Another inverse problem that we consider in the lab is the separation of intrinsic and extrinsic contribution to the large cell-to-cell variability observable even in a clonal cell population. To separate those contributions is key for determining from data the correct molecular mechanism of a cellular process under study. If the variability in data is misinterpreted, erroneous conclusions about the underlying biology will be drawn. With more single-cell technologies available, this problem becomes increasingly important. We use a mixed-effect type of models that allow different sources of variability to be separated and quantifyied.
Single-cell measurements reveal cellular heterogeneity in a clonal population of cells. Separating the different contributions to this heterogeneity is crucial for quantitative biology.