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2,562 results for “SARS CoV 2”
The use of nanobodies in a sensitive ELISA test for SARS-CoV-2 Spike 1 protein
<p>A rapid detection method for SARS-CoV-2 spike protein is essential for control of COVID19. We investigated various combinations of engineered nanobodies in a sandwich ELISA to detect the Spike protein of SARS-CoV-2. We have identified an optimal combination of nanobodies. These were selectively functionalised to further improve antigen capture. This dataset contains data from ELISA experiments described in the manuscript.<span> </span></p> <p><span>Plate coating of nanobodies for ELISA by passive adsorption vs biotinylation was compared. A series of nanobody pairings (two cluster 2 ACE2-binding epitope and two cluster 1 CR3022 epitope) were screened for optimum sensitivity. The optimal pair were then tested against a series of SARS-COV-2 antigens: recombinant spike 1 protein; recombinant receceptor binding domain (RBD); pseudotyped HIV-1 and heat-empigen inactivated SARS-CoV-2 virus. X-ray irradiated SARS-CoV-2 was also tested. Sensitivity to these antigens was compared with nanobodies biotinylated a) site-selectively and b) in a non-specific stochastic manner. Batch-to-batch viral variation and effects of inactivating agents were investigated. Limit of detection was compared against delta and beta viral mutants. Combining optimal nanobody pairing and site-selective biotinylation, we observed a limit of detection of 147 pg/mL for Spike protein; 33 pg/mL for RBD; 16 TCID50/mL of pseudovirus and 15 ffu/mL of heat-Empigen inactivated SARS-CoV-2. The pairing also showed sensitivity towards delta variant. We have demonstrated the use and sensitivity of nanobodies in ELISA by detection of recombinant and viral SARS-CoV-2 antigens.</span></p>
Training data for "Identification of allelic variants in SARS-CoV-2 from deep sequencing reads"
<p>Effectively monitoring global infectious disease crises, such as the COVID-19 pandemic, requires capacity to generate and analyze large volumes of sequencing data in near real time. These data have proven essential for monitoring the emergence and spread of new variants, and for understanding the evolutionary dynamics of the virus.</p> <p>Two sequencing platforms in combination with several established library preparation strategies are predominantly used to generate SARS-CoV-2 sequence data. However, data alone do not equal knowledge: they need to be analyzed. The Galaxy community developed analysis workflows to support the <strong>identification of allelic variants (AVs) in SARS-CoV-2 from deep sequencing reads</strong>.</p> <p>These workflows allow one to identify AVs and lineages in SARS-CoV-2 genomes with variant allele frequencies ranging from 5% to 100% (i.e., they detect variants with intermediate frequencies as well.</p> <p>In this tutorial we will see how to run these workflows for the different types of input data:</p> <ul> <li>Single end data derived from Illumina-based RNAseq experiments</li> <li>Paired end data derived from Illumina-based RNAseq experiments</li> <li>Paired-end data generated with Illumina-based Ampliconic (ARTIC) protocols</li> <li>ONT fastq files generated with Oxford nanopore (ONT)-based Ampliconic (ARTIC) protocols</li> </ul> <p>To illustrate the tutorial, we took some example datasets (paired-end data generated with Illumina-based Ampliconic (ARTIC) protocols) from COG-UK, the COVID-19 Genomics UK Consortium.</p>
Molecular Dynamics of SARS-CoV-2 Delta Variant Receptor Binding Domain in Complex with ACE2 Receptor
<p>Molecular dynamics simulation for 10 ns at 37 C degrees of SARS-CoV-2 delta variant. Performed with NAMD and visualized/analyzed in ChimeraX software using Frontera supercomputer from Texas Advanced Computing Center. By Victor Padilla-Sanchez, PhD.</p> <p>https://www.youtube.com/watch?v=8N_MjWwxbMQ</p>
CSV-format data for: Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7
<p>This is a supplementary upload to <a href="https://zenodo.org/record/4579857">https://zenodo.org/record/4579857</a>.</p> <p>This upload provides the same anonymised individual-level SARS-CoV-2 testing data for England as that earlier upload provided, but provides it in CSV format (comma-separated values) instead of in the previous QS format. The QS format requires specialised software (e.g. the <strong>qs</strong> package for R) to read, so I am providing the data in CSV format to facilitate access to and re-use of the data.</p> <p>Please see the original data upload, <a href="https://zenodo.org/record/4579857">https://zenodo.org/record/4579857</a>, the associated journal article, <a href="https://www.nature.com/articles/s41586-021-03426-1">Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7</a>, and the project's Github repository, <a href="https://github.com/nicholasdavies/cfrvoc">https://github.com/nicholasdavies/cfrvoc</a>, for full details.</p>
