Shmulevich, I., Dougherty, E.R., Kim, S. and Zhang, W. (2002) Probabilistic Boolean Networks: A Rule-Based Uncertainty Model for Gene Regulatory Networks. Bioinformatics, 18, 261-274.
http://dx.doi.org/10.1093/bioinformatics/18.2.261

has been cited by the following article:

• TITLE: Attractor-Based Simultaneous Design of the Minimum Set of Control Nodes and Controllers in Boolean Networks

  AUTHORS: Koichi Kobayashi

  KEYWORDS: Boolean Networks, Integer Linear Programming, Minimum Set of Control Nodes, Singleton Attractors

  JOURNAL NAME: Applied Mathematics, Vol.7 No.14, August 18, 2016

  ABSTRACT: Design of control strategies for gene regulatory networks is a challenging and important topic in systems biology. In this paper, the problem of finding both a minimum set of control nodes (control inputs) and a controller is studied. A control node corresponds to a gene that expression can be controlled. Here, a Boolean network is used as a model of gene regulatory networks, and control specifications on attractors, which represent cell types or states of cells, are imposed. It is important to design a gene regulatory network that has desired attractors and has no undesired attractors. Using a matrix-based representation of BNs, this problem can be rewritten as an integer linear programming problem. Finally, the proposed method is demonstrated by a numerical example on a WNT5A network, which is related to melanoma.