Evidence map›Paper›PMID 35043153›Full record

ArticleBriefings in bioinformatics2022

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

Dalang Yu, Xiao Yang, Bixia Tang, Yi-Hsuan Pan, Jianing Yang, Guangya Duan, Junwei Zhu, Zi-Qian Hao, Hailong Mu, Long Dai and 11 more

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.5field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 24 citations in OpenAlex.

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  10. BCEDB: a linear B-cell epitopes database for SARS-CoV-2.Database : the journal of biological databases and curation · 2023
    Article
  11. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors at 4 institutions in 1 country.

Dalang YuNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Xiao YangNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Bixia TangNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Yi-Hsuan PanKey Laboratory of Brain Functional Genomics of Ministry of Education, School of Life Science, East China Normal University, Shanghai 200062, China.
Jianing YangNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Guangya DuanNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Junwei ZhuNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Zi-Qian HaoNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Hailong MuNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Long DaiNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Wangjie HuNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Mochen ZhangNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Ying CuiNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Tong JinNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Cui-Ping LiNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Lina MaNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Language translation team
Xiao SuInstitut Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai 200031, China.
Guoqing ZhangNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.
Wenming ZhaoNational Genomics Data Center, Beijing Institute of Genomics (China National Center for Bioinformation), Chinese Academy of Sciences, Beijing 100101, China.
Haipeng LiNational Genomics Data Center, Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China.ORCID 0000-0001-7856-4488
Beijing Institute of Genomics · CNShanghai Institute of Nutrition and Health · CNChinese Academy of Sciences · CNEast China Normal University · CN

Funding

Chinese Academy of Sciences XDB38030100National Key Research and Development Project of China 2020YFC084-7000Shanghai Institute of Nutrition and Health JBGSRWBD-SINH-2021-10Shanghai Municipal Science and Technology Major Project 2017SHZDZX01
6 · The paper itself

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 challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

Indexed as

SoftwareWeb BrowserComputational BiologyCOVID-19Databases, GeneticDNA Mutational AnalysisGenome, ViralGenomicsHumansMolecular EpidemiologyMolecular Sequence AnnotationMutationPublic Health SurveillanceSARS-CoV-2coronavirus GenBrowserevolutiongenomic epidemiologySARS-CoV-2transmission

Identifiers

PMID35043153
PMCPMC8921643
OpenAlexW4206394908

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.