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相关概念视频

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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Point and Frameshift Mutations01:30

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Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
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Mutation, Gene Flow, and Genetic Drift01:09

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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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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Vaccinia Virus Infection & Temporal Analysis of Virus Gene Expression: Part 1
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使用基于长期短期记忆的时间序列模型进行麻基因组突变分析.

Refat Khan Pathan1, Mohammad Amaz Uddin2, Ananda Mohan Paul3

  • 1Department of Computing and Information Systems, School of Engineering and Technology, Sunway University, Selangor, Malaysia.

PloS one
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概括
此摘要是机器生成的。

根据一项分析NCBI数据的新研究,病毒基因突变率正在下降. 这项研究利用深度学习模型来预测未来的麻疹突变.

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科学领域:

  • 病毒学 病毒学
  • 遗传学 遗传学 是一个
  • 计算生物学 计算生物学

背景情况:

  • 麻疹是一种双链DNA病毒,属于Orthopoxvirus属和Poxviridae家族.
  • 人与人之间的传播是通过与呼吸道分泌物,受感染的个人/动物或受污染的物体直接接触而发生的.
  • 世界卫生组织在2022年7月宣布公共卫生紧急情况,原因是麻疹病例普遍蔓延.

研究的目的:

  • 通过使用最新的NCBI数据集,分析病毒的基因突变率.
  • 为了独立识别核酸和密码子突变.
  • 为了预测麻疹病毒的未来突变率.

主要方法:

  • 从NCBI.BI收集并准备的水基因数据.
  • 基于地理数据 (加拿大,德国,世界其他地区) 的分类突变率.
  • 采用深度学习模型,特别是长短期记忆 (LSTM) 和门式循环单元 (GRU),用于基因组突变率的预测.

主要成果:

  • 长期短期记忆 (LSTM) 模型实现了0.09的根平均平方误差 (RMSE) 值,用于测试和0.08用于训练.
  • 观察到核酸突变率正在下降.
  • 保持了双向突变率之间的平衡.

结论:

  • 深度学习模型,特别是LSTM,可以有效地预测麻疹基因组突变率.
  • 这项研究为病毒病毒的进化和突变趋势提供了新的见解.
  • 观察到的核酸突变率下降表明病毒进化的潜在稳定或转变.