.png){kind=icon}
.png){kind=icon}
Return
Deciphering tissue structure and function using spatial transcriptomics
.png){kind=icon}
OA
AI
DOI：10.1038/s42003-022-03175-5.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and transcriptional information in analysis of ST datasets. The wide diversity of approaches in aim, methodology and technology for ST provides great challenges in dissecting cellular functions in spatial contexts. Here, we synthesize and review the key problems in analysis of ST data and methods that are currently applied, while also expanding on open questions and areas of future development. Walker et al. review methods used to analyse spatial transcriptomics data and discuss open questions and areas of future development.
Keywords:
GENOME-WIDE EXPRESSION
GENE-EXPRESSION
SEQ
IDENTIFICATION
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.1
Papers:
1.0W
Citations:
3.2W