Evidence summary on activities or settings associated with a higher risk of SARS-CoV-2 transmission: Summary of included evidence syntheses
<p>This is a data extraction table associated with the HIQA report entitled: Evidence summary on activities or settings associated with a higher risk of SARS-CoV-2 transmission</p>
Pandemic, epidemic, endemic: B cell repertoire analysis reveals unique anti-viral responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus
<p>VDJ gene usage, and associated amino acid sequences and properties, from healthy controls as well as patients with COVID-19, RSV or Ebola and Yellow fever vaccine recipients.</p>
SARS-CoV-2 raw fastq files
<p>Illumina paired end FASTQ files from MiSeq. Sequenced at the African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State.</p> <p>Training data</p>
SARS-CoV-2 viral loads across the upper and lower respiratory tract, sex, disease severity and age groups for adult and pediatric COVID-19
<p>This dataset shows SARS-CoV-2 respiratory viral loads (viral RNA concentration in the respiratory tract) in the upper and lower respiratory tract for age, sex and COVID-19 severity groups. The data were obtained from a systematic review. The model outputs show the Weibull distributions, case percentiles, and sensitivity & specificity when using SARS-CoV-2 viral load (URT or LRT) as a prognostic indicator. See our paper for more information.</p>
Mass Spectrometry Datasets for "Highly synergistic combinations of nanobodies that target SARS-CoV-2 and are resistant to escape"
<p>This repository contains mass spectrometry raw datasets for the research paper "<strong><em>Highly synergistic combinations of nanobodies that target SARS-CoV-2 and are resistant to escape</em></strong>". An early version of the manuscript can be viewed on <a href="https://www.biorxiv.org/content/10.1101/2021.04.08.438911v1">bioRxiv</a>.</p> <p>The datasets include two parts:</p> <ol> <li>Identification of nanobodies targeting SARS-CoV-2 spikes.</li> <li>Chemical cross-linking of nanobody-spikes complexes.</li> </ol> <p>The included <strong>.raw</strong> files are Thermo Orbitrap Raw files, and can be assessed by various software such as <em>Thermo Xcalibur</em>, <em><a href="https://proteowizard.sourceforge.io/">ProteoWizard</a></em> and <em><a href="https://pypi.org/project/pymsfilereader/">pymsfilereader</a></em>.</p>
Nsp3 macrodomain of SARS-CoV-2 ; A Target Enabling Package
<p>The conserved macrodomain encoded as non-structural protein 3 (Nsp3 Mac1) is employed by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to remove host-derived ribosylation, which is a post-translational modification involved in the production of antiviral cytokines. This TEP provides early tools to develop Nsp3 Mac1 inhibitors, including purification protocols of recombinant proteins, reproducible crystallisation condition suitable for X-ray crystallography fragment screening, biophysical (activity and binding) assays and over 200 fragment hits representing a wide range of chemotypes, that are a starting point for the development of more selective and potent compounds.</p>
Source data for Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum
<p>This dataset contains the source data used in the publication: "Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum" published in Nature communications on August 26, 2021 (10.1038/s41467-021-25479-6).</p>
Simulated wastewater sequencing data for benchmarking SARS-CoV-2 variant abundance estimation
<p>To evaluate the accuracy of variant abundance predictions from wastewater sequencing, we built a collection of benchmarking datasets that resemble real wastewater samples. For each variant (B.1.1.7, B.1.351, B.1.427, B.1.429, P.1) we created a series of 33 benchmarks by simulating sequencing reads from a variant genome, as well as a collection of background (non-variant of concern/interest) sequences, such that the variant abundance ranges from 0.05% to 100%. Analogously, we created a second series of benchmarks, simulating reads only from the Spike gene of each SARS-CoV-2 genome. We refer to the first set of benchmarks as "whole genome" (WG) and to the second set of benchmarks as "S-only". We repeated these simulations at different sequencing depths: 100x and 1000x coverage for the whole genome benchmarks, and 100x, 1000x, and 10,000x coverage for the S-only benchmarks.</p>
Source data for "Date of introduction and epidemiologic patterns of SARS-CoV-2 in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020"
<p>Source data for the model fitting code at https://doi.org/10.5281/zenodo.5525349, accompanying the article "<em>Date of introduction and epidemiologic patterns of SARS-CoV-2 in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020</em>"</p>
