首页|RCoV19:A One-stop Hub for SARS-CoV-2 Genome Data Integration,Variant Monitoring,and Risk Pre-warning
RCoV19:A One-stop Hub for SARS-CoV-2 Genome Data Integration,Variant Monitoring,and Risk Pre-warning
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NETL
NSTL
万方数据
The Resource for Coronavirus 2019(RCoV19)is an open-access information resource dedicated to providing valuable data on the genomes,mutations,and variants of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).In this updated implementation of RCoV19,we have made significant improvements and advancements over the previous version.Firstly,we have implemented a highly refined genome data curation model.This model now features an auto-mated integration pipeline and optimized curation rules,enabling efficient daily updates of data in RCoV19.Secondly,we have developed a global and regional lineage evolution monitoring plat-form,alongside an outbreak risk pre-warning system.These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns,enabling better preparedness and response strategies.Thirdly,we have developed a powerful interactive mutation spectrum com-parison module.This module allows users to compare and analyze mutation patterns,assisting in the detection of potential new lineages.Furthermore,we have incorporated a comprehensive knowledgebase on mutation effects.This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations.In summary,RCoV19 serves as a vital scientific resource,providing access to valuable data,relevant information,and technical sup-port in the global fight against COVID-19.The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.
National Genomics Data Center,Beijing Institute of Genomics,Chinese Academy of Sciences and China National Center for Bioinformation,Beijing 100101,China
CAS Key Laboratory of Genome Sciences and Information,Beijing Institute of Genomics,Chinese Academy of Sciences and China National Center for Bioinformation,Beijing 100101,China
University of Chinese Academy of Sciences,Beijing 100049,China
Sino-Danish College,University of Chinese Academy of Sciences,Beijing 100049,China
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National Key R&D Program of ChinaNational Key R&D Program of ChinaKey Collaborative Research Program of the Alliance of International Science OrganizationsNational Natural Science Foundation of ChinaBeijing Nova ProgramYouth Innovation Promotion Association of the Chinese Academy of Sciences,ChinaYouth Innovation Promotion Association of the Chinese Academy of Sciences,China
NETL
NSTL
万方数据
