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Title: Exact Identification of the Structure of a Probabilistic Boolean Network from Samples
Authors: Cheng, Xiaoqing
Mori, Tomoya  kyouindb  KAKEN_id  orcid (unconfirmed)
Qiu, Yushan
Ching, Wai-Ki
Akutsu, Tatsuya  kyouindb  KAKEN_id  orcid (unconfirmed)
Author's alias: 森, 智弥
阿久津, 達也
Keywords: probabilistic Boolean networks
genetic networks
network inference
sample complexity
Issue Date: 1-Nov-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Journal title: IEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume: 13
Issue: 6
Start page: 1107
End page: 1116
Abstract: We study the number of samples required to uniquely determine the structure of a probabilistic Boolean network (PBN), where PBNs are probabilistic extensions of Boolean networks. We show via theoretical analysis and computational analysis that the structure of a PBN can be exactly identified with high probability from a relatively small number of samples for interesting classes of PBNs of bounded indegree. On the other hand, we also show that there exist classes of PBNs for which it is impossible to uniquely determine the structure of a PBN from samples.
Rights: © 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.
This is not the published version. Please cite only the published version.
DOI(Published Version): 10.1109/TCBB.2015.2505310
Appears in Collections:Journal Articles

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