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相关概念视频

RNA-seq03:21

RNA-seq

9.8K
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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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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Sanger Sequencing01:57

Sanger Sequencing

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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: May 28, 2025

Competitive Genomic Screens of Barcoded Yeast Libraries
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Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

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寡核酸子集选择单核酸分辨率条形码识别标识

Woojin Kim1, Mingweon Chon2, Yoonhae Koh1

  • 1School of Materials Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.

Nature communications
|February 12, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的方法来选择没有原始体的DNA子集,使得基因组学和数据存储应用程序的可扩展和具有成本效益的oligo库管理成为可能.

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
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Competitive Genomic Screens of Barcoded Yeast Libraries

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
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Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella
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科学领域:

  • 分子生物学分子生物学
  • 基因组学就是基因组学.
  • 合成生物学 合成生物学
  • DNA 数据存储 DNA 数据存储

背景情况:

  • 从复杂的寡核酸库中选择子集对于各种科学领域至关重要.
  • 目前使用聚合酶连锁反应 (PCR) 的方法受到原料设计和长度的限制,阻碍了可扩展性和增加成本.

研究的目的:

  • 开发一种可扩展和具有成本效益的方法来从复杂的寡核酸库中选择子集.
  • 克服在寡核酸库应用中依赖于原料的选择方法的局限性.

主要方法:

  • 一种新的奥利戈子集选择技术,采用序列特异性循环核酸合成和模板奥利戈阻断.
  • 在选择性杂交过程中消除了对原料的需求.

主要成果:

  • 能够用短条码 (少于5个核酸) 来编码和选择数百个子集.
  • 在oligo库中促进层次数据结构,提高可编程性.
  • 为管理复杂的oligo库提供了一个可扩展和成本效益的解决方案.

结论:

  • 开发的方法为处理复杂的oligo库提供了显著的进步.
  • 这种方法提高了效率,并降低了基因组学,合成生物学和DNA数据存储中的子集选择的成本.