生物
计算生物学
背景(考古学)
多细胞生物
基因组学
蛋白质组学
数据科学
代谢组学
转录组
生物信息学
基因组
计算机科学
遗传学
基因
基因表达
古生物学
作者
Nicola Crosetto,Magda Bienko,Alexander van Oudenaarden
摘要
Considerable progress in sequencing technologies makes it now possible to study the genomic and transcriptomic landscape of single cells. However, to better understand the complexity of multicellular organisms, we must devise ways to perform high-throughput measurements while preserving spatial information about the tissue context or subcellular localization of analysed nucleic acids. In this Innovation article, we summarize pioneering technologies that enable spatially resolved transcriptomics and discuss how these methods have the potential to extend beyond transcriptomics to encompass spatially resolved genomics, proteomics and possibly other omic disciplines.
科研通智能强力驱动
Strongly Powered by AbleSci AI