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相关概念视频

RNA-seq03:21

RNA-seq

9.9K
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...
9.9K
Ribosome Profiling02:24

Ribosome Profiling

3.5K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.5K

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相关实验视频

Updated: Jun 23, 2025

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

10.4K

RNA-Seq 数据分析 数据分析

James Li1, Rency S Varghese1, Habtom W Ressom2

  • 1Genomics & Epigenomics Shared Resource, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA.

Methods in molecular biology (Clifton, N.J.)
|June 22, 2024
PubMed
概括
此摘要是机器生成的。

本章详细介绍了一个全面的RNA测序 (RNA-Seq) 数据分析管道,涵盖质量控制,预处理,对齐,微分表达和功能分析. 它还引入了先进的机器学习应用程序,以从基因组学数据中获得更深入的生物学见解.

关键词:
不同表达式的差异表达式这是下一代测序.序列对齐方式 序列对齐方式文字转录学 (Transcriptomics) 是一个学科.

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Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs
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Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Published on: September 16, 2019

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Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms
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Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms

Published on: February 2, 2024

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相关实验视频

Last Updated: Jun 23, 2025

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

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Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs
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Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

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Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms
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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:

  • RNA测序 (RNA-Seq) 对于现代基因组学研究至关重要.
  • 分析复杂的RNA-Seq数据需要一个结构化和全面的方法.
  • 快速的进步需要更新的分析方法.

研究的目的:

  • 为RNA-Seq数据分析提供详细的管道.
  • 涵盖从数据质量控制到先进机器学习应用的基本步骤.
  • 为研究人员使用RNA-Seq数据提供基础的理解.

主要方法:

  • 质量控制和原始序列数据的预处理.
  • 处理的序列与参考基因组对齐.
  • 不同基因表达分析和功能丰富 (例如,基因本体学,通路分析).
  • 机器学习技术的应用,包括维度缩小和监督/无监督学习.

主要成果:

  • 阐明了RNA-Seq数据分析的系统工作流.
  • 关键步骤确保数据完整性和准确的映射.
  • 实现了差异表达基因及其生物背景的识别.
  • 机器学习揭示了RNA-Seq数据中的复杂模式.

结论:

  • 描述的管道为RNA-Seq数据解释提供了一个强大的框架.
  • 整合机器学习可以提高RNA-Seq分析的发现潜力.
  • 对这些方法的彻底理解对于推进基因组学研究至关重要.