accuracy and per class user’s (UA) and producer’s accuracy (PA) of the random forest classifier were calculated.</p> <p>Overall accuracy: 95%</p> <p>Kappa: .92</p> <p>Phragmites: UA = 97% PA = 95%</p> <p>Other vegetation: UA = 92% PA = 96%</p> <p>Open water: UA = 100% PA = 95%</p> <p><strong>Code link:</strong></p> <p>The Google Earth Engine code used in this analysis is publicly available.</p> <p>https://github.com/mattswalter/Phragmites_Classification</p> <p><strong>Data for download:</strong></p> <p>The following zipped file is available for download:</p> <p> 1. Delaware_Phragmites_Classification.zip</p> <p>Contains a GEOTIFF titled "Phrag_DE_5PC" with the classified image for 2017. </p>
Data for manuscript "Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting"
<p>The tar file contains the input files for RADICAL augmented MDFF implementation (R-MDFF) for two protein systems, Adenylate Kinase (ADK) and Carbon Monoxide Dehydrogenase (CODH). These examples demonstrate the implementation of R-MDFF using RADICAL-Cybertools to flexibly fit biomolecules in cryo-EM density maps with on-the-fly decision making.</p> <p>All molecular simulations were performed using CUDA enabled NAMD 2.14 installed on OLCF Summit HPC resource. The CHARMM36 force field parameters were used for the proteins. Synthetic density maps were prepared at 1.8, 3 and 5 Å for ADK and 1.8 and 3 Å for CODH using VMD 1.9.3 software installed on OLCF Summit HPC resource. During the analysis stage, the cross correlation coefficients between density maps and atomic model were computed using VMD 1.9.3 on Summit HPC as part of the R-MDFF workflow.</p> <p>The source code is publicly available on GitHub: <a href="https://github.com/radical-collaboration/MDFF-EnTK">https://github.com/radical-collaboration/MDFF-EnTK </a></p> <p>The preprint of this research is submitted on bioRxiv, doi: <a href="https://doi.org/10.1101/2021.12.07.471672">https://doi.org/10.1101/2021.12.07.471672 </a></p> <p>To obtain maximum compression of the data, the tar command used to generate this tarball was:</p> <pre><code class="language-bash">GZIP=-9 tar --exclude='last.pdb' --exclude='*last_from_prev_iter.pdb' --exclude='*old' --exclude='*log' --exclude='*coor' --exclude='*vel' --exclude='*xsc' --exclude='*dcd' --exclude='lastframepdbs_fix' --exclude='*out' --exclude='*sl' --exclude='*rs' --exclude='*prof' --exclude='*err' --exclude='*dx' --exclude='*grid.pdb' --exclude='*txt' -cvzf rmdffv2.tar.gz rmdff-zenodo/</code></pre> <p> </p>
High-resolution spatial multi-omics datasets
<p>Supplementary raw data. The raw microscopy data are not uploaded owing to their large size (6.8 Tb), but are available upon reasonable request (Long Cai: lcai@caltech.edu, Yodai Takei: ytakei@caltech.edu).</p> <p>These supplementary data contain additional files for RNA seqFISH+, DNA seqFISH+, and sequential immunofluorescence from cell culture and adult mouse cerebellum experiments.</p> <p>DNA seqFISH+ datasets (provided as a tar.gz folder for each replicate): Super-resolved DNA spot locations by DNA seqFISH+ along with sequential immunofluorescence intensity at the rounded voxel location.</p> <p>RNA seqFISH datasets (provided as a zip folder): Super-resolved mRNA or intron spot locations.</p> <p>Sequential immunofluorescence table (provided as a csv file): Mean voxel intensity of each immunofluorescence marker per nucleus for the adult mouse cerebellum datasets.</p> <p>Note that voxel sizes are 103 nm for x and y, and 250 nm for z in our experimental setting.</p> <p>Please find the uploaded readme.txt file for more details.</p>
High spatial resolution satellite images for glacier outlines
<p>Two RapidEye satellite images acquired on Sep 13, 2013 and Sep 17, 2018. The two satellite images have a high spatial resolution of 5 m × 5 m and were used to derive the outlines of the Parlung No. 94 Glacier in years 2013 and 2018, respectively. The GaoFen-7 (GF-7) satellite image with a high spatial resolution of 3 m × 3 m acquired on Feb 26, 2021 was used to derive the outlines of the Dongkemadi Glacier in 2021</p>
supplementary data for Bemelmans et al., 2023, High-resolution InSAR reveals localised pre-eruptive deformation inside the crater of Agung volcano, Indonesia.
