Modeling and integer programming techniques applied to propositional calculus
Computers and Operations Research - Special issue: Expert systems and operations research
Intervention in context-sensitive probabilistic Boolean networks revisited
EURASIP Journal on Bioinformatics and Systems Biology - Special issue on applications of signal procesing techniques to bioinformatics, genomics, and proteomics
Minimalilty of finite automata representation in hybrid systems control
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Control of systems integrating logic, dynamics, and constraints
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
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.