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相关概念视频

Next-generation Sequencing03:00

Next-generation Sequencing

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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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RNA-seq03:21

RNA-seq

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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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Maxam-Gilbert Sequencing01:05

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In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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相关实验视频

Updated: Jul 24, 2025

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome
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在资源有限的设备上进行高效的实时选择性基因组测序.

Po Jui Shih1, Hassaan Saadat2, Sri Parameswaran3

  • 1School of Computer Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

GigaScience
|July 3, 2023
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概括

硬件加速读取 (HARU) 能够在资源有限的设备上实现高效的纳米孔选择性测序. 这种方法显著加快了实时基因组分析的速度,使得快速遗传测试更容易获得和节能.

关键词:
在FPGA中,FPGA是指FPGA.适应性采样采样方式边缘计算是一种边缘计算.硬件加速加速器 硬件加速器这是一个纳米孔.选择性测序是一种选择性测序.随后的动态时间扭曲.

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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:

  • 第三代纳米孔测序器能够进行选择性测序 (Read Until) 以实时分析.
  • 这项技术对于快速,低成本的基因测试等应用至关重要.
  • 当前后续动态时间曲 (sDTW) 方法是计算密集的,阻碍便携式测序器的实时分析.

研究的目的:

  • 开发一种资源高效的方法来加速纳米孔选择性测序的sDTW算法.
  • 在便携式和资源有限的设备上实现实时基因组分析.

主要方法:

  • 引入了硬件加速读取 (HARU),一种硬件-软件代码设计方法.
  • 使用了一个异质的多处理器芯片上的系统 (SoC) 与芯片上的现场可编程网关阵列 (FPGA).
  • 加快sDTW算法进行实时读取分析.

主要成果:

  • 与36核服务器上的优化软件相比,HARU实现了2.5倍的速度,使用Xilinx FPGA与4核ARM处理器.
  • 与未经优化软件相比,显示了85倍的加快速度.
  • 与基于服务器的执行相比,能源消耗减少了两个数量级.

结论:

  • 在资源有限的设备上,HARU成功实现了纳米孔选择性测序.
  • 这种方法突出了硬件和软件优化的潜力,用于便携式基因组分析.
  • 哈鲁的开源代码可供进一步开发和应用.