  Cellular signaling is essential in information processing and decision
making. Therefore, a variety of experimental approaches have been developed to
study signaling on bulk and single-cell level. Single-cell measurements of
signaling molecules demonstrated a substantial cell-to-cell variability,
raising questions about its causes and mechanisms and about how cell
populations cope with or exploit cellular heterogeneity. To gain insights from
single-cell signaling data, analysis and modeling approaches have been
introduced. This review discusses these modeling approaches, with a focus on
recent advances in the development and calibration of mechanistic models.
Additionally, it outlines current and future challenges.
