CoV-Seq, a New Tool for SARS-CoV-2 Genome Analysis and Visualization: Development and Usability Study.

Liu, Boxiang; Liu, Kaibo; Zhang, He; Zhang, Liang; Bian, Yuchen; Huang, Liang

Liu, Boxiang; Liu, Kaibo; Zhang, He; Zhang, Liang; Bian, Yuchen; Huang, Liang.

Affiliation

Liu B; Baidu Research, Sunnyvale, CA, United States.
Liu K; Baidu Research, Sunnyvale, CA, United States.
Zhang H; Baidu Research, Sunnyvale, CA, United States.
Zhang L; Baidu Research, Sunnyvale, CA, United States.
Bian Y; School of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR, United States.
Huang L; Baidu Research, Sunnyvale, CA, United States.

J Med Internet Res ; 22(10): e22299, 2020 10 02.

Article in En | MEDLINE | ID: mdl-32931441

Subject(s)

Betacoronavirus/genetics; Coronavirus Infections/virology; Data Visualization; Databases, Genetic; Genome, Viral/genetics; Pneumonia, Viral/virology; Software; COVID-19; Computational Biology; Coronavirus Infections/epidemiology; Humans; Pandemics; Pneumonia, Viral/epidemiology; SARS-CoV-2

Key words

COVID-19; SARS-CoV-2; bioinformatics; data sets; genetics; genome; programming; sequence; virus; web server

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Full text: 1 Database: MEDLINE Main subject: Pneumonia, Viral / Software / Genome, Viral / Coronavirus Infections / Databases, Genetic / Betacoronavirus / Data Visualization Limits: Humans Language: En Year: 2020 Type: Article

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