Design of Large-scale Boolean Networks Based on Prescribed Attractors

摘要

In this paper, the problem of designing large-scale Boolean networks with prescribed attractors is considered. The obtained Boolean networks satisfy the attractor constraints, as well as that the size of the basins of attraction (BOAs) of desired attractors is at its maximum. This is achieved by network aggregation, under which desired attractors and undesired attractors can be mapped to input-state cycles in the subnetworks. The input-state cycles corresponding to desired attractors must be contained in subnetworks, and for each undesired attractor at least one input-state cycle is not contained. An algorithm is proposed to maximize the size of the BOAs of desired attractors. Finally, a practical example is given to illustrate the effectiveness of the proposed methods.