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44 results for “monkeypox”
BioPropaPhenKG Towards Monkeypox and COVID-19 Case Tracing and Analysing
<p>This repository contains:</p> <ul> <li>The BioPropaPhen ontology created from PropaPhen, being specialized with UMLS and World Knowledge Graph ontologies;</li> <li>A neo4j 4.4.3 dump file of the BioPropaPhenKG knowledge graph with WHO ground truth data about COVID-19 and Monkeypox, and enhanced presence edges between UMLS entities to World KG entities for evaluating the<a href="https://github.com/Gabriel382/DDPF-Health-Risks"> Description-Detection-Prediction Framework </a></li> </ul> <p>The datasets used for enhancing the KG are:</p> <table> <tbody> <tr> <td>Phenomenon</td> <td>Dataset</td> <td>Period</td> <td>Documents</td> <td>Source</td> <td>Link</td> </tr> <tr> <td>COVID-19</td> <td>Aylien</td> <td>Nov-2019</td> <td>8</td> <td>Online News</td> <td>ttps://aylien.com/resources/datasets/coronavirus-dataset</td> </tr> <tr> <td>COVID-19</td> <td>CORD-19</td> <td>Dec-2019</td> <td>720</td> <td>Medical Articles</td> <td>https://allenai.org/data/cord-19</td> </tr> <tr> <td>COVID-19</td> <td>RedditCOVID</td> <td>Feb-2020</td> <td>4,980</td> <td>Social Media</td> <td>https://paperswithcode.com/dataset/the-reddit-covid-dataset</td> </tr> <tr> <td>Monkeypox</td> <td>Mined from BBC</td> <td>May-2022</td> <td>27</td> <td>Online News</td> <td> </td> </tr> <tr> <td>Monkeypox</td> <td>Mined from Pubmed</td> <td>June-2022</td> <td>36</td> <td>Medical Articles</td> <td> </td> </tr> <tr> <td>Monkeypox</td> <td>MonkeyPox2022</td> <td>May-2022</td> <td>33,826</td> <td>Social Media</td> <td>https://doi.org/10.3390/idr14060087</td> </tr> </tbody> </table>
Supplement to: Enhanced surveillance of monkeypox in Bas-Uélé, Democratic Republic of Congo: the limitations of symptom-based case definitions
<p>This repository contains data and R code which are supplements to:</p> <p><em>Enhanced surveillance of monkeypox in Bas-Uélé, Democratic Republic of Congo: the limitations of symptom-based case definitions</em><br> Gaspard Mande, Innocent Akonda, Anja De Weggheleire, Isabel Brosius, Laurens Liesenborghs, Emmanuel Bottieau, Noam Ross, Guy Crispin Gembue, Robert Colebunders, Erik Verheyen Ngonda Daulya, Herwig Leirsh, and Anne Laudisoit (2022).</p> <p>A data dictionary and instructions for reproducing the analysis are provided. Details can be found in the README.md file.</p>
Comprehensive Single Point Mutational Landscape Analysis of the Monkeypox Virus Proteome
Open the record for dataset details and reuse information.
