  Self-organization is the autonomous assembly of a network of interacting
components into a stable, organized pattern. This article shows that the
process of self-assembly can be encoded in terms of evolutionary entropy, a
statistical measure of the cooperativity of the interacting components.
Evolutionary entropy describes the rate at which a network of interacting
metabolic units convert an external energy source into mechanical energy and
work. We invoke Directionality Theory, an analytic model of Darwinian evolution
to analyze self-assembly as a variation-selection process, and to derive a
general tenet, namely, the Entropic Principle of Self-Organization: The
equilibrium states of a self-organizing process are states which maximize
evolutionary entropy, contingent on the production rate of the external energy
source. This principle is a universal rule, applicable to the self-assembly of
structures ranging from the folding of proteins, to branching morphogenesis,
and the emergence of social organization. The principle also elucidates the
origin of cellular life: the transition from inorganic matter to the emergence
of cells, capable of replication and metabolism.

Statistical Mechanics;Biological Physics;Populations and Evolution