DISCRETE STOCHASTIC-MODEL FOR SELF-RENEWAL AND DIFFERENTIATION OF PROGENITOR CELLS

We propose a discrete model for self-renewal and differentiation of he matopoietic stem cells based on the notion that, in a favorable enviro nment, the commitment of the cells to a particular pair of progeny is a stochastic event with the possibility of either self-renewal or diff erentiation. Regulatory mechanisms are incorporated into the model, as is diffusion of the cytokines that carry the signals for such mechani sms. The model can produce chaotic states, and is shown to be capable of predicting some key features of the experimental data.