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Found 11 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.
We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.
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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.
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The CyberCell database (CCDB) is a comprehensive collection of detailed enzymatic, biological, chemical, genetic, and molecular biological data about E. coli (strain K12, MG1655). It is intended to provide sufficient information and querying capacity for biologists and computer scientists to use computers or detailed mathematical models to simulate all or part of a bacterial cell at a nanoscopic (10-9 m), mesoscopic (10-8 m).The CyberCell database CCDB actually consists of 4 browsable databases: 1) the main CyberCell database (CCDB - containing gene and protein information), 2) the 3D structure database (CC3D – containing information for structural proteomics), 3) the RNA database (CCRD – containing tRNA and rRNA information), and 4) the metabolite database (CCMD – containing metabolite information). Each of these databases is accessible through hyperlinked buttons located at the top of the CCDB homepage. All CCDB sub-databases are fully web enabled, permitting a wide variety of interactive browsing, search and display operations. and microscopic (10-6 m) level.
The Avian Knowledge Network (AKN) is an international network of governmental and non-governmental institutions and individuals linking avian conservation, monitoring and science through efficient data management and coordinated development of useful solutions using best-science practices based on the data.
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The ICES Data Repository consists of record-level, coded and linkable health data sets. It encompasses much of the publicly funded administrative health services records for the Ontario population eligible for universal health coverage since 1986 and is capable of integrating research-specific data, registries and surveys. Currently, the repository includes health service records for as many as 13 million people. Files in the ICES Data Repository are described in the Data Dictionary. This includes ICES General Use Data, as well as ICES Controlled Use Data. Datasets obtained by ICES for specific project(s) (project-specific data) are not described in the Data Dictionary. The ICES Data Dictionary is an essential resource for anyone doing research at ICES. The information in this Data Dictionary is almost entirely based on the metadata belonging to the datasets described.
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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.
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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.
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The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education.
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The CHILDdb platform provides access to data produced by the CHILD project, a longitudinal birth cohort study of children from pregnancy to 8 years of age, across four Canadian provinces. This study analyzes the participants' home environment including physical, chemical, viral, bacterial, nutritional and psychosocial exposures. This data is expected to further knowledge of the genetic and environmental determinants of atopic diseases including asthma, allergy, allergic rhinitis, and eczema. Researchers can create an account to view meta and aggregate data; access demographic data summaries based on selected variables; and submit a scientific Concept Proposal for approval to access individual-level study data.