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相关概念视频

RNA-seq03:21

RNA-seq

10.0K
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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Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
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相关实验视频

Updated: Jul 9, 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

Published on: July 6, 2022

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在单细胞分辨率下进行空间转录组学解卷使用Redeconve.

Zixiang Zhou1,2, Yunshan Zhong1, Zemin Zhang1,2

  • 1Changping Laboratory, Yard 28, Science Park Road, Changping District, Beijing, China.

Nature communications
|December 1, 2023
PubMed
概括
此摘要是机器生成的。

Redeconve是一个新的算法,它以单细胞分辨率解读空间转录组学数据,提供卓越的准确性和速度. 这一进步使我们能够更深入地了解复杂的生物系统和疾病机制.

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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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Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level
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Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

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相关实验视频

Last Updated: Jul 9, 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

Published on: July 6, 2022

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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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Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level
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Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level

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科学领域:

  • 基因组学就是基因组学.
  • 计算生物学 计算生物学
  • 免疫学 免疫学 免疫学

背景情况:

  • 空间转录学对于理解组织结构和细胞相互作用至关重要.
  • 目前的解卷方法缺乏单细胞分辨率,限制了详细分析.
  • 解释复杂的空间转录学数据需要先进的计算工具.

研究的目的:

  • 开发和介绍 Redeconve,一个用于空间转录学数据单细胞分辨率解卷的算法.
  • 为了使空间转录学数据能够解释数千种细微的细胞状态.
  • 为现有解卷方法提供一个优质的替代方案.

主要方法:

  • 开发了Redeconve,这是一个用于解构的新型计算算法.
  • 与使用各种空间转录组学平台和数据集的最先进算法进行基准重新定义.
  • 应用Redeconve对人类胰腺癌和淋巴结数据集.

主要成果:

  • 与现有方法相比,Redeconve表现出卓越的准确性,分辨率,稳定性和速度.
  • 在胰腺癌中识别了癌症克隆特异性T细胞透.
  • 在淋巴结中的IgA+和IgG+斑点之间揭示了差异性细胞毒性T细胞.

结论:

  • Redeconve显著提升了空间转录组学数据的解卷化到单细胞分辨率.
  • 该算法为瘤免疫学和抗体类切换机制提供了新的见解.
  • Redeconve 能够在空间背景下对细胞异质性的更细致的理解.