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Technique to measure the expression dynamics of each gene in a single cell
A method has been developed to infer whether the expression of each gene in a single cell is increasing or decreasing, and at what rate, using RNA-sequencing data. This tool has many potential applications.
To understand and control complex systems, we must be able to measure the dynamics of their constituent parts. In biology, gene expression is probably the ultimate example of a complex system, with more than 20,000 genes orchestrating the functions of human tissues. However, we lack the tools to measure how genes vary in expression in individual cells over time. In a paper in Nature, La Manno et al.1 describe a powerful method that enables the level and rate of change of expression to be estimated simultaneously for each gene in a single cell. The approach has considerable implications for studying cellular dynamics, particularly in disease progression and in complex processes such as embryonic development.