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Genes, Morphogenesis, Evolution: Life and ALife Aspects


Boolean Network, a Definition


The basis for the Boolean networks was introduced by Turing and Von Neumann in the form of automata theory [8,9,10].

A Boolean network is a system of n interconnected binary elements; any element in the system can be connected to a series I of other k elements, where k (and hence I) can vary. For each individual element there is a logical or Boolean rule B which compute its value based on the values of the elements connected with one. The state of the system S is defined by the pattern of states (on/off or 0/1) of all its elements. All elements are updated synchronously, moving the system into its next state, and each state can has only one resultant state. The total system space is defined as all possible N combinations of the values of the n elements in S. The state of the system is computed in discrete time steps. Therefore, at any moment (t) it is defined as follows:
S(t+1)=f(S(t),{I1... In}, {B1...Bn}).
Since the number of all possible states of the system is limited and the transition rules are defined and do not depend on time, the system reaches a cycle or attractor. It can be a steady state (point attractor) or a limit cycle (dynamic attractor).
Attractors may be envisioned as the "target area" of the organism, e.g. cell types at the end of development, repaired tissue following the response to injury, or even the adaptation of metabolic gene expression following a change in nutrient environment in microorganisms The limit cycles in certain respects may reflect the biological rhythms.
All states leading to the same attractor constitute the basin of the attractor.


References


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