SARS-CoV-2–host proteome interactions for antiviral drug discovery
<p>Images and datasets used in Fig 6 and corresponding supplementary material Image analysis was performed with Harmony 4.9 software (PerkinElmer) with feature extraction and linear classification of N-protein positive cells from the total population as presented in the PlateResults file. Prism files (GraphPad Software) include the calculations for curve fits of drug testing data (4PL logistic regression) as well as area under the curve (AUC) of the fitted curves..</p>
OME-NGFF: EM image of SARS-CoV-2
<p>Section of a 30 GB EM image of SARS-CoV-2 in the human intestine from Lamers et al. (Science 2020; 10.1126/science.abc1669) available in the Image Data Resource under accession idr0083 and DOI 10.17867/10000135 under CC-BY 4.0.</p> <p>The original data in TIFF format was converted into the Zarr format following the 0.1 version of the OME-NGFF specification (https://ngff.openmicroscopy.org/0.1/)</p>
Primers for whole genome sequencing of the Sars-Cov-2 virus
<p>Here is the primer sequence for amplification and sequencing of the whole genome of the Sars-Cov-2 virus.</p>
A patient-centric modelling framework captures recovery from SARS-CoV-2 infection
<p>The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year post-disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct “systemic recovery” profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter- and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery at the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool <a href="https://aus01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fshiny.mrc-bsu.cam.ac.uk%2Fapps%2Fcovid-19-systemic-recovery-prediction-app&data=05%7C01%7CJulien.Wist%40murdoch.edu.au%7C117789e168814a13808a08dabcf18a3e%7Cc00d4c1bcf7b4e93b7c710113a9bc230%7C1%7C0%7C638030042858394016%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=z7RJ8%2BGTWr84dYvWSoc%2F9Cj1zYRHV7%2BHfyr9MyCnX6M%3D&reserved=0">http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app</a>, designed to test our findings prospectively.</p>
AMTraC-19 (v7.9) Dataset: Persistence of the Omicron variant of SARS-CoV-2 in Australia
<p>The paper describing scenarios which generated this dataset:</p> <p>S. L. Chang, Q. D. Nguyen, A. Martiniuk, V. Sintchenko, T. C. Sorrell, M. Prokopenko, Persistence of the Omicron variant of SARS-CoV-2 in Australia: The impact of fluctuating social distancing, <em>PLOS Global Public Health</em>, 3(4): e0001427, 2023.</p> <p>The AMTraC-19 source code (v7.9) is released on Zenodo: https://zenodo.org/record/7325675</p>
Evaluation of Ortho VITROS and Roche Elecsys S and NC immunoassays for SARS-CoV-2 serosurveillance applications
<p>SARS-CoV-2 seroprevalence studies are instrumental in monitoring epidemic activity and require <span>well-characterized, high-throughput assays, and appropriate testing algorithms.</span> The U.S. Nationwide Blood Donor Seroprevalence Study performed monthly cross-sectional serological testing from July 2020 to December 2021, implementing evolving testing algorithms in response to changes in pandemic activity. With high vaccine uptake, anti-Spike (S) reactivity rates reached > 80% by May 2021, and the study pivoted from reflex Roche anti-nucleocapsid (NC) testing of Ortho S-reactive specimens to parallel Ortho S/NC testing. We evaluated the performance of the Ortho NC assay as a replacement for the Roche NC assay and compared performance of parallel S/NC testing on both platforms. Qualitative and quantitative agreement of Ortho NC with Roche NC assays was evaluated on pre-selected S/NC concordant and discordant specimens. All 190 Ortho S+/Roche NC+ specimens were reactive on the Ortho NC assay; 34% of 367 Ortho S+/Roche NC- specimens collected prior to vaccine availability and 43% of 37 Ortho S-/Roche NC+ specimens were reactive on the Ortho NC assay. Performance of parallel S/NC testing using Ortho and Roche platforms was evaluated on 200 specimens collected in 2019 and 3,903 study specimens collected in 2021. All 200 pre-COVID 2019 specimens tested negative on the four assays. Agreement of S and NC reactivity on specimens was 96.4% (3,769/3,903); most discordant results had reactivity close to the cutoffs on the alternate assays. These findings, and higher efficiency and throughput, support use of parallel S/NC testing on either Roche or Ortho platforms for large serosurveillance studies.</p>
Detection of SARS-CoV-2 variants by genomic analysis of wastewater ampliconic samples (Galaxy Training Material)
<p>The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater ampliconic samples. (https://training.galaxyproject.org/training-material/)</p>
ScienceDex guides
Understand access before you commit
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.