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URL: https://covidcg.org/?tab=home
Proper Citation: COVID CG (RRID:SCR_022266)
Description: Open browser to inform therapeutics development for tracking SARS-CoV-2 single nucleotide variations, lineages, and clades using virus genomes on GISAID database while filtering by location, date, gene, and mutation of interest. can Provides information on which virus mutations are present in area during specific period by processing data on mutations found in viral genetic material collected worldwide from hundreds of thousands of people with COVID-19, which are hosted in existing online database.
Synonyms: COVID-19 CG, covidcg.org, COVID-19 CoV Genetics (CG), COVID-19 CoV Genetics
Resource Type: data processing software, software application, software resource
Defining Citation: DOI:10.7554/eLife.63409
Keywords: SNVs, Single Nucleotide Variations, single nucleotide variations, tracking SARS-CoV-2, virus genomes, GISAID database, virus mutations, processing data on mutations found in viral genetic material, COVID-19
Availability: Free, Available for download, Freely available
Resource Name: COVID CG
Resource ID: SCR_022266
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Source: SciCrunch Registry (RRID:SCR_005400)
Description: Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.
URL: https://rrid.site/rin/sources/SCR_005400
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
Email: info_at_ dknet.org
