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

作者：Kobayashi Koichi^*; Hiraishi Kunihiko

来源：IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(8): 1966-1971.

DOI：10.1109/TNNLS.2016.2572063

• Gene regulatory network
• network structure
• probabilistic Boolean network (PBN)
• systems biology

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.

• 出版日期2017-8