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- W3014952014 abstract "High-dimensional, single-cell cell technologies revolutionized the way to study biological systems, and polychromatic flow cytometry (FC) and mass cytometry (MC) are two of the drivers of this revolution. As up to 30–50 dimensions respectively can be measured per single-cell, they allow deep phenotyping combined with cellular functions studies, like cytokine production or protein phosphorylation. In parallel, the bioinformatics field develops algorithms that are able to process incoming data and extract the most useful and meaningful biological information. However, the success of automated analysis tools depends on the generation of high-quality data. In this review we present the most recent FC and MC computational approaches that are used to prepare, process and interpret high-content cytometry data. We also underscore proper experimental design as a key step for obtaining good quality data." @default.
- W3014952014 created "2020-04-10" @default.
- W3014952014 creator A5028701129 @default.
- W3014952014 creator A5033558509 @default.
- W3014952014 creator A5052973247 @default.
- W3014952014 date "2020-01-01" @default.
- W3014952014 modified "2023-10-14" @default.
- W3014952014 title "Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry" @default.
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