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Found 68 result(s)
The COVID-19 Data Portal was launched in April 2020 to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse COVID-19 related reference data and specialist datasets as part of the wider European COVID-19 Data Platform.
The N3C Data Enclave is a secure portal containing a very large and extensive set of harmonized COVID-19 clinical electronic health record (EHR) data. The data can be accessed through a secure cloud Enclave hosted by NCATS and cannot be downloaded due to regulatory control. Broad access is available to investigators at institutions that sign a Data Use Agreements and via Data Use Requests by investigators. The N3C is a unique open, reproducible, transparent, collaborative team science initiative to leverage sensitive clinical data to expedite COVID-19 discoveries and improve health outcomes.
The COVID-19 pandemic has affected every country in the world. It is well documented that those most susceptible to the worst outcomes of COVID-19 are the immunocompromised and those with underlying comorbidities. Therefore, patients requiring treatment for COVID-19 will also be on additional medication, posing a risk for drug-drug interactions (DDIs). In order to address this, the Liverpool Drug Interactions website team developed this freely available drug interactions resource to provide information on the likelihood of interactions between the experimental agents used for the treatment of COVID-19 and commonly prescribed co-medications.
Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Johns Hopkins experts in global public health, infectious disease, and emergency preparedness have been at the forefront of the international response to COVID-19. This website is a resource to help advance the understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives. All data collected and displayed are made freely available through a GitHub repository https://github.com/CSSEGISandData/COVID-19, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas: https://livingatlas.arcgis.com/en/
The Oxford COVID-19 Government Response Tracker (OxCGRT) systematically collects information on several different common policy responses that governments have taken to respond to the pandemic on 18 indicators such as school closures and travel restrictions. It now has data from more than 180 countries.
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The German Central Health Study Hub COVID-19 (Study Hub) is an inventory of German COVID-19 studies covering structured health data from administrative databases, clinical trials incl. vaccination studies, primary care, epidemiological studies, and public health surveillance. The aim is to enable the findability of studies and access to structured health data to improve the management of public health data on the COVID-19 pandemic. Unlike other initiatives, the Study Hub will focus not only on clinical research but also on studies relating to the consequences of the pandemic for public health, such as utilisation of healthcare services, quality of life, and the effects of social isolation. Furthermore, the Study Hub provides access to the study documents and data collection instruments like (sample) questionnaires, including information down to the variable level. The Study Hub has been created in the project NFDI4Health Task Force COVID-19 (DFG project number 451265285), which is an additionally funded use case of the National Research Data Infrastructure for Personal Health Data – NFDI4Health (DFG project number 442326535).
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Contains data on patients who have been tested for COVID-19 (whether positive or negative) in participating health institutions in Brazil. This initiative makes available three kinds of pseudonymized data: demographics (gender, year of birth, and region of residency), clinical and laboratory exams. Additional hospitalization information - such as data on transfers and outcomes - is provided when available. Clinical, lab, and hospitalization information is not limited to COVID-19 data, but covers all health events for these individuals, starting November 1st 2019, to allow for comorbidity studies. Data are deposited periodically, so that health information for a given individual is continuously updated to time of new version upload.
To help flattening the COVID-19 curve public health systems need better information on whether preventive measures are working and how the virus may spread. Facebook Data for Good offer maps on population movement that researchers and nonprofits are already using to understand the coronavirus crisis, using aggregated data to protect people’s privacy.
Research Collaborators & Institutions related to Coronavirus Epidemic Aim: Identify potential research experts or collaborators in areas related to the coronavirus epidemic across basic science, translational research, or clinical practice. Scope: A selection of Researchers active or cited in the area of Coronavirus, Middle East Respiratory Syndrome (MERS), SARS, etc.
The Infectious Diseases Data Observatory (IDDO) assembles clinical, laboratory and epidemiological data on a collaborative platform to be shared with the research and humanitarian communities. The data are analysed to generate reliable evidence and innovative resources that enable research-driven responses to the major challenges of emerging and neglected infections. Access is available to individual patient data held for malaria and Ebola virus disease. Resources for visceral leishmaniasis, schistosomiasis and soil transmitted helminths, Chagas disease and COVID-19 are under development. IDDO contains the following repositories : COVID-19 Data Platform, Chagas Data Platform, Schistosomiasis & Soil Transmitted Helminths Data Platform, Visceral Leishmaniasis Data Platform, Ebola Data Platform, WorldWide Antimalarial Resistance Network (WWARN)
Novartis provides the technical results and trial summaries for patients from Phase 1 through 4 interventional trials for innovative products within one year of trial completion. A trial summary for patients is a trial result written in easier to understand language than the technical results.
