在单细胞分辨率上重建空间转录组学,使用贝叶斯深度
Xi Jiang1,2, 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
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.
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.
相关概念视频
01:58Cell Specific Gene Expression
4.7K
4.7K
03:21RNA-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...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.0K
02:07Improving Translational Accuracy
2.6K
2.6K