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Identification of Novel Viruses Using VirusHunter -- an Automated Data Analysis Pipeline

Overview of attention for article published in PLOS ONE, October 2013
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Title
Identification of Novel Viruses Using VirusHunter -- an Automated Data Analysis Pipeline
Published in
PLOS ONE, October 2013
DOI 10.1371/journal.pone.0078470
Pubmed ID
Authors

Guoyan Zhao, Siddharth Krishnamurthy, Zhengqiu Cai, Vsevolod L. Popov, Amelia P. Travassos da Rosa, Hilda Guzman, Song Cao, Herbert W. Virgin, Robert B. Tesh, David Wang

Abstract

Quick and accurate identification of microbial pathogens is essential for both diagnosis and response to emerging infectious diseases. The advent of next-generation sequencing technology offers an unprecedented platform for rapid sequencing-based identification of novel viruses. We have developed a customized bioinformatics data analysis pipeline, VirusHunter, for the analysis of Roche/454 and other long read Next generation sequencing platform data. To illustrate the utility of VirusHunter, we performed Roche/454 GS FLX titanium sequencing on two unclassified virus isolates from the World Reference Center for Emerging Viruses and Arboviruses (WRCEVA). VirusHunter identified sequences derived from a novel bunyavirus and a novel reovirus in the two samples respectively. Further sequence analysis demonstrated that the viruses were novel members of the Phlebovirus and Orbivirus genera. Both Phlebovirus and Orbivirus genera include many economic important viruses or serious human pathogens.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
United Kingdom 1 <1%
Netherlands 1 <1%
Germany 1 <1%
Unknown 109 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 21%
Student > Ph. D. Student 24 21%
Student > Master 20 17%
Other 9 8%
Student > Bachelor 9 8%
Other 16 14%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 45%
Biochemistry, Genetics and Molecular Biology 13 11%
Medicine and Dentistry 8 7%
Immunology and Microbiology 7 6%
Computer Science 6 5%
Other 11 9%
Unknown 19 16%