Section edited by Marek Kimmel
Progress in experimentation, quantification and visualization techniques now makes it possible to build mathematical models that are far more accurate than ever before. Importantly, single-cell dynamic imaging sequencing enables gauging the heterogeneity within cell populations, whether stochastic or caused by deterministic complexity. This makes models that were purely theoretical 20 or 30 years ago falsifiable and capable of predicting effects of a wide range of perturbations. We seek papers combining new biology with advanced and rigorous mathematics. Examples of focal topics include, but are not limited to: stochastic models of mutation, emergence and evolution of multiple clonal populations in cancer, biological pattern formation influenced by stochasticity, interaction of cell population genetics and cell population dynamics in progression of chronic diseases, and self-organization in normal and disease processes (such as cancer).