蛋白质组学
计算生物学
代谢组学
基因组学
组学
系统生物学
生物
转录组
单细胞分析
细胞
计算机科学
基因组
生物信息学
基因
遗传学
基因表达
作者
Daojing Wang,Steven Bodovitz
标识
DOI:10.1016/j.tibtech.2010.03.002
摘要
Cellular heterogeneity that arises from stochastic expression of genes, proteins and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capability of ‘omics’ technology. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in omics, and single cell omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity. Cellular heterogeneity that arises from stochastic expression of genes, proteins and metabolites is a fundamental principle of cell biology, but single cell analysis has been beyond the capability of ‘omics’ technology. This is rapidly changing with the recent examples of single cell genomics, transcriptomics, proteomics and metabolomics. The rate of change is expected to accelerate owing to emerging technologies that range from micro/nanofluidics to microfabricated interfaces for mass spectrometry to third- and fourth-generation automated DNA sequencers. As described in this review, single cell analysis is the new frontier in omics, and single cell omics has the potential to transform systems biology through new discoveries derived from cellular heterogeneity.
科研通智能强力驱动
Strongly Powered by AbleSci AI