We investigate the problem of finding optimal one-bit perturbation that maximizes the size of the basin of attractions(BOAs)of desired attractors and minimizes the size of the BOAs of undesired attractors for large-sc...We investigate the problem of finding optimal one-bit perturbation that maximizes the size of the basin of attractions(BOAs)of desired attractors and minimizes the size of the BOAs of undesired attractors for large-scale Boolean networks by cascading aggregation.First,via the aggregation,a necessary and sufficient condition is given to ensure the invariance of desired attractors after one-bit perturbation.Second,an algorithm is proposed to identify whether the one-bit perturbation will cause the emergence of new attractors or not.Next,the change of the size of BOAs after one-bit perturbation is provided in an algorithm.Finally,the efficiency of the proposed method is verified by a T-cell receptor network.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61773371)。
文摘We investigate the problem of finding optimal one-bit perturbation that maximizes the size of the basin of attractions(BOAs)of desired attractors and minimizes the size of the BOAs of undesired attractors for large-scale Boolean networks by cascading aggregation.First,via the aggregation,a necessary and sufficient condition is given to ensure the invariance of desired attractors after one-bit perturbation.Second,an algorithm is proposed to identify whether the one-bit perturbation will cause the emergence of new attractors or not.Next,the change of the size of BOAs after one-bit perturbation is provided in an algorithm.Finally,the efficiency of the proposed method is verified by a T-cell receptor network.