<p>This repository contains the supplementary materials for the paper "High-resolution InSAR reveals localised pre-eruptive deformation inside the crater of Agung volcano, Indonesia." to be published in JGR: Solid Earth.</p> <p>The dataset contains files assiciated with the StaMPS time series processing. Each dataset has its own folder containing:</p> <ol> <li>*_data.csv : data file containing latitude, longitude, incidence angle, heading and LOS displacement for each acquistion (date is listed in the column name in the format yyyymmdd).</li> <li>parms.mat : parameter file used for StaMPS processing of that dataset</li> </ol> <p>The dataset also contains input and results from the GBIS modelling (/GBIS_results/). the *.inp files are the input files for each model inversion where the letter ('M','T','P','Y', or 'D') refer to the Mogi (point), McTigue (sphere), penny-shaped crack, Yang (ellipsoid), and dyke (also sill) model used for that run. folders with the same name as the *.inp file contain the inversion results (invert_*.mat), a summary table (summary_*.txt) and several figures showing the distribution and convergence of the model inversion.</p> <p>The input for the GBIS inversions is stored in /GBIS_results/INSAR_input/</p> <p>the file <a href="https://zenodo.org/api/files/f30be116-1e2f-4d52-8fcf-a54e11ab691f/matlab_functions.zip?versionId=490de786-f245-45b5-92bb-d2ae0d50be56">matlab_functions.zip </a>contains matlab functions used for data processing, visualisation, storage and conversion.</p> <p>the file <a href="https://zenodo.org/api/files/f30be116-1e2f-4d52-8fcf-a54e11ab691f/GBISv1_1_MJWB.zip?versionId=cec83c81-a0b7-4e4a-8aa8-ac81e32b8772">GBISv1_1_MJWB.zip </a>contains GBIS code adapted by the author to perform statistical analysis of the model inversion, perform region-of-interest based subsampling and store modeled results as shapefiles for further processing.</p> <p> </p>
High-resolution figures and shape analyses files of Mengel et al.
<p>High-resolution figures and shape analyses files of Mengel et al. 2023 "The morphological diversity of dragon lacewing larvae changed more over geological time scales than anticipated" in Insects (MDPI)</p>
Model output for "A high-resolution physical-biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12)"
<p>This dataset contains the numerical model output files that were used in the analysis presented in "A high-resolution physical-biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12)", submitted to Geoscientific Model Development.</p>
High-resolution version for Fig. 1 in Rev. Sci. Instrum 94, 053706 (2023)
<p>Here is the same figure as Fig. 1 in Rev. Sci. Instrum 94, 053706 (2023), but with much higher resolution.</p>
High Resolution Langley
<p>Each pair of CSV files corresponds to a Langley regression analysis carried out at each wavelength point from 950 nm to 2100 nm for solar radiation at the ground recorded on an individual day using a coupled solar tracker- Bruker IFS-125 M Fourier transform spectrometer as part of the MAPP campaign at the Izana atmospheric observatory, Tenerife on DD-MM-YYYY. Each file contains two columns, the first giving the wavelength in nm, the second giving either the Langley gradient or intercept result at that wavelength on that day.</p>
Subset of non-redundant, high resolution multi-pass membrane protein PDB structure files from OPM
