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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 18, 2025

Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms
05:12

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

Published on: February 2, 2024

719

scIDPMs:使用扩散概率模型进行单细胞RNA-Seq推算.

Zhiqiang Zhang, Lin Liu

    IEEE journal of biomedical and health informatics
    |August 2, 2024
    PubMed
    概括

    一种名为scIDPMs的新方法有效地将单细胞RNA测序 (scRNA-seq) 数据中的缺失基因表达值归因. 它克服了学事件,改善了研究人员的生物准确性和下游分析.

    科学领域:

    • 基因组学就是基因组学.
    • 计算生物学 计算生物学
    • 生物信息学是一种生物信息学.

    背景情况:

    • 单细胞RNA测序 (scRNA-seq) 提供了高分辨率的基因表达数据.
    • 在scRNA-seq数据中出现的脱落事件 (虚假零) 阻碍了准确的分析.
    • 现有的归算方法在scRNA-seq数据稀疏性和复杂性方面扎.

    研究的目的:

    • 开发一种新的计算方法,用于在scRNA-seq数据中赋值缺失的值.
    • 为了解决当前的归算技术在捕获掉落分布方面的局限性.
    • 提高基因表达特征和下游分析的准确性.

    主要方法:

    • 介绍了scIDPMs,一种使用条件扩散概率模型进行归算的新方法.
    • scIDPMs通过基因表达特征来识别脱落点并推断缺失的值.
    • 采用了具有注意力机制的深度神经网络来捕获全球基因表达特征.

    主要成果:

    • 与其他十种方法相比,scIDPMs在赋值scRNA-seq数据方面表现优异.
    • 该方法有效地恢复了生物学上有意义的基因表达值.
    • 使用模拟和现实世界scRNA-seq数据集进行评估.

    更多相关视频

    Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
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    Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

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    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.0K

    相关实验视频

    Last Updated: Jun 18, 2025

    Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms
    05:12

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

    Published on: February 2, 2024

    719
    Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
    10:10

    Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

    Published on: September 18, 2021

    37.1K
    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.0K

    结论:

    • scIDPMs在scRNA-seq数据归算方面提供了显著的进步.
    • 该方法提高了基因表达分析和生物见解的可靠性.
    • scIDPMs为解决单细胞基因组学中脱落事件提供了强大的解决方案.