منابع مشابه
Genomic analysis at the single-cell level.
Studying complex biological systems such as a developing embryo, a tumor, or a microbial ecosystem often involves understanding the behavior and heterogeneity of the individual cells that constitute the system and their interactions. In this review, we discuss a variety of approaches to single-cell genomic analysis.
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Microbiologists traditionally study population rather than individual cells, as it is generally assumed that the status of individual cells will be similar to that observed in the population. However, the recent studies have shown that the individual behavior of each single cell could be quite different from that of the whole population, suggesting the importance of extending traditional microb...
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The heterogeneity of microorganisms themselves is orders of magnitude greater than the heterogeneity of perspectives from which they are contemplated by human observers. Even closely related species may exhibit marked differences in biochemistry and behavior, and, under many conditions, similar, striking heterogeneity may exist within a clonal population of organisms which, in the aggregate, oc...
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One of the most rapidly advancing areas in genomics in recent years has been the explosion of platforms to assess properties at the single-cell level. The driving force behind these advancements has been a renaissance of sorts in how we think about the architecture and heterogeneity present in a population of cells (1, 2). While these concepts are not new, the advancement of technologies to ass...
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The timing of a cellular event often hides critical information on the process leading to the event. Our ability to measure event times in single cells along with other quantities allow us to learn about the drivers of the timed process and its downstream effects. In this review, we cover different types of events that have been timed in single cells, methods to time such events and types of an...
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ژورنال
عنوان ژورنال: Annual Review of Genetics
سال: 2011
ISSN: 0066-4197,1545-2948
DOI: 10.1146/annurev-genet-102209-163607