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《BioRxiv，3月14日，Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning》

  • 来源专题：COVID-19科研动态监测
  • 编译者： zhangmin
  • 发布时间：2020-03-15

  • Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning

    Alejandro Lopez-Rincon, Alberto Tonda, Lucero Mendoza-Maldonado, Eric Claassen, Johan Garssen, Aletta D. Kraneveld

    doi: https://doi.org/10.1101/2020.03.13.990242

    Abstract

    One of the reasons for the fast spread of SARS-CoV-2 is the lack of accuracy in detection tools in the clinical field. Molecular techniques, such as quantitative real-time RT-PCR and nucleic acid sequencing methods, are widely used to identify pathogens. For this particular virus, however, they have an overall unsatisfying detection rate, due to its relatively recent emergence and still not completely understood features. In addition, SARS-CoV-2 is remarkably similar to other Coronaviruses, and it can present with other respiratory infections, making identification even harder. To tackle this issue, we propose an assisted detection test, combining molecular testing with deep learning.

    *注，本文为预印本论文手稿，是未经同行评审的初步报告，其观点仅供科研同行交流，并不是结论性内容，请使用者谨慎使用.

  • 原文来源：https://www.biorxiv.org/content/10.1101/2020.03.13.990242v1
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