TY - JOUR
TI - Basin entropy in Boolean network ensembles
AU - Krawitz, P.
AU - Shmulevich, I.
T2 - Phys Rev Lett
AB - The information processing capacity of a complex dynamical system is reflected in the partitioning of its state space into disjoint basins of attraction, with state trajectories in each basin flowing towards their corresponding attractor. We introduce a novel network parameter, the basin entropy, as a measure of the complexity of information that such a system is capable of storing. By studying ensembles of random Boolean networks, we find that the basin entropy scales with system size only in critical regimes, suggesting that the informationally optimal partition of the state space is achieved when the system is operating at the critical boundary between the ordered and disordered phases.
DA - 2007/04/13/
PY - 2007
VL - 98
IS - 15
SP - 158701
KW - *Logic
KW - *Models
KW - Biological
KW - Entropy
KW - Mathematical Computing
KW - Theoretical
ER -