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Risklayer Explorer is a collaboration between Risklayer GmbH and the Karlsruhe Institute of Technology's Center for Disaster Risk Management and Risk Reduction Technology (CEDIM). This website is still under development, but we are going live with it already, because we want to present data on the Novel Coronavirus (COVID-19) to help inform the public of the current situation. You will be able to track disaster events and read about our analysis here. Our work is a continuation of a new style of disaster research started by CEDIM in 2011 to analyze disasters immediately after their occurrence, assess the impacts, and retrace the temporal development of disaster events. We are already analyzing damaging earthquakes globally, providing you with event characteristics, earthquake's intensity footprints, as well as the population affected by earthquakes. In addition to earthquake events, we expect to be tracking and analyzing tropical cyclone, volcano and extreme weather events in 2020.
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VirHostNet is a bioinformatic information system dedidacted to the biocuration, data integration, reproducible systems-level analysis and visualisation of Virus / Host protein-protein interactions Network based on graph theory. VirHostNet is an open and gold standard knowledgebase shared in PSI MITAB 2.5 format using the PSICQUIC webservice and distributed through the NDEx platform. VirHostNet is FAIR and is recognized as a COVID-19 ressource by Elixir bio.tools, the European Virus Bioinformatics Center and FAIRsharing.org.
The Coronavirus Antiviral Research Database is designed to expedite the development of SARS-CoV-2 antiviral therapy. It will benefit global coronavirus drug development efforts by (1) promoting uniform reporting of experimental results to facilitate comparisons between different candidate antiviral compounds; (2) identifying gaps in coronavirus antiviral drug development research; (3) helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development; (4) providing an objective, evidenced-based, source of information for the public; and (5) creating a hub for the exchange of ideas among coronavirus researchers whose feedback is sought and welcomed. By comprehensively reviewing all published laboratory, animal model, and clinical data on potential coronavirus therapies, the Database makes it unlikely that promising treatment approaches will be overlooked. In addition, by making it possible to compare the underlying data associated with competing treatment strategies, stakeholders will be better positioned to prioritize the most promising anti-coronavirus compounds for further development.
The Lens is building an open platform for Innovation Cartography. Specifically, the Lens serves nearly all of the patent documents in the world as open, annotatable digital public goods that are integrated with scholarly and technical literature along with regulatory and business data.
The Health Data Research Innovation Gateway (the ‘Gateway’) provides a common entry point to discover and enquire about access to UK health datasets for research and innovation. It provides detailed information about the datasets, which are held by members of the UK Health Data Research Alliance, such as a description, size of the population, and the legal basis for access. The Gateway includes the ability to search for research projects, publications and health data tools, such as those related to COVID-19. New interactive features provide a community forum for researchers to collaborate and connect and the ability to add research projects. The Innovation Gateway does not hold or store any datasets or patient or health data but rather acts as a portal to allow discovery of datasets and to request access to them for health research. A dataset is a collection of related individual pieces of data but in the case of health data, identifiable information (e.g. name or NHS number) is removed and data is de-identified where possible. When you access the Gateway you will not be able to view or extract the data itself. Instead, you will be able to see information that describes what the different datasets are (e.g. where the dataset has come from, a description of the dataset, the time period and the geographical areas the dataset covers).
WorldData.AI comes with a built-in workspace – the next-generation hyper-computing platform powered by a library of 3.3 billion curated external trends. WorldData.AI allows you to save your models in its “My Models Trained” section. You can make your models public and share them on social media with interesting images, model features, summary statistics, and feature comparisons. Empower others to leverage your models. For example, if you have discovered a previously unknown impact of interest rates on new-housing demand, you may want to share it through “My Models Trained.” Upload your data and combine it with external trends to build, train, and deploy predictive models with one click! WorldData.AI inspects your raw data, applies feature processors, chooses the best set of algorithms, trains and tunes multiple models, and then ranks model performance.
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
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The UMIN case data repository system was implemented by adding a function to the UMIN Clinical Trials Registry System. The aim of this system is to keep anonymized case data from clinical research conducted by individual researchers at the UMIN center, and to guarantee the content of the data to third parties. This system enables other researchers to inspect case data or to repeat statistical analyses
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PsychArchives is a disciplinary repository publishing a variety of digital research objects (DROs), with 21 different publication types (preprints, primary, and secondary publications), research data, tests, preregistrations, multimedia and code. It provides easy and free access to DROs according to the FAIR principles, which implies the commitment to ensure that research and research data are findable, accessible, interoperable, and reusable.
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DisGeNET is a discovery platform containing one of the largest publicly available collections of genes and variants associated to human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships.
MassIVE is a community resource developed by the NIH-funded Center for Computational Mass Spectrometry to promote the global, free exchange of mass spectrometry data. MassIVE datasets can be assigned ProteomeXchange accessions to satisfy publication requirements.
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The mission of ChiCTR is to “unite clinicians, clinical epidemiologists, biostatisticians, epidemiologists and healthcare managers both at home and abroad, to manage clinical trials in a strict and scientific manner, and to promote their quality in China, so as to provide reliable evidence from clinical trials for health care workers, consumers and medical policy decision makers, and also to use medical resources more effectively to provide better service for Chinese people and all human beings.