Discrimination of attractors with noisy nodes in Boolean networks
Discrimination of attractors with noisy nodes in Boolean networks
复制标题
布尔网络中具有噪声节点的吸引子的判别
DOI：
10.1016/j.automatica.2021.109630
复制
发表时间：
2021-06-10
期刊：
影响因子：
6.4
通讯作者：
Akutsu, Tatsuya
中科院分区：
文献类型：
--
作者：
Cheng, Xiaoqing;Ching, Wai-Ki;Akutsu, Tatsuya
使用少量传感器节点观察整个系统的内部状态对于复杂网络的分析非常重要。在这里，我们研究了在每个吸引子最多有 K 个噪声节点的假设下确定区分吸引子的最小传感器节点数量的问题。我们针对这个最小化问题提出了精确算法和近似算法。使用合成数据和真实生物数据的计算实验也证明了算法的有效性。 (C) 2021 Elsevier Ltd. 保留所有权利。
Observing the internal state of the whole system using a small number of sensor nodes is important in analysis of complex networks. Here, we study the problem of determining the minimum number of sensor nodes to discriminate attractors under the assumption that each attractor has at most K noisy nodes. We present exact and approximation algorithms for this minimization problem. The effectiveness of the algorithms is also demonstrated by computational experiments using both synthetic data and realistic biological data. (C) 2021 Elsevier Ltd. All rights reserved.