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Found 8 result(s)
COViMS (COVID-19 Infections in MS & Related Diseases) is a joint effort of the National MS Society, Consortium of MS Centers and Multiple Sclerosis Society of Canada to capture information on outcomes of people with MS and other CNS demyelinating diseases (Neuromyelitis Optica, or MOG antibody disease) who have developed COVID-19.
Country
BenchSci is a free platform designed to help biomedical research scientists quickly and easily identify validated antibodies from publications. Using various filters including techniques, tissue, cell lines, and more, scientists can find out published data along with the antibody that match specific experimental contexts within seconds. Free registration & access for academic research scientists.
Country
Since 2004, the Leibniz Institute for Prevention Research and Epidemiology – BIPS has been working on the establishment and maintenance of the project-based German Pharmacoepidemiological Research Database (short GePaRD). GePaRD is based on claims data from statutory health insurance (SHI) providers and currently includes information on about 20 million persons who have been insured with one of the participating providers since 2004. Per data year, there is information on approximately 17% of the general population from all geographical regions of Germany.
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The Biobanque québécoise de la COVID-19 (BQC19) is a pan-provincial initiative that collects, stores and shares data and blood samples from COVID-19 patients, both severe and non-severe cases and control cases, in an effort to respond effectively to the public health challenges posed by the pandemic. BQC19 believes that better understanding the disease will help society in returning to social activities and in preparing for future pandemics. It sees access to high-quality samples and data as essential in fulfilling research and works to bring about national and international research collaborations.
Country
InTOR is the institutional digital repository of the Institute of Virology, Vaccines and Sera “Torlak”. It provides open access to publications and other research outputs resulting from the projects implemented by the Institute of Virology, Vaccines and Sera “Torlak”. The software platform of the repository is adapted to the modern standards applied in the dissemination of scientific publications and is compatible with international infrastructure in this field.
Country
From April 2020 to March 2023, the Covid-19 Immunity Task Force (CITF) supported 120 studies to generate knowledge about immunity to SARS-CoV-2. The subjects addressed by these studies include the extent of SARS-CoV-2 infection in Canada, the nature of immunity, vaccine effectiveness and safety, and the need for booster shots among different communities and priority populations in Canada. The CITF Databank was developed to further enhance the impact of CITF funded studies by allowing additional research using the data collected from CITF-supported studies. The CITF Databank centralizes and harmonizes individual-level data from CITF-funded studies that have met all ethical requirements to deposit data in the CITF Databank and have completed a data sharing agreement. The CITF Databank is an internationally unique resource for sharing epidemiological and laboratory data from studies about SARS-CoV-2 immunity in different populations. The types of research that are possible with data from the CITF Databank include observational epidemiological studies, mathematical modelling research, and comparative evaluation of surveillance and laboratory methods.
The Allele Frequency Net Database (AFND) is a public database which contains frequency information of several immune genes such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex class I chain-related (MIC) genes, and a number of cytokine gene polymorphisms. The Allele Frequency Net Database (AFND) provides a central source, freely available to all, for the storage of allele frequencies from different polymorphic areas in the Human Genome. Users can contribute the results of their work into one common database and can perform database searches on information already available. We have currently collected data in allele, haplotype and genotype format. However, the success of this website will depend on you to contribute your data.