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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
https://ncats.nih.gov/n3c/about
Portal for centralized national data to study COVID-19 and identify potential treatments.Centralized, secure analytics platform where patient privacy is protected. Enables collection and analysis of clinical, laboratory and diagnostic data from hospitals and health care plans. Data are provided after executing data transfer agreement with National Center for Advancing Translational Sciences. N3C is partnership among NCATS supported Clinical and Translational Science Awards Program hubs and National Center for Data to Health with overall stewardship by NCATS.
Proper citation: National COVID Cohort Collaborative (RRID:SCR_018757) Copy
https://marks.hms.harvard.edu/sars-cov-2/
Portal for quantitative models using virus sequence variation to predict mutation effects for SARS-CoV-2 proteins, alignments to homologs in other viruses, 3D structures, evolutionarily coupled residues and structure predictions.
Proper citation: SARS-CoV-2 mutation effects and 3D structure prediction from sequence covariation (RRID:SCR_018759) Copy
https://app.terra.bio/#workspaces/pathogen-genomic-surveillance/COVID-19
Broad Terra cloud workspace for best practices with COVID-19 genomics data. Raw COVID-19 sequencing data from NCBI Sequence Read Archive. Workflows for genome assembly, quality control, metagenomic classification, and aggregate statistics.
Proper citation: Broad Terra cloud commons for pathogen surveillance (RRID:SCR_018278) Copy
https://www.go-fair.org/implementation-networks/overview/vodan/
Network as federated AI-ready repository of COVID-19 data adherent to FAIR principles. SARS CoV-2 virus data FAIR, meaning that they are Findable, Accessible, Interoperable and thus Reusable by both humans and machines, during this epidemic of COVID-19.
Proper citation: Virus Outbreak Data Network (RRID:SCR_018285) Copy
https://covic.lji.org/databases/
Serves as clearinghouse for monoclonal antibodies against SARS-CoV-2. Database will catalog contributed antibodies in searchable resource and provide interactive analysis tools for comparisons among them. Most potent antibodies will guide development of vaccines to stop current outbreak and protect against future pandemics.
Proper citation: CoVIC-DB Database (RRID:SCR_018339) Copy
https://www.addgene.org/collections/covid-19-resources/
Collections of Addgene plasmids, open access articles, protocols, and other resource collections related to COVID-19 that may be of use to scientists. Ordering or depositing plasmids related to COVID-19 research.
Proper citation: COVID-19 and Coronavirus plasmids and resources (RRID:SCR_018347) Copy
Consortium to unite efforts and resources from experts across globe to advance effective, antibody based therapies against novel coronavirus, SARS-CoV-2. Represents multidisciplinary convergence of structural biology, virologists, immunologists, clinicians and bioinformaticians from academic and industry settings. Collects antibodies for testing as part of CoVICS. Contributed antibodies are blinded and will only be known as code name. Antibody contributors will be able to see performance of their own molecules and take part in analysis. Contributors retain ownership of their antibodies and may continue to publish on them using original antibody names. Goal is to determine relative in vitro potency and in vivo efficacy using centralized standardized assays to identify best individual mAbs and rational combinations of mAbs. Consortium will recommend ideal therapeutic molecules for human use to protect vulnerable populations from COVID-19 disease. CoVIC database (CoVIC-DB) will serve as clearinghouse for monoclonal antibodies against SARS-CoV-2. Database will catalog contributed antibodies in searchable resource and provide interactive analysis tools for comparisons among them.
Proper citation: Coronavirus Immunotherapy Consortium (RRID:SCR_018258) Copy
Platform for global network of researchers to investigate role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Provides results of three genome-wide association meta analyses that consist of patients with COVID-19 from studies across countries.
Proper citation: COVID-19 Host Genetics Initiative (RRID:SCR_022272) Copy
https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge
Collection of scholarly articles about COVID-19 and coronavirus family of viruses for use by global research community. Dataset is updated on weekly basis.
Proper citation: COVID-19 Open Research Dataset (RRID:SCR_018336) Copy
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