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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.
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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.
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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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CTD is a robust, publicly available database that aims to advance understanding about how environmental exposures affect human health. It provides manually curated information about chemical–gene/protein interactions, chemical–disease and gene–disease relationships. These data are integrated with functional and pathway data to aid in development of hypotheses about the mechanisms underlying environmentally influenced diseases. We also have additional ongoing projects involving manual curation of exposome data and chemical–phenotype relationships to help identify pre–disease biomarkers resulting from environmental exposures. The initial release of CTD was on November 12, 2004. We’re grateful to our strong community support and encourage you to give us feedback so we can continue to evolve with your research needs.