A Twitter dataset for Monkeypox outbreak in 2022
<p><span><span>Right after the COVID-19 pandemic, the Monkeypox virus has infected people from more than twenty different countries. The COVID-19 pandemic has badly hit the healthcare system, social culture, and the global economy. The world does not have the strength to go through another catastrophe. Thus, it is very important to contain Monkeypox and stop the spread. This dataset includes the tweet id and user id of </span></span><span>2,400,202</span> tweets gathered using keywords related to Monkeypox for researchers to study on different subjects such as Monkeypox trend prediction, Monkeypox stigmatization, and Monkeypox misinformation and fake news detection.</p>
Data from: Pathogen reduction of monkeypox virus in plasma and whole blood using riboflavin and UV light
<p>Background</p> <p>Monkeypox virus has recently emerged from endemic foci in Africa and, to date, several hundred human infections have been reported from at least 16 non-African countries. The detection of virus in skin lesions, blood, semen, and saliva of infected patients with monkeypox infections raises the potential for disease transmission via routes that have not been previously documented, including by blood and plasma transfusions. Methods for protecting the blood supply against the threats of newly emerging disease agents exist and include Pathogen Reduction Technologies (PRT) which utilize photochemical treatment processes to inactivate pathogens in blood while preserving the integrity of plasma and cellular components. Such methods have been employed broadly for over 15 years, but effectiveness of these methods under routine use conditions against monkeypox virus has not been reported.</p> <p>Results</p> <p>The levels of spiked virus present in whole blood and plasma samples exceeded 103 infectious particles per dose, corresponding to greater than 105 DNA copies per mL. Treatment of whole blood and plasma units under standard operating procedures for the Mirasol PRT System resulted in complete inactivation of infectivity to the limits of detection. This is equivalent to a reduction of ≥ 2.86 +/- 0.73 log10 pfu/mL of infectivity in whole blood and ≥ 3.47 +/-0.19 log10 pfu/mL of infectivity in plasma under standard operating conditions for those products. </p> <p>Conclusion</p> <p>Based on this data and corresponding studies on infectivity in patients with monkeypox infections, use of Mirasol PRT would be expected to significantly reduce the risk of transfusion transmission of monkeypox.</p>
Tecovirimat for Treatment of Monkeypox Virus
ClinicalTrials.gov study NCT05559099. IPD Sharing: NO. Countries: 1. Publications: 1.
Trial to Evaluate the Immunogenicity of Dose Reduction Strategies of the MVA-BN Monkeypox Vaccine
ClinicalTrials.gov study NCT05512949. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Pathogen reduction of monkeypox virus in plasma and whole blood using riboflavin and UV light
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A Twitter dataset for Monkeypox outbreak in 2022
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Monkeypox virus emergence in wild chimpanzees reveals distinct clinical outcomes and viral diversity
<p>Here we provide the 14 annotated monkeypox virus genomes detected in wild chimpanzees living in Tai National Park in 2017 and 2018.</p>
MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research Questions
<p><strong>Please cite the following paper when using this dataset:</strong></p> <p>N. Thakur, “MonkeyPox2022Tweets: A large-scale Twitter dataset on the 2022 Monkeypox outbreak, findings from analysis of Tweets, and open research questions,” Infect. Dis. Rep., vol. 14, no. 6, pp. 855–883, 2022, DOI: https://doi.org/10.3390/idr14060087</p> <p><strong>Abstract</strong></p> <p>The mining of Tweets to develop datasets on recent issues, global challenges, pandemics, virus outbreaks, emerging technologies, and trending matters has been of significant interest to the scientific community in the recent past, as such datasets serve as a rich data resource for the investigation of different research questions. Furthermore, the virus outbreaks of the past, such as COVID-19, Ebola, Zika virus, and flu, just to name a few, were associated with various works related to the analysis of the multimodal components of Tweets to infer the different characteristics of conversations on Twitter related to these respective outbreaks. The ongoing outbreak of the monkeypox virus, declared a Global Public Health Emergency (GPHE) by the World Health Organization (WHO), has resulted in a surge of conversations about this outbreak on Twitter, which is resulting in the generation of tremendous amounts of Big Data. There has been no prior work in this field thus far that has focused on mining such conversations to develop a Twitter dataset. Therefore, this work presents an open-access dataset of <strong>571,831 Tweets</strong> about monkeypox that have been posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset complies with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.