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Altering steady-state probabilities in probabilistic Boolean networks

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3 Author(s)
Pal, R. ; Electr. & Comput. Eng., Texas A & M Univ., College Station, TX ; Datta, A. ; Dougherty, E.R.

External control of a genetic regulatory network is used for the purpose of avoiding undesirable states, such as those associated with disease. Heretofore, intervention has focused on finite-horizon control, i.e., control over a small number of stages. This paper considers the design of optimal infinite-horizon control for probabilistic Boolean networks (PBNs). The stationary policy obtained is independent of time and dependent on the current state. The average-cost-per-stage problem formulation is used to generate the stationary policy for a PBN constructed from melanoma gene-expression data. The results show that the stationary policiy obtained is capable of shifting the probability mass of the stationary distribution from undesirable states to desirable ones.

Published in:

Genomic Signal Processing and Statistics, 2006. GENSIPS '06. IEEE International Workshop on

Date of Conference:

28-30 May 2006