Paper Info
Title
Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks.
Abstract
Gene regulatory networks (GRNs) are the complex dynamical systems that orchestrate the activities of biological cells. In order to design effective therapeutic interventions for diseases such as cancer, there is a need to control GRNs in more sophisticated ways. Computational control methods offer the potential for discovering such interventions, but the difficulty of the control problem means that current methods can only be applied to GRNs that are either very small or that are topologically restricted. In this paper, we consider an alternative approach that uses evolutionary algorithms to design GRNs that can control other GRNs. This is motivated by previous work showing that computational models of GRNs can express complex control behaviours in a relatively compact fashion. As a first step towards this goal, we consider abstract Boolean network models of GRNs, demonstrating that Boolean networks can be evolved to control trajectories within other Boolean networks. The Boolean approach also has the advantage of a relatively easy mapping to synthetic biology implementations, offering a potential path to in vivo realisation of evolved controllers.
Year
DOI
Venue
2016
10.1007/978-3-319-31204-0_23
Lecture Notes in Computer Science
Keywords
Field
DocType
Gene regulatory networks,Boolean networks,Control,Evolutionary algorithms
Boolean network,Evolutionary algorithm,Computer science,Theoretical computer science,Implementation,Computational model,Dynamical systems theory,Gene regulatory network,Synthetic biology
Conference
Volume
ISSN
Citations 
9597
0302-9743
2
PageRank 
References 
Authors
0.38
8
3
Name
Order
Citations
PageRank
Nadia S. Taou120.38
David W. Corne22161152.00
Michael A. Lones316820.42