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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.

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On page 3 showing 41 ~ 49 out of 49 results
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https://midasnetwork.us/covid-19/

Portal for COVID-19 modeling research. Public access data collections with documented metadata.Computational models to study transmission dynamics of broad range of infectious diseases.

Proper citation: Modeling Infectious Disease Agents Study online portal for COVID-19 (RRID:SCR_018281) Copy   


https://www.xsede.org/covid19-hpc-consortium

Consortium encompasses computing capabilities from powerful and advanced computers in the world. Used to empower researchers to accelerate understanding of COVID-19 virus and development of treatments and vaccines to help address infections. Teams who receive Consortium access will publish their results in open scientific literature. All supported projects will have name of principal investigator, project title and project abstract posted to COVID-19 HPC Consortium web site.

Proper citation: COVID-19 High Performance Computing Consortium (RRID:SCR_018287) Copy   


https://www.gisaid.org/

Portal to share hCoV-19 genome sequences. Collection of genome sequences and related clinical and epidemiological data associated with coronavirus hCoV-19. Global repository of SARS-CoV-2 genomes. Initiative involves public-private-partnerships between Freunde of GISAID and governments of Federal Republic of Germany, Singapore and United States of America, with support from private and corporate philanthropy.International database of hCoV-19 genome sequences and related clinical and epidemiological data. Resource for influenza and hCoV-19 data.

Proper citation: Global Initiative on Sharing All Influenza Data (RRID:SCR_018251) Copy   


https://amp.pharm.mssm.edu/covid19/

Software tool as interface to submit, serve, and analyze COVID19 related gene and drug sets. Collection of gene and drug sets related to COVID-19 research contributed by community.

Proper citation: COVID-19 Crowd Generated Gene and Drug Set Library (RRID:SCR_018252) Copy   


  • RRID:SCR_018260

    This resource has 50+ mentions.

http://glycam.org/

Web provides tools for modeling 3D structures of molecules and complexes containing carbohydrates including oligosaccharide conformation modeling and glycoprotein 3D structure modeling. Used to simplify prediction of three dimensional structures of carbohydrates and macromolecular structures involving carbohydrates.

Proper citation: GLYCAM-Web (RRID:SCR_018260) Copy   


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   


  • RRID:SCR_018814

https://mousecovid.org

Portal for Global Mouse Models for COVID-19 consortium. Presents consortium, its statement and membership, and URLs for mouse COVID-19 resources worldwide.

Proper citation: mousecovid.org (RRID:SCR_018814) Copy   


https://covid19questions.org/

Resource for questions and answers about COVID-19.Electronic health record data from leading medical centers to answer clinical questions related to COVID-19 while maintaining patient and institutional privacy. Data never leaves medical centers, only aggregate statistics are exchanged.

Proper citation: COVID-19 Data Discovery from Clinical Records (RRID:SCR_019097) Copy   



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