We, as the authors of the article, would like to initiate discussion by providing
our Author Summary:

Stem cell differentiation is a key process in embryogenesis and tissue regeneration. Certain states of differentiation, like the stem cell or terminally differentiated state, may constitute naturally stable phenotypes that correspond to attractor states of an individual cell. Their force of attraction is modulated by the cell environment. Much of the cell dynamics may be explained by the action of deterministic biochemical cell machinery. However, it has recently become clear that certain phenomena, like the spontaneous switching between different cellular phenotypes, are linked to probabilistic processes caused by molecular level noise. In the present study we carry this notion to an extreme and model stem cell differentiation as an exclusively probabilistic process that neglects any deterministic component. The systems dynamics is then governed by differences in the noise level associated with each individual cell state. Using this new approach we were able to quantitatively reproduce recent experimental data on various aspects of cell differentiation. Consequently, we suggest that state-specific noise reduction in response to environmental signals can select certain functional cell states. This noise-driven selection scheme appears to be an economic general purpose mechanism since it requires only that the cell states which are functional in a given environment need to be noise reduced. Thus, state-specific noise regulation may be effective in cellular development and environmental adaptation.