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相关概念视频

DNA-only Transposons02:57

DNA-only Transposons

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DNA-only transposons are called autonomous transposons since they code for the enzyme transposase that is required for the transposition mechanism. Insertion of transposons can alter gene functions in multiple ways. They can mutate the gene, alter gene expression by introducing a novel promoter or insulator sequence, introduce new splice sites, and change the mRNA transcripts produced, or remodel chromatin structure.
The donor site from where the transposon is excised is either degraded or...
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Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

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Transposons make up a significant part of genomes of various organisms. Therefore, it is believed that transposition played a major evolutionary role in speciation by changing genome sizes and modifying gene expression patterns. For example, in bacteria, transposition can lead to conferring antibiotic resistance. Movement of transposable elements within the genetic pool of pathogenic bacteria can aid in transfer of antibiotic-resistant genetic elements. In eukaryotes, transposons can carry out...
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Transposons01:24

Transposons

52
Transposons, or "jumping genes," are small mobile genetic elements (MGEs) that range from 700 to 40,000 base pairs in length. They are found in all organisms and can move within the same chromosome or transfer to different chromosomes. In some cases, transposons can also jump between different host DNA molecules, such as plasmids or viruses, contributing to genetic variability.Barbara McClintock first discovered these mobile genetic elements in the 1940s while studying maize genetics, and she...
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Non-LTR Retrotransposons03:18

Non-LTR Retrotransposons

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As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...
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LTR Retrotransposons03:08

LTR Retrotransposons

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LTR retrotransposons are class I transposable elements with long terminal repeats flanking an internal coding region. These elements are less abundant in mammals compared to other class I transposable elements. About 8 percent of human genomic DNA comprises LTR retrotransposons. Some of the common examples of LTR retrotransposons are Ty elements in yeast and Copia elements in Drosophila.
The internal coding region of LTR retrotransposons and their mechanism of transposition closely resembles a...
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Horizontal Gene Transfer01:27

Horizontal Gene Transfer

36
Horizontal gene transfer (HGT) is a process where genetic material moves between organisms within the same generation, unlike vertical gene transfer, which occurs from parent to offspring. HGT plays a crucial role in microbial evolution, adaptation, and survival, particularly in shared environments like the human gut.Mobile genetic elements such as plasmids, prophages, integrons, insertion sequences, and transposons facilitate this process. HGT occurs through three primary mechanisms:...
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相关实验视频

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DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
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基因组对象检测:使用卷积神经网络进行可转移元素检测和分类的改进方法.

Simon Orozco-Arias1,2, Luis Humberto Lopez-Murillo1, Johan S Piña1

  • 1Department of Computer Science, Universidad Autónoma de Manizales, Manizales, Colombia.

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概括

一种新的深度学习方法YORO准确地检测和分类真核生物基因组中的可转移元素 (TE). 这种方法使用卷积神经网络来预测TE的位置,长度和类型,提高基因组分析的效率.

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科学领域:

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

背景情况:

  • 可转移元素 (TE) 分析对于理解真核生物基因组至关重要.
  • 目前的TE检测和分类方法复杂且耗时.
  • 机器学习 (ML) 已被应用于TE分类,但尚未广泛用于检测.

研究的目的:

  • 引入YORO,一种用于基因组序列中可转移元素的新型检测分类策略.
  • 适应计算机视觉卷积神经网络 (YOLO) 用于基因组物体检测.
  • 为了能够预测基因组对象的位置,长度和在大型DNA序列中的分类.

主要方法:

  • 开发了YORO,这是一种基于从计算机视觉中调整的卷积神经网络的策略.
  • 使用LTR-逆转移子的内部蛋白质编码域训练神经网络.
  • 使用精度,回忆,准确性,F1分数和执行时间等指标评估性能.

主要成果:

  • YORO成功地检测和分类了基因组对象,特别是LTR-逆转移子.
  • 该方法在准确性和效率方面表现出很高的性能.
  • 执行时间和时间比率表明与现有方法相比有了显著的改进.

结论:

  • 对于下一代基因组分析工具来说,YORO是一个有前途的深度学习方法.
  • 该策略能够有效地检测和分类大型DNA序列中的可转移元素.
  • 这项工作有助于对真核生物基因组进行更全面,更快速的分析.