Yang Jung-Min, Lee Chun-Kyung, Kim Namhee, Cho Kwang-Hyun
IEEE Trans Cybern. 2025 Jan;55(1):24-37. doi: 10.1109/TCYB.2024.3473945. Epub 2024 Dec 19.
This article presents attractor-transition control of complex biological networks represented by Boolean networks (BNs) wherein the BN is steered from a prescribed initial attractor toward a desired one. The proposed approach leverages the similarity between attractors and Boolean algebraic properties embedded in the underlying state transition equations. To enhance the clarity of expression regarding stabilization toward the desired attractor, a simple coordinate transformation is performed on the considered BN. Based on the characteristics of transformed state equations, self-stabilizing state variables requiring no control efforts are derived in the first. Next, by applying the feedback vertex set (FVS) control scheme, control inputs stabilizing the remaining state variables are determined. The proposed control scheme exhibits versatility by accommodating both fixed-point and cyclic attractors. We validate the effectiveness of the proposed strategy through extensive numerical experiments conducted on random BNs as well as complex biological systems. In adherence to the reproducible research initiative, detailed results of numerical experiments and all the implementation codes are provided on the authors' website: https://github.com/choonlog/AttractorTransition.
本文提出了由布尔网络(BNs)表示的复杂生物网络的吸引子转换控制方法,其中布尔网络从规定的初始吸引子转向期望的吸引子。所提出的方法利用了吸引子与嵌入在基础状态转换方程中的布尔代数性质之间的相似性。为了提高关于向期望吸引子稳定化表达的清晰度,对所考虑的布尔网络进行了简单的坐标变换。基于变换后的状态方程的特性,首先导出不需要控制努力的自稳定状态变量。接下来,通过应用反馈顶点集(FVS)控制方案,确定稳定其余状态变量的控制输入。所提出的控制方案通过适应定点和循环吸引子而具有通用性。我们通过在随机布尔网络以及复杂生物系统上进行的大量数值实验验证了所提出策略的有效性。为遵循可重复研究倡议,作者网站(https://github.com/choonlog/AttractorTransition)提供了数值实验的详细结果和所有实现代码。