</p> <p> <strong>Data Description</strong></p> <p>The dataset consists of a total of <strong>571,831 Tweet IDs</strong> of the same number of tweets about monkeypox that were posted on Twitter from 7th May 2022 to 11th November (the most recent date at the time of uploading the most recent version of the dataset). The Tweet IDs are presented in 12 different .txt files based on the timelines of the associated tweets. The following represents the details of these dataset files.</p> <ul> <li>Filename: TweetIDs_Part1.txt (No. of Tweet IDs: 13926, Date Range of the associated Tweet IDs: May 7, 2022, to May 21, 2022)</li> <li>Filename: TweetIDs_Part2.txt (No. of Tweet IDs: 17705, Date Range of the associated Tweet IDs: May 21, 2022, to May 27, 2022)</li> <li>Filename: TweetIDs_Part3.txt (No. of Tweet IDs: 17585, Date Range of the associated Tweet IDs: May 27, 2022, to June 5, 2022)</li> <li>Filename: TweetIDs_Part4.txt (No. of Tweet IDs: 19718, Date Range of the associated Tweet IDs: June 5, 2022, to June 11, 2022)</li> <li>Filename: TweetIDs_Part5.txt (No. of Tweet IDs: 46718, Date Range of the associated Tweet IDs: June 12, 2022, to June 30, 2022)</li> <li>Filename: TweetIDs_Part6.txt (No. of Tweet IDs: 138711, Date Range of the associated Tweet IDs: July 1, 2022, to July 23, 2022)</li> <li>Filename: TweetIDs_Part7.txt (No. of Tweet IDs: 105890, Date Range of the associated Tweet IDs: July 24, 2022, to July 31, 2022)</li> <li>Filename: TweetIDs_Part8.txt (No. of Tweet IDs: 93959, Date Range of the associated Tweet IDs: August 1, 2022, to August 9, 2022)</li> <li>Filename: TweetIDs_Part9.txt (No. of Tweet IDs: 50832, Date Range of the associated Tweet IDs: August 10, 2022, to August 24, 2022)</li> <li>Filename: TweetIDs_Part10.txt (No. of Tweet IDs: 39042, Date Range of the associated Tweet IDs: August 25, 2022, to September 19, 2022)</li> <li>Filename: TweetIDs_Part11.txt (No. of Tweet IDs: 12341, Date Range of the associated Tweet IDs: September 20, 2022, to October 9, 2022)</li> <li>Filename: TweetIDs_Part12.txt (No. of Tweet IDs: 15404, Date Range of the associated Tweet IDs: October 10, 2022, to November 11, 2022) </li> </ul> <p>Please note: The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset, the <a href="https://github.com/DocNow/hydrator/releases">Hydrator application</a> may be used (a step-by-step process on how to use Hydrator to hydrate this dataset is explained in the above-mentioned paper). </p>
Assessment of the Efficacy and Safety of Tecovirimat in Patients With Monkeypox Virus Disease
ClinicalTrials.gov study NCT05597735. IPD Sharing: NO. Countries: 3. Publications: 9.
A One Health Study of Monkeypox Human Infection
ClinicalTrials.gov study NCT05058898. IPD Sharing: NO. Countries: 1. Publications: 2.
A Clinical Study Investigating the Safety and Immune Responses After Immunization With Investigational Monkeypox Vaccines
ClinicalTrials.gov study NCT05988203. IPD Sharing: NO. Countries: 2. Publications: 1.
Monkeypox ASymptomatic Shedding: Evaluation by Self-Sampling MPX-ASSESS
ClinicalTrials.gov study NCT05443867. IPD Sharing: YES. Countries: 1. Publications: 1.
ChIP-seq of human embryonic stem cells (hESCs) overexpressed with Monkeypox viral proteins H3L and A29L
GEO Series GSE239888. Homo sapiens. 19 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Primary human intestinal organoids recapitulate enteric infection of monkeypox virus and enable scalable drug discovery
GEO Series GSE298715. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
A multivalent mRNA vaccine elicits robust immune responses and confers protection in a murine model of monkeypox virus infection
GEO Series GSE276667. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing; Other.
Virological characterization of the 2022 outbreak-causing monkeypox virus using human keratinocytes and colon organoids
GEO Series GSE219036. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Comparison of host cell gene expression in cowpox, monkeypox or vaccinia virus infected cells reveals virus-specific regulation of immune response genes
GEO Series GSE36854. Homo sapiens. 8 samples. Type: Expression profiling by array.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.