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Related Concept Videos

Viral Mutations00:36

Viral Mutations

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

Updated: Aug 9, 2025

Author Spotlight: A Pseudotype Virus System for Assessing Omicron Subvariants and Neutralizing Antibodies in SARS-CoV-2 Research
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Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

Lue Ping Zhao1, Seth Cohen2,3, Michael Zhao4

  • 1Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.

JAMA Network Open
|February 22, 2023
PubMed
Summary
This summary is machine-generated.

An artificial intelligence model accurately identified novel SARS-CoV-2 variants, including mixture variants and those with new mutations, aiding public health surveillance and prevention strategies.

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Area of Science:

  • Genomics
  • Virology
  • Artificial Intelligence
  • Public Health

Background:

  • Early detection of novel SARS-CoV-2 variants is crucial for public health surveillance and prevention research.
  • Artificial intelligence (AI) offers a potential method for early variant detection using mutation haplotypes.

Purpose of the Study:

  • To develop a haplotype-based artificial intelligence (HAI) model for identifying novel SARS-CoV-2 variants.
  • The model aims to detect mixture variants (MVs) and variants with new mutations.

Main Methods:

  • A cross-sectional study utilized over 5 million global viral genomic sequences for training and validation.
  • Statistical learning analysis identified variant-specific mutations and haplotype frequencies to construct the HAI model.
  • The model was validated on an independent set and tested on a prospective set of over 344,000 viruses.

Main Results:

  • The HAI model achieved 92.8% accuracy in identifying novel SARS-CoV-2 variants.
  • It identified 4 Omicron MVs, 2 Delta MVs, and 1 Alpha-Epsilon MV, with Omicron-Epsilon MVs being the most frequent.
  • The model detected 1699 Omicron viruses with unidentifiable variants due to novel mutations and identified 16 novel mutations in 524 variant-unassigned viruses.

Conclusions:

  • The HAI model successfully identified SARS-CoV-2 viruses with mixture variants or novel mutations globally.
  • These findings suggest HAI can complement traditional phylogenetic methods for variant assignment.
  • The study highlights the potential of AI in enhancing public health surveillance of emerging viral threats.