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Cell Specific Gene Expression

Cell Specific Gene Expression

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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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Updated: Jul 8, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

在单细胞分辨率上重建空间转录组学,使用贝叶斯深度.

Xi Jiang^1,2, Lei Dong¹, Shidan Wang¹

¹Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, The University of Texas Southwestern Medical Center, Dallas, Texas, U.S.A.

bioRxiv : the preprint server for biology

|December 18, 2023

概括

此摘要是机器生成的。

BayesDeep使用组织学图像重建了单细胞分辨率空间分辨的转录组学 (SRT) 数据. 这种新的贝叶斯模型在组织环境中增强了生物学见解和下游分析.

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.

关键词:

贝叶斯的等级模型是贝叶斯的等级模型.细胞形态特征细胞形态特征单细胞分辨率的解决方案空间分辨的转录学.

更多相关视频

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

Published on: November 2, 2020

相关实验视频

Last Updated: Jul 8, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

An Approach to Study Shape-Dependent Transcriptomics at a Single Cell Level

Published on: November 2, 2020

背景情况:

空间解析转录学 (SRT) 技术提供了具有空间背景的分子分析.
目前的SRT方法通常捕获有限的空间域,在许多细胞中平均基因表达.
对于单细胞分辨率的SRT数据来理解组织生物学是非常需要的.

结论:

贝叶斯深度使组织内的高分辨率分子映射成为可能.
重建的SRT数据提供了更深入的生物学见解.
这种方法提升了SRT在理解复杂生物系统中的实用性.