转录组
背景(考古学)
空间语境意识
RNA序列
功能(生物学)
基因表达
维数(图论)
基因
表达式(计算机科学)
基因表达调控
计算机科学
生物
遗传学
计算生物学
人工智能
古生物学
数学
程序设计语言
纯数学
作者
Yingwen Chen,Weizhou Qian,Lin Liu,Linfeng Cai,Ke‐Jie Yin,Shaowei Jiang,Jia Song,Ray P. S. Han,Chaoyong Yang
标识
DOI:10.1002/smtd.202100722
摘要
Abstract The main function and biological processes of tissues are determined by the combination of gene expression and spatial organization of their cells. RNA sequencing technologies have primarily interrogated gene expression without preserving the native spatial context of cells. However, the emergence of various spatially‐resolved transcriptome analysis methods now makes it possible to map the gene expression to specific coordinates within tissues, enabling transcriptional heterogeneity between different regions, and for the localization of specific transcripts and novel spatial markers to be revealed. Hence, spatially‐resolved transcriptome analysis technologies have broad utility in research into human disease and developmental biology. Here, recent advances in spatially‐resolved transcriptome analysis methods are summarized, including experimental technologies and computational methods. Strengths, challenges, and potential applications of those methods are highlighted, and perspectives in this field are provided.
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