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An integer programming approach to optimal control problems in context-sensitive probabilistic Boolean networks

โœ Scribed by Koichi Kobayashi; Kunihiko Hiraishi


Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
302 KB
Volume
47
Category
Article
ISSN
0005-1098

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โœฆ Synopsis


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.


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An optimal control approach to nonlinear
โœ H.W.J. Lee; K.L. Teo; X.Q. Cai ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 984 KB

Motivated by the recent developments of the Control Parametrization Enhancing Technique (CPET), a novel method for solving a general cleee of nonlinear mixed integer prcgramming problems is introduced in thii paper. By imposing appropriate dynamice as well ee a set of statistical variance type of fu