Title
Discrimination of attractors with noisy nodes in Boolean networks
Abstract
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.
Year
DOI
Venue
2021
10.1016/j.automatica.2021.109630
Automatica
Keywords
DocType
Volume
Observability,Boolean networks,Attractors,Genetic networks,Biomarkers
Journal
130
Issue
ISSN
Citations 
1
0005-1098
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Xiaoqing Cheng1123.26
Wai-Ki Ching268378.66
Sini Guo352.44
Tatsuya Akutsu42169216.05