Table 2.

Model parameter values. The table shows the default model parameter values, in dimensionless form, that are used to produce the results in Figs. 3, 4, 5, 6

Kernel	Parameter description	Parameter values	Biological description
$B_1$	Gaussian kernel with integral $b_1$ and standard deviation ${\sigma }_B$	$b_1=0.001$, ${\sigma }_B=25$	Dispersal kernel of $s_1$ daughter cells, for cell division mediated via autocrine signalling of growth factors (Fig. 2a)
$B_{11}$	Gaussian kernel with integral $b_{11}$ and standard deviation ${\sigma }_B$	$b_{11}=0.025$, ${\sigma }_B=25$	Dispersal kernel of $s_1$ daughter cells, for cell division mediated via uptake of growth factors from other $s_1$ cells (Fig. 2b)
$B_{12}$	Gaussian kernel with integral $b_{12}$ and standard deviation ${\sigma }_B$	$b_{12}=0.050$, ${\sigma }_B=25$	Dispersal kernel of $s_2$ daughter cells, for cell division mediated via uptake of growth factors from $s_1$ cells (Fig. 2c)
C	Gaussian kernel with integral c and standard deviation ${\sigma }_C$	$c=100$, ${\sigma }_C=100$	Interaction kernel describing growth factor secretion (from $s_1$ cells) and uptake (by $s_1$ or $s_2$) cells (Fig. 2b, c)
Parameter
$\ell ,ϵ$	Scaling parameters	$\ell =1,$ $ϵ=1/\ell =1$	Scaling parameters that result from the perturbation expansion and model rescaling (Sects. 2.6, 2.7)