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2,551 results for “SARS-CoV”
Haruspex Analysis for SARS-CoV-2 rna_polymerase-nsp7-nsp8 pdb entry 6m71 emdb 30127
<p>Haruspex (version 1.0 190116) analysis for SARS-CoV-2 rna_polymerase-nsp7-nsp8 , pdb entry 6m71 , emdb 30127. https://onlinelibrary.wiley.com/doi/10.1002/anie.202000421</p>
Haruspex Analysis for SARS-CoV surface_glycoprotein pdb entry 5x58 emdb 6703
<p>Haruspex (version 1.0 190116) analysis for SARS-CoV surface_glycoprotein , pdb entry 5x58 , emdb 6703. https://onlinelibrary.wiley.com/doi/10.1002/anie.202000421</p>
Haruspex Analysis for SARS-CoV surface_glycoprotein pdb entry 5x5b emdb 6705
<p>Haruspex (version 1.0 190116) analysis for SARS-CoV surface_glycoprotein , pdb entry 5x5b , emdb 6705. https://onlinelibrary.wiley.com/doi/10.1002/anie.202000421</p>
Haruspex Analysis for SARS-CoV surface_glycoprotein pdb entry 5xlr emdb 6732
<p>Haruspex (version 1.0 190116) analysis for SARS-CoV surface_glycoprotein , pdb entry 5xlr , emdb 6732. https://onlinelibrary.wiley.com/doi/10.1002/anie.202000421</p>
Investigating evolution at the catalytic site of the main SARS-CoV-2 protease using over 15,000 genomes
<p>We investigated evolution and genomic variation of SARS-CoV-2 within the current pandemic at the catalytic site of the main SARS-CoV-2 protease (see https://zenodo.org/record/3834875#.Xs1IHsZ7nyk and <a href="https://openlabnotebooks.org/mapping-the-genetic-variations-of-sars-cov-2-onto-its-proteins-crystal-structures-post-1/">https://openlabnotebooks.org/mapping-the-genetic-variations-of-sars-cov-2-onto-its-proteins-crystal-structures-post-1/ </a>).<br> We used more than 15,000 genomic sequences from GISAID (<a href="https://www.epicov.org/">https://www.epicov.org/</a>) available on the 17th of May 2020.<br> We use a new approach based on phylogenetic inference of homoplasy, clustering of mutations, and ambiguous consensus sequence characters, to identify sites that are likely affected by sequencing artefacts.<br> We find that these sites are mostly conserved, and the amino acid variants observed are only M49I, P52S, N142S, and P168S, all of which appear only at extremely low frequencies (maximum of two samples each).</p>
Datasets for GTN tutorial on SARS-CoV-2 variant analysis
<p>A reference genome in FASTA format is provided for SARS-CoV-2, "Severe acute respiratory syndrome coronavirus 2 isolate Wuhan-Hu-1, complete genome", having the accession ID of NC_045512.2.</p> <p>This file was obtained from NCBI within this Galaxy history: https://usegalaxy.org/u/dan/h/nc0455122-from-ncbi</p>
QM/MM MD simulations of the ES complexes of SARS-CoV-2 main protease and oligopeptide substrates
<p>qmdcd.7z : QM/MM MD trajectories for all considered systems in dcd format for QM parts without link atoms (QMpart_nolink.pdb)</p> <p>frames.7z : QM parts of the MD frames selected for the electron density analysis.</p> <p> </p> <p> </p>
ekoraytascilar/naturecommunicationscovid: Data and analysis code to accompany "Patients with immune-mediated inflammatory diseases receiving cytokine inhibitors have low prevalence of SARS-CoV-2 seroconversion"
<p>This release contains raw datasets and analysis code for the research paper titled "Patients with immune-mediated inflammatory diseases receiving cytokine inhibitors have low prevalence of SARS-CoV-2 seroconversion"</p>
SARS-CoV-2 detection dogs - a pilot study
<p>The outstanding olfactory acuity of canines led us to consider whether dogs are able to reliably detect the odour of respiratory diseases associated with a SARS-CoV-2 infection in saliva or tracheobronchial secretion of hospitalized COVID-19 patients. Furthermore, we examined if SARS-CoV-2 detection dogs could provide an appropriate screening method for the human virus.The aim of this data publication is to provide the data acquired in the controlled, randomized and double-blinded pilot study `Scent dog identification of SARS-CoV-2 infection’ (submitted to BMC Infectious Diseases).</p>
On the evolutionary epidemiology of SARS-CoV-2
<p><span><span><span><span><span><span><span><span><span><span><span>There is no doubt that the novel coronavirus SARS-CoV-2 that causes COVID-19 is mutating and thus has the potential to adapt during the current pandemic. Whether this evolution will lead to changes in the transmission, the duration, or the severity of the disease is not clear. This has led to considerable scientific and media debate, from raising alarms about evolutionary change to dismissing it. Here we review what little is currently known about the evolution of SARS-CoV-2 and extend existing evolutionary theory to consider how this disease might evolve during the COVID-19 pandemic. While there is currently no definitive evidence that SARS-CoV-2 is undergoing further adaptation, continued, evidence-based, analysis of evolutionary change is important so that public health measures can be adjusted in response to substantive changes in the infectivity or severity of COVID-19.</span></span></span></span></span></span></span></span></span></span></span></p>
Electron microscopy of SARS-CoV-2 particles - Dataset 03
