Reduction mappings between probabilistic Boolean networks

Authors:
Ivan Ivanov;Edward R. Dougherty
Affiliations:
Department of Electrical Engineering, Texas A&M University, College Station, TX;Department of Electrical Engineering, Texas A&M University, TAMU College Station, TX
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2004

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Abstract

Probabilistic Boolean networks (PBNs) comprise a model describing a directed graph with rule-based dependences between its nodes. The rules are selected, based on a given probability distribution which provides a flexibility when dealing with the uncertainty which is typical for genetic regulatory networks. Given the computational complexity of the model, the characterization of mappings reducing the size of a given PBN becomes a critical issue. Mappings between PBNs are important also from a theoretical point of view. They provide means for developing a better understanding about the dynamics of PBNs. This paper considers two kinds of mappings reduction and projection and their effect on the original probability structure of a given PBN.