Carolin Loos introduces two novel approaches for theanalysis of single-cell data. Both
approaches can be used to study cellularheterogeneity and therefore advance a holistic
understanding of biologicalprocesses. The first method ODE constrained mixture modeling
enables theidentification of subpopulation structures and sources of variability in
single-cellsnapshot data. The second method estimates parameters of single-cell time-lapsedata
using approximate Bayesian computation and is able to exploit the temporalcross-correlation of
the data as well as lineage information.
