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  • Research Article
  • Open Access

Reduction Mappings between Probabilistic Boolean Networks

EURASIP Journal on Advances in Signal Processing20042004:314935

https://doi.org/10.1155/S1110865704309182

  • Received: 11 April 2003
  • Published:

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.

Keywords

  • Boolean network
  • genetic network
  • graphical models
  • projection
  • reduction

Authors’ Affiliations

(1)
Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA
(2)
Department of Electrical Engineering, Texas A&M University, 3128 TAMU, College Station, TX 77843-3128, USA

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