<p>The dataset contains 122 transmission electron microscopy images of ultrathin (60-70 nm) plastic sections through extracellular SARS-CoV-2 particles in Vero cell cultures. Images were recorded with 1376 x 1032 pixel dimensions at 0.64 nm pixel size (12 bit) and stored in 16 bit TIF format. For visualization of the images, use an image viewer capable of reading 16 bit images (e.g. IrfanView). Image files are size calibrated and can be opened with the correct size calibration using ImageJ or Fiji using the Bioformats importer. The image files are accompanied by a PDF document which describes the methods which were used for generation of the images. The dataset was produced as dataset 03 for a comparative morphometric analysis of SARS-CoV and SARS-CoV-2. Further datasets which were used for the analysis are available in this repository (see dataset description document).</p> <p>Related publication: Laue M, Kauter A, Hoffmann T, Möller L, Michel J, Nitsche A. Morphometry of SARS-CoV and SARS-CoV-2 particles in ultrathin plastic sections of infected Vero cell cultures. Sci Rep. 2021 Feb 10;11(1):3515. doi: 10.1038/s41598-021-82852-7. PMID: 33568700; PMCID: PMC7876034.</p>
Electron microscopy of SARS-CoV-2 particles - Dataset 07
<p>The dataset contains 134 transmission electron microscopy images of ultrathin (45 nm) plastic sections through extracellular SARS-CoV-2 particles in Vero cell cultures. Images were recorded with 1376 x 1032 pixel dimensions at 0.54 nm pixel size (12 bit) and stored in 16 bit TIF format. For visualization of the images, use an image viewer capable of reading 16 bit images (e.g. IrfanView). Image files are size calibrated and can be opened with the correct size calibration using ImageJ or Fiji using the Bioformats importer. The image files are accompanied by a PDF document which describes the methods which were used for generation of the images. The dataset was produced as dataset 07 for a comparative morphometric analysis of SARS-CoV and SARS-CoV-2. Further datasets which were used for the analysis are available in this repository (see dataset description document).</p> <p>Related publication: Laue M, Kauter A, Hoffmann T, Möller L, Michel J, Nitsche A. Morphometry of SARS-CoV and SARS-CoV-2 particles in ultrathin plastic sections of infected Vero cell cultures. Sci Rep. 2021 Feb 10;11(1):3515. doi: 10.1038/s41598-021-82852-7. PMID: 33568700; PMCID: PMC7876034.</p>
A Combined approach of MALDI-TOF Mass Spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs.
<p>The spectra were provided as unprocessed raw data in the manufacturers data format (Bruker), as labelled two zip archives with SARS CoV 2 positives and negative, according to the reviewer's recommendation.</p> <p>This information belongs to the publication (in review in <em>Journal of Virological Methods</em>)<br> "A Combined approach of MALDI-TOF Mass Spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs"<br> All the information belongs to the National Reference Institute, INEI-ANLIS DR CARLOS G MALBRAN, BUENOS AIRES, ARGENTINA.</p>
SARS-CoV-2 transmission via speech-generated respiratory droplets
<p>The physics of generating acoustic waves involves the high-speed passage of air pressurized by the lungs through narrow passages, past the mucosal epithelial layers of the vibrating vocal folds. Sounds are further modulated by the passage of this air through narrow passages between the tongue, lips, and teeth, dislodging oral fluid at all of these locations. Generation of droplets is inevitably linked to the physics of speech generation, and not limited to one person as is highlighted in a short video recording</p>
Supplementary material from "Possible fates of the dispersion of SARS-COV-2 in the Mexican context"
<p>The determination of the adequate time for house confinement and when social distancing restrictions should end are now two of the main challenges that any country has to face in an effective battle against. The possibility of a new outbreak of the pandemic and how to avoid it is, nowadays, one of the primary objectives of epidemiological research. In this work, we go deep in this subject by presenting an innovative compartmental model, that explicitly introduces the number of active cases, and employing it as a conceptual tool to explore the possible fates of the dispersion of SARS-COV-2 in the Mexican context. We incorporated the impact of starting, inattention, and end of restrictive social policies on the time evolution of the pandemics via time-in-run corrections to the infection rates. The magnitude and impact on the epidemic due to post-social restrictive policies are also studied. The scenarios generated by the model can help authorities to determine an adequate time and population load that may be allowed to reassume normal activities.</p>
VTR case studies datasets: myoglobin against hemoglobin, RBDs of SARS-CoV-1 vs. SARS-CoV-2, and glucose-tolerant vs. non-tolerant β-glucosidases
