Paper Info
Title
Fixed Parameter Algorithms and Hardness of Approximation Results for the Structural Target Controllability Problem.
Abstract
Recent research has revealed new applications of network control science within bio-medicine, pharmacology, and medical therapeutics. These new insights and new applications generated in turn a rediscovery of some old, unresolved algorithmic questions, this time with a much stronger motivation for their tackling. One of these questions regards the so-called Structural Target Control optimization problem, known in previous literature also as Structural Output Controllability problem. Given a directed network (graph) and a target subset of nodes, the task is to select a small (or the smallest) set of nodes from which the target can be independently controlled, i.e., it can be driven from any given initial configuration to any desired final one, through a finite sequence of input values. In recent work, this problem has been shown to be NP-hard, and several heuristic algorithms were introduced and analyzed, both on randomly generated networks, and on bio-medical ones. In this paper, we show that the Structural Target Controllability problem is fixed parameter tractable when parameterized by the number of target nodes. We also prove that the problem is hard to approximate at a factor better than O(log n).
Year
DOI
Venue
2018
10.1007/978-3-319-91938-6_9
ALGORITHMS FOR COMPUTATIONAL BIOLOGY (ALCOB 2018)
Keywords
DocType
Volume
Systems biology,Protein interaction networks,Structural network control,Approximation algorithms,Fixed parameter algorithms
Conference
10849
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Eugen Czeizler110716.76
Alexandru Popa27013.34
Victor Popescu300.34