Next Article in Journal
A New Quintic Spline Method for Integro Interpolation and Its Error Analysis
Previous Article in Journal
Towards Efficient Positional Inverted Index †
Previous Article in Special Issue
Modeling Delayed Dynamics in Biological Regulatory Networks from Time Series Data
Article Menu

Export Article

Open AccessReview

Optimization-Based Approaches to Control of Probabilistic Boolean Networks

Graduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kita-ku, Sapporo 060-0814, Hokkaido, Japan
School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan
Author to whom correspondence should be addressed.
Academic Editors: Tatsuya Akutsu and Henning Fernau
Algorithms 2017, 10(1), 31;
Received: 30 September 2016 / Revised: 17 February 2017 / Accepted: 20 February 2017 / Published: 22 February 2017
(This article belongs to the Special Issue Biological Networks)
PDF [219 KB, uploaded 22 February 2017]


Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs), which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs) are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained. View Full-Text
Keywords: integer programming; gene regulatory network; polynomial optimization; probabilistic Boolean network integer programming; gene regulatory network; polynomial optimization; probabilistic Boolean network

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Kobayashi, K.; Hiraishi, K. Optimization-Based Approaches to Control of Probabilistic Boolean Networks. Algorithms 2017, 10, 31.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top