<p>Description of the four files:</p> <ol> <li><strong>contacts.xlsx</strong> <ul> <li>List of detected contacts for the three case studies</li> </ul> </li> <li><strong>pymol_files_case_study_1.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 1: comparison between contacts of myoglobin against hemoglobin</li> </ul> </li> <li><strong>pymol_files_case_study_2.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 2: comparison between contacts of RBDs of SARS-CoV-1 vs. SARS-CoV-2 both complexed with the cell receptor ACE2</li> </ul> </li> <li><strong>pymol_files_case_study_3.zip</strong> <ul> <li>Contains files in PDB format of the analyzed structures, and files in PML format used to display visualizations in the PyMOL tool for the case study 3: comparison between contacts of glucose-tolerant vs. non-tolerant β-glucosidases </li> </ul> </li> </ol>
Pandemic-related Attitudes, Stressors and Work Outcomes among Medical Assistants during the SARS-CoV-2 ("Coronavirus") Pandemic in Germany: a cross-sectional Study
<p>File type: SPSS file (.sav)</p> <p>Study type: Cross-sectional study</p> <p>Population: Medical assistants in Germany</p> <p>Study period: April 7th-April 14th, 2020</p> <p>Number of participants: 2150</p> <p>Research question: Investigation of pandemic-related attitudes, stressors and work outcomes among medical assistants during the SARS-CoV-2 (“Coronavirus”) pandemic</p> <p>Missing values: None (due to online survey) </p> <p>Original variables: v_982, v_1, v_2, v_3, v_5, v_6, v_7, v_13, v_14, v_21, v_22, v_23, v_24, v_26, v_27, v_28, v_29, v_31, v_32, v_33, v_40, v_41, v_42, v_43, v_46, v_47, v_48 v_49, v_52, v_57, Beruf_MFA</p> <p>All other variables were calculated from the original variables either by rescaling or dichotomization. </p>
SARS-CoV-2 transmission and control in a hospital setting: an individual-based modelling study
<p><strong>Background</strong>: Development of strategies for mitigating the severity of COVID-19 is now a top public health priority. We sought to assess strategies for mitigating the COVID-19 outbreak in a hospital setting via the use of non-pharmaceutical interventions.</p> <p><strong>Methods</strong>: We developed an individual-based model for COVID-19 transmission in a hospital setting. We calibrated the model using data of a COVID-19 outbreak in a hospital unit in Wuhan. The calibrated model was used to simulate different intervention scenarios and estimate the impact of different interventions on outbreak size and workday loss.</p> <p><strong>Findings</strong>: The use of high efficacy facial masks was shown to be able to reduce infection cases and workday loss by 80% (90% CrI: 73.1% - 85.7%) and 87% (CrI: 80.0% - 92.5%), respectively. The use of social distancing alone, through reduced contacts between healthcare workers, had a marginal impact on the outbreak. Our results also indicated that a quarantine policy should be coupled with other interventions to achieve its effect. The effectiveness of all these interventions was shown to increase with their early implementation.</p> <p><strong>Conclusions</strong>: Our analysis shows that a COVID-19 outbreak in a hospital's non-COVID-19 unit can be controlled or mitigated by the use of existing non-pharmaceutical measures.</p>
Predicting reservoir hosts based on early SARS-CoV-2 samples and analyzing later world-wide pandemic
<p><span>The SARS-CoV-2 pandemic has raised the concern for reservoir hosts of the virus since the early-stage outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting the viral genomic features, to calculate the infection likelihoods and further predict the probable hosts of novel viruses. Overcoming the limitation of sequence similarity-based methods, DeepHoF was applied to the analysis of SARS-CoV-2 in the 2020 pandemic. Using the isolates sequenced in the earliest stage of COVID-19, DeepHoF identified minks, bats, dogs and cats can be highly susceptible to SARS-CoV-2, while minks might be one of the most noteworthy reservoir hosts. Several genes of SARS-CoV-2 demonstrated their significance in determining the infection likelihood on human or the host range. With a large-scale genome analysis based on DeepHoF's computation for the later world-wide pandemic, it should not be slighted for the probably bidirectional transmission of SARS-CoV-2 between humans and minks.</span></p>
Targeted Intracellular Degradation of SARS-CoV-2 via Computationally-Optimized Peptide Fusions
<p>The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has elicited a global health crisis of catastrophic proportions. With only a few vaccines approved for early or limited use, there is a critical need for effective antiviral strategies. In this study, we report a unique antiviral platform, through computational design of ACE2-derived peptides which both target the viral spike protein receptor binding domain (RBD) and recruit E3 ubiquitin ligases for subsequent intracellular degradation of SARS-CoV-2 in the proteasome. Our engineered peptide fusions demonstrate robust RBD degradation capabilities in human cells and are capable of inhibiting infection-competent viral production, thus prompting their further experimental characterization and therapeutic development. </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.