Insights into growth from single-cell data

Over the last decade, single-cell measurements of growth have become more accurate and more throughput. These advances were accompanied by the developments of new models as well as new methodologies to analyze the wealth of single-cell data. I will describe several new methods we developed to extract biological insights into the processes of cell growth and division from single-cell measurements of cell size and timing of key cell cycle events, which we applied to single-cell data of bacteria as well as mamallian cells. I will discuss the question of whether growth rate fluctuations are dominated by intracellular processes, which manifest as continuous noise, or by division events, which manifest as noise at birth. I will also discuss the effect of regression dilution, and how using it helps us infer the different kinds of measurement noise in a given dataset.