open access

https://hdl.handle.net/2115/67196

Design of Probabilistic Boolean Networks Based on Network Structure and Steady-State Probabilities

英語

systems biology

2017-08

IEEE (Institute of Electrical and Electronics Engineers)

IEEE transactions on neural networks and learning systems

28(8)

1966-1971

In this brief, we consider the problem of finding a probabilistic Boolean network (PBN) based on a network structure and desired steady-state properties. In systems biology and synthetic biology, such problems are important as an inverse problem. Using a matrix-based representation of PBNs, a solution method for this problem is proposed. The problem of finding a BN has been studied so far. In the problem of finding a PBN, we must calculate not only the Boolean functions, but also the probabilities of selecting a Boolean function and the number of candidates of the Boolean functions. Hence, the problem of finding a PBN is more difficult than that of finding a BN. The effectiveness of the proposed method is presented by numerical examples.

学術雑誌論文

Accepted Manuscript

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