2017/04/11 by Kuize Zhang, Zhang, Kuize
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #03C90 #92C42 #93B07 #Computational Drug Discovery Methods #FOS: Mathematics #Gene Regulatory Network Analysis #Optimization and Control (math.OC) #Receptor Mechanisms and Signaling #math.OC #msc:03C90 #msc:92C42 #msc:93B07
paper · pdf · doi:10.48550/arxiv.1704.03231
14 pages, 18 figures
openalex publication_date 2017/04/11 · arxiv created 2017/07/21 · arxiv updated 2017/07/24 · openalex created_date 2019/05/09 · openalex updated_date 2026/07/28
It is known that determining the observability and reconstructibility of Boolean control networks (BCNs) are both NP-hard in the number of nodes of BCNs. In this paper, we use the aggregation method to overcome the challenging complexity problem in verifying the observability and reconstructibility of large-scale BCNs with special structures in some sense. First, we define a special class of aggregations that are compatible with observability and reconstructibility (i.e, observability and reconstructibility are meaningful for each part of the aggregation), and show that even for this special class of aggregations, the whole BCN being observable/reconstructible does not imply the resulting sub-BCNs being observable/reconstructible, and vice versa. Second, for acyclic aggregations in this special class, we prove that all resulting sub-BCNs being observable/reconstructible implies the whole BCN being observable/reconstructible. Third, we show that finding such acyclic special aggregations with sufficiently small parts can tremendously reduce computational complexity. Finally, we use the BCN T-cell receptor kinetics model to illustrate the efficiency of these results. In addition, the special aggregation method characterized in this paper can also be used to deal with the observability/reconstructibility of large-scale linear (special classes of nonlinear) control systems with special network structures.