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Exact Identification of the Structure of a Probabilistic Boolean Network from Samples

Published: 01 November 2016 Publication History

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.

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  • (2019)Bayesian selection probability estimation for probabilistic Boolean networksAsian Journal of Control10.1002/asjc.216621:6(2513-2520)Online publication date: 1-Jul-2019

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Published In

cover image IEEE/ACM Transactions on Computational Biology and Bioinformatics
IEEE/ACM Transactions on Computational Biology and Bioinformatics  Volume 13, Issue 6
November 2016
198 pages

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 November 2016
Published in TCBB Volume 13, Issue 6

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  • (2019)Bayesian selection probability estimation for probabilistic Boolean networksAsian Journal of Control10.1002/asjc.216621:6(2513-2520)Online publication date: 1-Jul-2019

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