Original Research ARTICLE
Target Control in Logical Models Using the Domain of Influence of Nodes
- 1Physics, Pennsylvania State University, United States
- 2Medical Oncology, Dana–Farber Cancer Institute, United States
- 3Broad Institute, United States
- 4Biology, Pennsylvania State University, United States
Dynamical models of biomolecular networks are successfully used to understand the mechanisms underlying complex diseases and to design therapeutic strategies. Network control, and its special case of target control, is a promising avenue toward developing disease therapies. In target control it is assumed that a small subset of nodes is most relevant to the system's state and the goal is to drive the target nodes into their desired states. An example of target control would be driving a cell to commit to apoptosis (programmed cell death). From the experimental perspective, gene knockout, pharmacological inhibition of proteins and providing sustained external signals are among practical intervention techniques. We identify methodologies to use the stabilizing effect of sustained interventions for target control in Boolean network models of biomolecular networks. Specifically, we define the domain of influence of a node (in a certain state) to be the nodes (and their corresponding states) that will be ultimately stabilized by the sustained state of this node regardless of the initial state of the system. We also define the related concept of the logical domain of influence of a node, and develop an algorithm for its identification using an auxiliary network that incorporates the regulatory logic. This way a solution to the target control problem is a set of nodes whose domain of influence can cover the desired target node states. We perform greedy randomized adaptive search in node state space to find such solutions. We apply our strategy to in silico biological network models of real systems to demonstrate its effectiveness. ffectiveness.
Keywords: Target control, Boolean network, biological network, Domain of influence, Logical modeling, network dynamics
Received: 04 Jan 2018;
Accepted: 13 Apr 2018.
Edited by:Matteo Barberis, University of Amsterdam, Netherlands
Reviewed by:Osbaldo Resendis-Antonio, Universidad Nacional Autónoma de México, Mexico
Maria Suarez-Diez, Wageningen University & Research, Netherlands
Denis Thieffry, École Normale Supérieure, France
Copyright: © 2018 YANG, Zañudo and Albert. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. GANG YANG, Pennsylvania State University, Physics, University Park, 16802, Pennsylvania, United States, firstname.lastname@example.org