Altering steady-state probabilities in probabilistic Boolean networks

Ranadip Pal; Aniruddha Datta; Edward R. Dougherty

doi:10.1109/GENSIPS.2006.353163

Altering steady-state probabilities in probabilistic Boolean networks

Ranadip Pal, Aniruddha Datta, Edward R. Dougherty

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006
Pages	75-76
Number of pages	2
DOIs	https://doi.org/10.1109/GENSIPS.2006.353163
State	Published - 2006
Event	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006 - College Station, TX, United States Duration: May 28 2006 → May 30 2006

Publication series

Name	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006

Conference

Conference	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
Country/Territory	United States
City	College Station, TX
Period	05/28/06 → 05/30/06

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10.1109/GENSIPS.2006.353163

Cite this

Pal, R., Datta, A., & Dougherty, E. R. (2006). Altering steady-state probabilities in probabilistic Boolean networks. In 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006 (pp. 75-76). Article 4161784 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006). https://doi.org/10.1109/GENSIPS.2006.353163

@inproceedings{d87e10780dfd416b80b357e9706aa94e,

title = "Altering steady-state probabilities in probabilistic Boolean networks",

abstract = "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.",

author = "Ranadip Pal and Aniruddha Datta and Dougherty, {Edward R.}",

year = "2006",

doi = "10.1109/GENSIPS.2006.353163",

language = "English",

isbn = "1424403855",

series = "2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006",

pages = "75--76",

booktitle = "2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006",

note = "2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006 ; Conference date: 28-05-2006 Through 30-05-2006",

}

Pal, R, Datta, A & Dougherty, ER 2006, Altering steady-state probabilities in probabilistic Boolean networks. in 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006., 4161784, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, pp. 75-76, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, College Station, TX, United States, 05/28/06. https://doi.org/10.1109/GENSIPS.2006.353163

Altering steady-state probabilities in probabilistic Boolean networks. / Pal, Ranadip; Datta, Aniruddha; Dougherty, Edward R.
2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006. 2006. p. 75-76 4161784 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Datta, Aniruddha

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AB - 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.

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BT - 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006

T2 - 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006

Y2 - 28 May 2006 through 30 May 2006

ER -

Altering steady-state probabilities in probabilistic Boolean networks

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