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- W3211208650 abstract "Stochastic outcomes of viral infections are attributed in large part to multiple layers of intrinsic and extrinsic heterogeneity that exist within a population of cells and viruses. Traditional methods in virology often lack the ability to demonstrate cell-to-cell variability in response to the invasion of viruses, and to decipher the sources of heterogeneities that are reflected in the variable infection dynamics. To overcome this challenge, the field of single-cell virology emerged less than a decade ago, enabling researchers to reveal the behavior of single, isolated, infected cells that has been masked in population-based assays. The use of microfluidics in single-cell virology, in particular, has resulted in the development of high-throughput devices that are capable of capturing, isolating, and monitoring single infected cells over the duration of an infection. Results from the studies of viral infection dynamics presented in this chapter indicate how single-cell data provide a more accurate prediction of the start time, replication rate, duration, and yield of infection when compared to population-based data. Additionally, single-cell analysis reveals striking differences between genetically distinct viruses that are almost indistinguishable in population methods. Importantly, both the efficacy and distinct mechanisms of action of antiviral compounds can be elucidated by using single-cell analysis." @default.
- W3211208650 created "2021-11-08" @default.
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- W3211208650 date "2021-01-01" @default.
- W3211208650 modified "2023-10-18" @default.
- W3211208650 title "Single-cell analysis for the study of viral inhibitors" @default.
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- W3211208650 doi "https://doi.org/10.1016/bs.enz.2021.07.004" @default.
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