Discrete Model-Based Methods for Control of Complex BiologicalSyetems

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We performed studies on analysis and control of complex biological networks from various viewpoints. In particular, we developed algorithms for detecting a singleton attractor and a periodic attractor in certain kinds of Boolean networks, clarified the computational hardness of control of probabilistic Boolean networks, developed an approximate method to derive distribution of the number of reactions impacted by knockout of a single reaction, developed a method for network completion using dynamic programming and least-squares fitting, and analyzed structural controllability of complex networks using the concept of the minimum dominating set in graph theory.