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

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 hi...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2016-11, Vol.13 (6), p.1107-1116
Hauptverfasser:	Xiaoqing Cheng, Mori, Tomoya, Yushan Qiu, Wai-Ki Ching, Akutsu, Tatsuya
Format:	Artikel
Sprache:	eng
Schlagworte:	Bioinformatics Biological system modeling Boolean functions Complexity theory Computer applications Computer Simulation Data Interpretation, Statistical Gene Expression Regulation - physiology genetic networks Mathematical model Models, Biological Models, Statistical network inference Probabilistic analysis Probabilistic Boolean networks Probabilistic logic Probability distribution Proteome - metabolism sample complexity Sample Size Samples (statistical) Signal Transduction - physiology Theoretical analysis
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