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相关概念视频

Next-generation Sequencing03:00

Next-generation Sequencing

92.6K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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DNA-only Transposons02:57

DNA-only Transposons

14.8K
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...
14.8K
DNA as a Genetic Template02:05

DNA as a Genetic Template

22.7K
Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...
22.7K
Overview of Transposition and Recombination02:13

Overview of Transposition and Recombination

16.1K
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...
16.1K
Translesion DNA Polymerases02:10

Translesion DNA Polymerases

10.1K
Translesion (TLS) polymerases rescue stalled DNA polymerases at sites of damaged bases by replacing the replicative polymerase and installing a nucleotide across the damaged site. Doing so, TLS allows additional time for the cell to repair the damage before resuming regular DNA replication.
TLS polymerases are found in all three domains of life - archaea, bacteria, and eukaryotes. Of the different classes of TLS polymerases, members of the Y family are fitted with specialized structures that...
10.1K
RNA-seq03:21

RNA-seq

10.4K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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相关实验视频

Updated: Sep 10, 2025

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

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转基因:在基因数据存储中进行序列重建的深度转移学习网络

Yun Qin, Fei Zhu, Bo Xi

    IEEE transactions on computational biology and bioinformatics
    |August 26, 2025
    PubMed
    概括

    这项研究介绍了TransDNA,一个新的深度传输学习网络,通过提高序列重建精度来改善DNA数据恢复. 在DNA存储系统中,TransDNA有效地克服了有限的训练数据挑战.

    科学领域:

    • 生物技术
    • 计算机科学
    • 数据存储

    背景情况:

    • DNA数据存储提供了高密度和耐用性,但由于错误,在准确的信息恢复方面面临挑战.
    • 序列重建对于解码DNA数据至关重要,但有限的训练样本阻碍了深度学习方法.

    研究的目的:

    • 开发一种有效的深度学习方法来重建DNA序列,克服稀缺的训练数据的限制.
    • 推出一个深度转移学习网络TransDNA,旨在提高DNA数据恢复的准确性和效率.

    主要方法:

    • 提出了TransDNA,一个包含编码器,域特定解码器和域不变特征提取器的深度转移学习网络.
    • 采用交替域调整和特定域的重建机制.
    • 使用来自较大的源数据集的知识传输来提高来自真实DNA存储实验的较小目标数据集的性能.

    主要成果:

    • 在真实DNA存储数据集上,TransDNA显著提高了序列重建成功率.
    • 拟议的方法在没有转移学习和其他比较方法的基础模型中表现出色.
    • 与SDG方法相比,TransDNA在重建成功率和训练效率方面表现优越.

    结论:

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  • 转基因是将转移学习应用到DNA序列重建任务中的第一个成功应用.
  • 开发的方法有效地解决了DNA存储系统中有限的训练数据的挑战.
  • 在DNA数据存储中提高信息恢复可靠性的TransDNA提供了一个有前途的解决方案.