多细胞生物
表型
生物
细胞
单细胞分析
计算生物学
细胞生物学
电池类型
功能(生物学)
质量细胞仪
细胞功能
活体细胞成像
生物系统
遗传学
系统生物学
单细胞测序
计算机科学
细胞培养
基因
作者
Mojca Mattiazzi Ušaj,Clarence Hue Lok Yeung,Helena Friesen,Charles Boone,Brenda Andrews
出处
期刊:Cell systems
[Elsevier]
日期:2021-06-01
卷期号:12 (6): 608-621
被引量:13
标识
DOI:10.1016/j.cels.2021.05.010
摘要
Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.
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