Skip to main content
Advertisement

PLOS One

  • Publish
    • Submissions
      • Getting Started
      • Submission Guidelines
      • Figures
      • Tables
      • Supporting Information
      • LaTeX
      • What We Publish
      • Preprints
      • Revising Your Manuscript
      • Submit Now
      • Calls for Papers
    • Policies
      • Best Practices in Research Reporting
      • Human Subjects Research
      • Animal Research
      • Competing Interests
      • Disclosure of Funding Sources
      • Licenses and Copyright
      • Data Availability
      • Complementary Research
      • Materials, Software and Code Sharing
      • Ethical Publishing Practice
      • Authorship
      • Corrections, Expressions of Concern, and Retractions
    • Manuscript Review and Publication
      • Criteria for Publication
      • Editorial and Peer Review Process
      • Editor Center
      • Resources for Editors
      • Guidelines for Reviewers
      • Accepted Manuscripts
      • Comments

    Submit Your Manuscript

    Discover a faster, simpler path to publishing in a high-quality journal. PLOS ONE promises fair, rigorous peer review, broad scope, and wide readership – a perfect fit for your research every time.

    Learn More Submit Now

  • About
    • Why Publish with PLOS ONE
    • Journal Information
    • Staff Editors
    • Editorial Board
    • Section Editors
    • Advisory Groups
    • Find and Read Articles
    • Publishing Information
    • Publication Fees
    • Press and Media
    • Contact
  • Browse
  • Search
    advanced search
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study

  • Gurjit S. Randhawa ,

    Contributed equally to this work with: Gurjit S. Randhawa, Maximillian P. M. Soltysiak

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    * E-mail: grandha8@uwo.ca

    Affiliation Department of Computer Science, The University of Western Ontario, London, ON, Canada

    ORCID logo http://orcid.org/0000-0003-1054-125X

    ⨯
  • Maximillian P. M. Soltysiak ,

    Contributed equally to this work with: Gurjit S. Randhawa, Maximillian P. M. Soltysiak

    Roles Formal analysis, Investigation, Writing – original draft, Writing – review & editing

    Affiliation Department of Biology, The University of Western Ontario, London, ON, Canada

    ORCID logo http://orcid.org/0000-0001-7495-5203

    ⨯
  • Hadi El Roz,

    Roles Formal analysis, Writing – review & editing

    Affiliation Department of Biology, The University of Western Ontario, London, ON, Canada

    ORCID logo http://orcid.org/0000-0002-4020-701X

    ⨯
  • Camila P. E. de Souza,

    Roles Formal analysis, Writing – review & editing

    Affiliation Department of Statistical and Actuarial Sciences, The University of Western Ontario, London, ON, Canada

    ⨯
  • Kathleen A. Hill,

    Roles Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Writing – review & editing

    Affiliation Department of Biology, The University of Western Ontario, London, ON, Canada

    ⨯
  • Lila Kari

    Roles Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing

    Affiliation School of Computer Science, University of Waterloo, Waterloo, ON, Canada

    ⨯

Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study

  • Gurjit S. Randhawa, 
  • Maximillian P. M. Soltysiak, 
  • Hadi El Roz, 
  • Camila P. E. de Souza, 
  • Kathleen A. Hill, 
  • Lila Kari
PLOS
x
  • Published: April 24, 2020
  • https://doi.org/10.1371/journal.pone.0232391
  • Article
  • Authors
  • Metrics
  • Comments
  • Media Coverage
Download PDF
 
  • Citation
  • XML
Print
Share
  • RedditReddit
  • FacebookFacebook
  • LinkedInLinkedIn
  • MendeleyMendeley
  • BlueskyBluesky
  • EmailEmail
  Check for updates via CrossMark

Related PLOS Articles

  • has CORRECTION
  • Correction: Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study
    • View Page
    • PDF
Advertisement

Subject Areas
?

For more information about PLOS Subject Areas, click here.

We want your feedback. Do these Subject Areas make sense for this article? Click the target next to the incorrect Subject Area and let us know. Thanks for your help!

  • COVID 19  

    Is the Subject Area "COVID 19" applicable to this article?

    Thanks for your feedback.

  • Viral genomics  

    Is the Subject Area "Viral genomics" applicable to this article?

    Thanks for your feedback.

  • Sequence alignment  

    Is the Subject Area "Sequence alignment" applicable to this article?

    Thanks for your feedback.

  • Virus testing  

    Is the Subject Area "Virus testing" applicable to this article?

    Thanks for your feedback.

  • Coronaviruses  

    Is the Subject Area "Coronaviruses" applicable to this article?

    Thanks for your feedback.

  • Viral taxonomy  

    Is the Subject Area "Viral taxonomy" applicable to this article?

    Thanks for your feedback.

  • Genomics  

    Is the Subject Area "Genomics" applicable to this article?

    Thanks for your feedback.

  • Taxonomy  

    Is the Subject Area "Taxonomy" applicable to this article?

    Thanks for your feedback.

  • Publications
  • PLOS Biology
  • PLOS Climate
  • PLOS Complex Systems
  • PLOS Computational Biology
  • PLOS Digital Health
  • PLOS Genetics
  • PLOS Global Public Health
  •  
  • PLOS Medicine
  • PLOS Mental Health
  • PLOS Neglected Tropical Diseases
  • PLOS One
  • PLOS Pathogens
  • PLOS Sustainability and Transformation
  • PLOS Water
  • Home
  • Blogs
  • Collections
  • Give feedback
  • LOCKSS
  • Privacy Policy
  • Terms of Use
  • Advertise
  • Media Inquiries
  • Contact

PLOS PLOS is a nonprofit 501(c)(3) corporation, #C2354500, based in California, US