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相关概念视频

RNA-seq03:21

RNA-seq

10.1K
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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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Ribosome Profiling02:24

Ribosome Profiling

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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...
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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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相关实验视频

Updated: Jul 26, 2025

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Published on: February 25, 2017

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一个组成模型来评估从单细胞RNA-SEQ数据中表达的变化.

Xiuyu Ma1, Keegan Korthauer2, Christina Kendziorski3

  • 1Department of Statistics, University of Wisconsin-Madison.

The annals of applied statistics
|June 19, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种经验贝叶斯混合模型,以检测单细胞基因表达分布的变化. 这种新的方法通过整合细胞亚型信息来提高灵敏度,以获得更准确的基因评分.

关键词:
当地的虚假发现率.聚类集群是指聚类的聚类.双迪里克莱混合物 双迪里克莱混合物经验上的贝叶斯贝叶斯.混合物模型模型的混合物模型

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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相关实验视频

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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科学领域:

  • 计算生物学 计算生物学
  • 基因组学就是基因组学.
  • 生物统计学 生物统计学

背景情况:

  • 在单细胞数据中准确地评分基因表达变化是具有挑战性的.
  • 现有的方法可能无法充分利用细胞亚型异质性.
  • 检测基因表达分布中的微妙变化需要强大的统计方法.

研究的目的:

  • 开发和评估一种新的经验贝叶斯混合方法,用于评分基因表达变化.
  • 通过结合细胞亚型信息来增强差异性基因表达分布的检测.
  • 为了提高识别基因与改变表达模式跨细胞条件的敏感性.

主要方法:

  • 开发了一个经验性的贝叶斯混合模型.
  • 来自集群分析的细胞亚型结构被利用.
  • 在多项概率向量上构建了一个先前分布.
  • 来自基因分布变化的后期概率.

主要成果:

  • 提出的方法在数值实验中显示出更好的灵敏度.
  • 细胞聚类的整合增强了基因表达变化的基因水平信息.
  • 该模型允许基因特异性混合物超过亚型.
  • 在细胞聚类和基因评分之间实现了新的信息共享.

结论:

  • 经验贝叶斯混合方法为检测差异性基因表达分布提供了一种敏感的方法.
  • 利用细胞亚型结构显著提高了基因水平分析的力量.
  • 这种方法为分析单细胞表达数据提供了一个强大的框架.