  We present a flexible branching process model for cell population dynamics in
synchrony/time-series experiments used to study important cellular processes.
Its formulation is constructive, based on an accounting of the unique cohorts
in the population as they arise and evolve over time, allowing it to be written
in closed form. The model can attribute effects to subsets of the population,
providing flexibility not available using the models historically applied to
these populations. It provides a tool for in silico synchronization of the
population and can be used to deconvolve population-level experimental
measurements, such as temporal expression profiles. It also allows for the
direct comparison of assay measurements made from multiple experiments. The
model can be fit either to budding index or DNA content measurements, or both,
and is easily adaptable to new forms of data. The ability to use DNA content
data makes the model applicable to almost any organism. We describe the model
and illustrate its utility and flexibility in a study of cell cycle progression
in the yeast Saccharomyces cerevisiae.
