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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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Viral Structure00:56

Viral Structure

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Viruses are extraordinarily diverse in shape and size, but they all have several structural features in common. All viruses have a core that contains a DNA- or RNA-based genome. The core is surrounded by a protective coat of proteins called the capsid. The capsid is composed of subunits called capsomeres. The capsid and genome-containing core are together known as the nucleocapsid.
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Viral Recombination00:57

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Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
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Evolutionary Relationships through Genome Comparisons02:54

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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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Classification of Leukocytes01:30

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Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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相关实验视频

Updated: Jun 4, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
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Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

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在规模上的无对齐病毒序列分类.

Daniel J van Zyl1,2, Marcel Dunaiski2, Houriiyah Tegally1

  • 1Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.

bioRxiv : the preprint server for biology
|December 23, 2024
PubMed
概括
此摘要是机器生成的。

无对齐方法为分类大型病毒数据集提供了快速而准确的解决方案,优于传统的基于对齐的方法. 这些技术有效地处理大量的序列数据,这对现代基因组学至关重要.

关键词:
没有对齐的自由对齐.生物序列的生物序列.功能提取 特性提取机器学习是机器学习.病毒分类病毒分类

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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 生物信息学是一种生物信息学.

背景情况:

  • 下一代测序 (NGS) 产生了大量的核酸数据,压倒了传统的基于对齐的测序比较工具,如BLAST.
  • 基于对齐的方法的计算需求限制了它们对大规模病毒数据集的分类的可扩展性.
  • 在大数据时代,对高效准确的病毒序列分类计算工具有极大需求.

研究的目的:

  • 评估无对齐 (AF) 方法作为病毒序列分类的可扩展和快速替代方案.
  • 在极大的病毒序列数据集上保持高精度和效率的AF技术.
  • 评估AF方法对分类各种病毒基因组的适用性,包括SARS-CoV-2,登革热和HIV.

主要方法:

  • 使用六种已建立的无对齐技术,从病毒基因组中提取特征向量.
  • 随机森林分类器被训练使用这些特征向量进行序列分类.
  • 模型在297,186个SARS-CoV-2序列的大量数据集上进行了训练和测试,跨越3502个谱系,并在登革热和艾滋病毒数据集上进行了验证.

主要成果:

  • 没有对齐的分类器实现了高精度:97.8%的SARS-CoV-2,99.8%的登革热和89.1%的HIV.
  • 基于word的无对齐方法有效地表示病毒序列,即使具有高维类结构.
  • 与基于对齐的方法相比,AF技术的处理时间明显更快.

结论:

  • 无对齐方法为病毒序列分类提供了可扩展和高效的解决方案.
  • 这些技术适用于使用适度的计算资源处理大规模的基因组数据集.
  • AF方法为快速病毒分类提供了实用优势,解决了传统方法的局限性.