论文标题
在布尔网络中使用嘈杂的节点歧视吸引子
Discrimination of attractors with noisy nodes in Boolean networks
论文作者
论文摘要
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很重要。在这里，我们研究了确定最小传感器节点数量以区分吸引子的问题，假设每个吸引子都具有最多具有K噪声的节点。我们为此最小化问题提供了精确和近似算法。使用合成数据和现实生物学数据的计算实验也证明了算法的有效性。
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.
