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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/10790

Title: An integer programming approach to optimal control problems in context-sensitive probabilistic Boolean networks
Authors: Kobayashi, Koichi
Hiraishi, Kunihiko
Keywords: context-sensitive probabilistic Boolean networks
optimal control
integer programming
biological networks
Issue Date: 2011-02-21
Publisher: Elsevier
Magazine name: Automatica
Volume: 47
Number: 6
Start page: 1260
End page: 1264
DOI: 10.1016/j.automatica.2011.01.035
Abstract: A Boolean network is one of the models of biological networks such as gene regulatory networks, and has been extensively studied. In particular, a probabilistic Boolean network (PBN) is well known as an extension of Boolean networks, but in the existing methods to solve the optimal control problem of PBNs, it is necessary to compute the state transition diagram with 2^n nodes for a given PBN with n states. To avoid this computation, an integer programming-based approach is proposed for a context-sensitive PBN (CS-PBN), which is a general form of PBNs. In the proposed method, a CS-PBN is transformed into a linear system with binary variables, and the optimal control problem is reduced to an integer linear programming problem. By a numerical example, the effectiveness of the proposed method is shown.
Rights: NOTICE: This is the author's version of a work accepted for publication by Elsevier. Koichi Kobayashi and Kunihiko Hiraishi, Automatica, 47(6), 2011, 1260-1264, http://dx.doi.org/10.1016/j.automatica.2011.01.035
URI: http://hdl.handle.net/10119/10790
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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