Stochasticity and Cell Fate

A 2008 Science-Paper from Richard Losick gives some examples why stochasticity in biochemical (genetic) control networks can be usefull:

• Persister state: A small fraction of a bacteria population goes into a non-growing state. So in the case of antibiotics that attack only growing cells, at least this fraction remains alive.
  

• Swimming or chaining: Some bacteria form spatially fixed chains, feeding on local food. Another statistical group is motile and explores new food sources.

• Red and green cones in human retina: A fraction of neurons become green sensitive, another fraction (non 50%, determined by distance between control region and gen) red sensitve. One fate inhibits the other. The two forms are randomely distributed over the retina.