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Recent years have witnessed extensive research activity in modeling biological phenomena as well as in developing intervention strategies for such phenomena. S-systems, which offer a good compromise between accuracy and mathematical flexibility, are a promising framework for modeling the dynamical behavior of biological phenomena. In this paper, two different intervention strategies, namely direct...
Probabilistic Boolean Networks have served as the main model for studying the application of optimal intervention strategies to favorably affect system dynamics. The errors originating in the data extraction or network inference process prevent the accurate estimation of the state transition probabilities of the network. The mathematical characterization of the uncertainties will enable us to analyze...
The design of effective therapeutic interventions can be formulated as Markov decision processes in the framework of context-sensitive probabilistic Boolean networks, assuming that the states are measurable. The full state of a context-sensitive probabilistic Boolean network is specified by an ordered pair composed of a network context and a gene-activity profile. In practice, however, the network...
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