Title
Identification of Control Targets in Boolean Molecular Network Models via Computational Algebra
Document Type
Article
Publication Date
9-23-2016
Publication Source
BMC Systems Biology
Abstract
Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system.
ISBN/ISSN
1752-0509
Document Version
Published Version
Copyright
Copyright © 2016, The Author(s)
Publisher
BioMed Central
Volume
10
Issue
1
Peer Reviewed
yes
eCommons Citation
Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; and Laubenbacher, Reinhard, "Identification of Control Targets in Boolean Molecular Network Models via Computational Algebra" (2016). Mathematics Faculty Publications. 71.
https://ecommons.udayton.edu/mth_fac_pub/71
COinS
Comments
This document has been made available for download in accordance with the publisher's policy on open access.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Permission documentation on file.