<p>A subset of OPM PDB structure files with membrane predictions curated for the MSc thesis project '<strong>Structural characterization of triplets of transmembrane α-helical segments consecutive in sequence in integral membrane proteins: a fragment-based computational pipeline'. </strong>The dataset contains PDB files downloaded from OPM on 22/02/2023. The files are alpha-helical integral membrane proteins with at least three transmembrane regions at better than 2.7 Angtrom resolution. They are non-redundant, with a sequence identity of less than 40% based on clustering with the cd-hit algorithm. </p>
Dataset for: Characterization of local deformation around hydrides in Zircaloy-4 using conventional and high angular resolution electron backscatter diffraction
<p>Datasets for:</p> <p>Characterization of local deformation around hydrides in Zircaloy-4 using conventional and high angular resolution electron backscatter diffraction</p> <p>Ruth M. Birch<sup>1,2*</sup>, James O. Douglas<sup>1</sup>, T. Ben Britton<sup>1,2</sup></p> <ol> <li>Department of Materials, Imperial College London, Exhibition Road, London, UK, SW7 2AZ</li> <li>Department of Materials Engineering, University of British Columbia, Frank Forward Building, 309-6350 Stores Road, Vancouver, BC, Canada V6T 1Z4</li> </ol> <p>---</p> <p>h5 files for all 4 examples used in the paper:</p> <ul> <li>Example 1: JustGBZrH_20kx_WD16-4_DD17_T10-4_Px100nm</li> <li>Example 2: ZrH_WD16_DD18_T10-4_px0</li> <li>Example 3: 20kx_WD16-5_DD17_T10-2_Px0-1um.</li> <li>Example 4: ZrHSpikes_18kx_WD16-5_DD17_T10-2_Px100nm<br> </li> </ul> <p>High quality figures for all figures in the paper (600 dpi)</p> <p> </p>
Dataset: Multi-resolution 3D rendering for high-performance Web AR
<p>The input data are the following four models: (i) Middlebury TempleRing [1] (ii) Human of CoRBS dataset [2]; (iii) Anton Memorial of Harvest4D consortium [3], and; (iv) Meteora site by Meteora Project [4]. The 3D files are converted into the multiresolution format NXS of Nexus.js library [5], in its compressed format NXZ, in the compressed DRC format of Draco library [6] and in the binary gtTF format (GLB) with some optimizations using meshoptimizer library [7]. </p> <p> </p> <p> </p> <ol> <li>Nair, N.S.; Nair, M.S. Multi-View Stereo Using Graph Cuts-Based Depth Refinement. <em>IEEE Signal Process. Lett</em>. <strong>2022</strong>, <em>29</em>, 1903–1907.</li> <li>Wasenmüller, O.; Meyer, M.; Stricker, D. CoRBS: Comprehensive RGB-D Benchmark for SLAM Using Kinect V2. In Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), New York, USA, 7 – 10 March 2016, pp. 1–7.</li> <li>Harvest 4D. Available Online: <a href="https://harvest4d.org">https://harvest4d.org</a> (accessed on 23 June 2023)</li> <li>Ioannidis, C.; Tallis, I.; Pastos, I.; Boutsi, A.M.; Verykokou, S.; Soile, S.; Tokmakidis, P.; Tokmakidis, K. A WEB-BASED PLATFORM FOR MANAGEMENT AND VISUALIZATION OF GEOMETRIC DOCUMENTATION PRODUCTS OF CULTURAL HERITAGE SITES, <em>ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci</em> <strong>2021</strong>, <em>V–2–2021</em>, 113–120.</li> <li> <p>Ponchio, F.; Dellepiane, M. Fast Decompression for Web-Based View-Dependent 3D Rendering. In Proceedings of the 20th International Conference on 3D Web Technology - Web3D ’15, Heraklion, Greece, 18-21 June 2015; pp. 199–207.</p> </li> <li> <p>Draco 3D data compression. Available online: https://google.github.io/draco/ (accessed on 23 June 2023)</p> </li> <li> <p>Meshoptimizer. Available online: <a href="https://github.com/zeux/meshoptimizer/tree/master">https://github.com/zeux/meshoptimizer/tree/master</a> (accessed on 23 June 2023)</p> </li> </ol>
High resolution LiDAR dataset acquired using UAV (unmanned aerial vehicle) over two vineyards and two years located in 'Tomiño', Pontevedra, Spain.
