2024-03-28T08:15:30Zhttps://eprints.lib.hokudai.ac.jp/dspace-oai/requestoai:eprints.lib.hokudai.ac.jp:2115/671962022-11-17T02:08:08Zhdl_2115_20053hdl_2115_145Design of Probabilistic Boolean Networks Based on Network Structure and Steady-State ProbabilitiesKobayashi, KoichiHiraishi, KunihikoGene regulatory networknetwork structureprobabilistic Boolean network (PBN)systems biology007In 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.IEEE (Institute of Electrical and Electronics Engineers)Journal Articleapplication/pdfhttp://hdl.handle.net/2115/67196https://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/67196/1/PBN_IEEE_TNNLS_final.pdf2162-237XIEEE transactions on neural networks and learning systems288196619712017-08enginfo:doi/10.1109/TNNLS.2016.2572063© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.author