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Found 13 result(s)

WorldData.AI

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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.

VirHostNet

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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.

Risklayer Explorer

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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.

SARS-CoV-2 Data Hub

SARS-CoV

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This Web resource provides data and information relevant to SARS coronavirus. It includes links to the most recent sequence data and publications, to other SARS related resources, and a pre-computed alignment of genome sequences from various isolates. In order to provide free and easy access to genome and protein sequences and associated metadata from the SARS-CoV-2, we created a dedicated Severe acute respiratory syndrome coronavirus 2 data hub. You can access the Results Table on SARS-CoV-2 data hub, by pressing "RefSeq genomes", "nucleotide" or "protein" links on announcement banner located on NCBI home page, in "Find data" navigation menu or using "Up-to-date SARS-CoV-2" shortcut button in "Search by virus" form. SARS-CoV-2 sequences is part of NCBI Virus https://www.re3data.org/repository/r3d100014322

The Lens

Lens COVID-19 Datasets

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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.

Biobanque québécoise de la COVID-19

BQC19

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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.

Comparative Toxicogenomics Database

CTD

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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.

Coronavirus Antiviral Research Database

COVDB

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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.

Facebook Data for Good

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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.

DisGeNET

A knowledge base for disease genomics

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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.

Liverpool COVID-19 Drug Interactions

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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.

euHCVdb

european Hepatitis C Virus database

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The euHCVdb is mainly oriented towards protein sequence, structure and function analyses and structural biology of HCV.

COVID-19 Research Collaborations

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