Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2

• Published in: Briefings in bioinformatics Vol. 23; no. 2
• Main Authors: Yu, Dalang, Yang, Xiao, Tang, Bixia, Pan, Yi-Hsuan, Yang, Jianing, Duan, Guangya, Zhu, Junwei, Hao, Zi-Qian, Mu, Hailong, Dai, Long, Hu, Wangjie, Zhang, Mochen, Cui, Ying, Jin, Tong, Li, Cui-Ping, Ma, Lina, Su, Xiao, Zhang, Guoqing, Zhao, Wenming, Li, Haipeng
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 10.03.2022; Oxford Publishing Limited (England)
• Subjects: Computational Biology - methods; Coronaviruses; COVID-19; COVID-19 - epidemiology; COVID-19 - virology; Data retrieval; Databases, Genetic; Disease transmission; DNA Mutational Analysis; Epidemiology; Evolution; Genome, Viral; Genomics; Humans; Java; Molecular Epidemiology - methods; Molecular Sequence Annotation; Mutation; Nomenclature; Pandemics; Positive selection; Problem Solving Protocol; Public Health Surveillance - methods; SARS-CoV-2 - genetics; Severe acute respiratory syndrome coronavirus 2; Software; Viral diseases; Web Browser; SARS-CoV-2; transmission; evolution; coronavirus GenBrowser; genomic epidemiology

Abstract Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic...