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DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
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Using artificial intelligence techniques for COVID-19 genome analysis.

M Saqib Nawaz1, Philippe Fournier-Viger1, Abbas Shojaee2

  • 1School of Humanities and Social Sciences, Harbin Institute of Technology (Shenzhen), Shenzhen, China.

Applied Intelligence (Dordrecht, Netherlands)
|November 12, 2021
PubMed
Summary
This summary is machine-generated.

Artificial intelligence, including sequential pattern mining and mutation analysis, reveals hidden patterns and evolution in COVID-19 genome sequences. These AI techniques aid in understanding virus behavior and developing effective strategies against COVID-19.

Keywords:
COVID-19Genome sequenceMutationNucleotide basesSequential pattern mining

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Area of Science:

  • Genomics
  • Bioinformatics
  • Artificial Intelligence

Background:

  • The COVID-19 pandemic emerged in late 2019, with its genome sequenced in January 2020.
  • Understanding the COVID-19 genome is crucial for tracking its origin, mutation rate, and developing vaccines and treatments.

Purpose of the Study:

  • To investigate the application of artificial intelligence techniques for analyzing COVID-19 genome sequences.
  • To uncover hidden patterns and evolutionary insights within the viral genome.

Main Methods:

  • Sequential Pattern Mining (SPM) was applied to identify frequent nucleotide base patterns.
  • Sequence prediction models were used to forecast nucleotide bases.
  • A custom algorithm was developed for mutation analysis to detect base changes and calculate mutation rates.

Main Results:

  • SPM identified significant patterns in nucleotide sequences, offering insights into viral relationships.
  • Mutation analysis successfully located genomic variations and quantified mutation rates.
  • AI techniques demonstrated potential in analyzing viral evolution and strain variations.

Conclusions:

  • AI-driven methods, particularly SPM and mutation analysis, provide valuable tools for dissecting COVID-19 genome data.
  • These techniques can enhance our understanding of viral evolution, aiding in the development of public health strategies and medical countermeasures.