<p>This dataset features an extensive collection of LiDAR data from vineyards in northern Spain, targeting vineyards to address the growing demand for public UAV LiDAR datasets in Agricultural Sciences. The data was gathered using a DJI M300 multi-rotor platform equipped with a DJI Zenmuse L1 LiDAR sensor, conducting UAV flights at 20, 30, and 50 meters Above Ground Level (AGL) across two vineyards during 2021 and 2022. The dataset comprises ten high-density 3D LiDAR point clouds stored in .laz format with embedded RGB information in each point. This information is essential for studying vineyard morphology and development and plays a key role in refining vineyard management tactics. In addition, the dataset is valuable for agricultural robotics, providing detailed terrain and canopy data crucial for designing efficient flight paths and navigation algorithms. Finally, it serves as a true "ground truth" dataset to verify satellite-derived models, enabling the generation of high-precision digital elevation models (DEMs) and other derivatives.</p>
High-speed TIRF and 2D super-resolution structured illumination microscopy with large field of view based on fiber optic components
<p>Super-resolved structured illumination microscopy (SR-SIM) is among the most flexible, fast, and least perturbing fluorescence microscopy techniques capable of surpassing the optical diffraction limit. Current custom-built instruments are easily able to deliver two-fold resolution enhancement at video-rate frame rates, but the cost of the instruments is still relatively high, and the physical size of the instruments based on the implementation of their optics is still rather large. Here, we present our latest results towards realizing a new generation of compact, cost-efficient, and high-speed SR-SIM instruments. Tight integration of the fiber-based structured illumination microscope capable of multi-color 2D- and TIRF-SIM imaging, allows us to demonstrate SR-SIM with a field of view of up to 150 × 150 μm<sup>2</sup> and imaging rates of up to 44 Hz while maintaining highest spatiotemporal resolution of less than 100 nm. We discuss the overall integration of optics, electronics, and software that allowed us to achieve this, and then present the fiberSIM imaging capabilities by visualizing the intracellular structure of rat liver sinusoidal endothelial cells, in particular by resolving the structure of their trans-cellular nanopores called fenestrations.</p>
Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator
<p>Dataset related to Huu-Hien Huynh, Vincent Delatour, Maxence Derbez-Morin, Qinde Liu, Amandine Boeuf, and Joëlle Vinh, (2022) Candidate High-Resolution Mass Spectrometry-Based Reference Method for the Quantification of Procalcitonin in Human Serum Using a Characterized Recombinant Protein as a Primary Calibrator. Anal. Chem. 2022, 94, 10, 4146–4154.</p>
Mapping past land cover on Poitiers in 1993 at Very High Resolution using GEOBIA approach and open data
<p>This dataset contains a land cover map of Poitiers in 1993 over an area of 225km².</p> <p>The land cover map was achieved using aerial images of the French National Geographic Institute (IGN) and Landsat-5 TM images combined with remote sensing methods. Geographic Object-Based Image Analysis (GEOBIA) and Random Forest classifications produced a reliable land cover map at a 1m of spatial resolution.</p> <p>Orthophotos produced as well as training and validating polygons to achieve the classifications were added into this dataset.</p> <p>As land cover changes is crucial to land management, this map will help to understand changes from 1993 to now for urban, agricultural issues but also their impact on ecological processes. Data will be easily used in GIS applications for any users.</p> <p>This work is part of the thesis of Elie Morin which was funded by la région Nouvelle-Aquitaine and Grand Poitiers Communauté urbaine, among others.</p>
Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development
<p class="MsoNormal"><span>With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called 'genoscapes') for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.</span></p>
High-Resolution Vegetation Height Maps for Switzerland in 2017-2020
<p>This dataset comprises 10m-resolution vegetation height maps for Switzerland spanning from 2017 to 2020. It encompasses both mean and maximum vegetation height data, generated through the integration of Sentinel-2 and airborne laser scanning information.</p>
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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.