The Markov process model is used to establish transition probabilities among various states such as looking at transitions between certain commands.
In its initial form, the transition-probability model44 postulated that there were two phases that controlled the distribution of cells' interdivision times.
There was a steady phase and a probabilistic phase. The fluctuating G1 phase was supposed to be related to the probabilistic phase, whereas the more stable S and G2 phases were thought to be related to the constant phase. When a cell divides, the daughter cells that result go into the probabilistic phase of the cycle and stay there until they move out in a purely stochastic manner.
With the same dynamics as a radioactive atom's decay, they exit the probabilistic phase. A constant phase comes after the probabilistic phase. The duration of the constant phase determines the shortest interdivision time.
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