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In systems biology, live single-cell imaging is a live-cell imaging technique that combines traditional live-cell imaging and time-lapse microscopy techniques with automated cell tracking and feature extraction, drawing many techniques from high-content screening. It is used to study signalling dynamics and behaviour in populations of ...
A list of more than 100 different single cell sequencing (omics) methods have been published. [1] The large majority of methods are paired with short-read sequencing technologies, although some of them are compatible with long read sequencing.
This single cell shows the process of the central dogma of molecular biology, which are all steps researchers are interested to quantify (DNA, RNA, and Protein).. In cell biology, single-cell analysis and subcellular analysis [1] refer to the study of genomics, transcriptomics, proteomics, metabolomics, and cell–cell interactions at the level of an individual cell, as opposed to more ...
FD or F/D: field of the drawing: The [main] field of the drawing, as opposed to other areas of it, such as the parts list , general notes (G/N), flagnotes , title block , rev block , bill of materials (B/M or BoM or BOM), or list of materials . Rationales for drawing changes that are noted in the rev block often use these abbreviations for ...
The Cell Painting assay [1] is a high-content, high-throughput imaging technique used to capture a wide array of cellular phenotypes in response to diverse perturbations. [2] These phenotypes, often termed "morphological profiles", can be used to understand various biological phenomena, including cellular responses to genetic changes, drug ...
Single-cell DNA genome sequencing involves isolating a single cell, amplifying the whole genome or region of interest, constructing sequencing libraries, and then applying next-generation DNA sequencing (for example Illumina, Ion Torrent). Single-cell DNA sequencing has been widely applied in mammalian systems to study normal physiology and ...
Detecting differences in gene expression level between two populations is used both single-cell and bulk transcriptomic data. Specialised methods have been designed for single-cell data that considers single cell features such as technical dropouts and shape of the distribution e.g. Bimodal vs. unimodal. [23]
Such differences can be detected using modern single-cell analysis techniques. [1] Investigation of variability within a population of cells contributes to understanding of developmental and pathological processes, An example of single cell analysis. Here, imaging software is used track individual cells as they migrate over time. [2]