Flow cytometry data can be generated for either an experimental series (cell samples are exposed to various stimuli), or for a time series (cell samples are measured at different times). Statistical analysis of the series data is a common technique for characterizing the effect stimuli or time has had on the samples. Given that the cells measured in one sample of the series are different from the cells measured in the next sample, a more difficult proposition is to infer how the measured properties of individual cells would change as each progresses through the series. A novel combination of clustering and biclustering is presented as a method for measuring the "migration" of cells from one sample to the next in flow cytometry series data.