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相关概念视频

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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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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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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Reporter Genes02:11

Reporter Genes

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Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
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相关实验视频

Updated: Jun 5, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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细胞特异性先验在基于空间点的技术中拯救差异性基因表达.

Ornit Nahman1, Timothy J Few-Cooper1, Shai S Shen-Orr1

  • 1Department of Immunology, Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, 1 Efron St., Haifa, 3525433, Israel.

Briefings in bioinformatics
|December 16, 2024
PubMed
概括

使用标准基因表达算法进行空间转录学 (ST) 分析,努力识别真正的差异表达基因 (DEG). 斑点内的细胞异质性导致性能差,但细胞类型特定的基因选择方法可以提高准确性.

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.
  • 分子生物学分子生物学

背景情况:

  • 空间转录组学 (ST) 能够在组织环境中进行基因表达分析.
  • 像Visium这样的基于现场的ST平台被广泛采用.
  • 目前的ST数据分析通常依赖于为单细胞 (SC) 和散装RNA-seq.开发的算法.

研究的目的:

  • 在ST数据上评估传统差异表达基因 (DEG) 算法的性能.
  • 为了确定在ST分析中DEG检测不佳的原因.
  • 开发一种改进的方法来识别ST数据中的DEG.

主要方法:

  • 构建一个in silico空间转录学数据模拟器,具有已知的DEG基础真实性.
  • 在模拟的ST数据上对经典DEG算法的性能评估.
  • 基于细胞类型特异性的基因选择方案的开发和测试.

主要成果:

  • 经典的DEG算法在识别ST数据中的已知DEG时的准确性有限.
  • 在ST点内的细胞异质性是限制DEG检测性能的主要因素.
  • 提出的细胞类型特定基因选择方案显著改善了DEG的恢复和可靠性.
关键词:
拆解和解体的过程中,不同表达的基因.基因特异性 基因特异性空间转录学 空间转录学

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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

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Radioactive in situ Hybridization for Detecting Diverse Gene Expression Patterns in Tissue

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相关实验视频

Last Updated: Jun 5, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

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Radioactive in situ Hybridization for Detecting Diverse Gene Expression Patterns in Tissue
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Radioactive in situ Hybridization for Detecting Diverse Gene Expression Patterns in Tissue

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结论:

  • 现有的DEG算法对于空间转录学数据分析来说并不理想.
  • 细胞异质性需要专门的方法来准确识别ST中的DEG.
  • 一种新的基因选择策略提高了空间转录学研究的可靠性和准确性.