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Optimal infinitehorizon control for probabilistic Boolean networks
| Venue: | IEEE Transactions on Signal Processing |
| Citations: | 35 - 14 self |
BibTeX
@ARTICLE{Pal_optimalinfinitehorizon,
author = {Ranadip Pal and Student Member and Aniruddha Datta and Senior Member and Edward R. Dougherty},
title = {Optimal infinitehorizon control for probabilistic Boolean networks},
journal = {IEEE Transactions on Signal Processing},
year = {},
volume = {54},
pages = {2006}
}
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Abstract
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 context-sensitive probabilistic Boolean networks (PBNs). It can also be applied to instantaneously random PBNs. The stationary policy obtained is independent of time and dependent on the current state. This paper concentrates on discounted problems with bounded cost per stage and on average-cost-per-stage problems. These formulations are used to generate stationary policies for a PBN constructed from melanoma gene-expression data. The results show that the stationary policies obtained by the two different formulations are capable of shifting the probability mass of the stationary distribution from undesirable states to desirable ones. Index Terms—Altering steady state, genetic network intervention, infinite-horizon control, optimal control of probabilistic Boolean networks. I.
Keyphrases
probabilistic boolean network optimal infinitehorizon control stationary policy undesirable state genetic network intervention optimal infinite-horizon control infinite-horizon control stationary distribution context-sensitive probabilistic boolean network steady state bounded cost small number different formulation current state abstract external control optimal control genetic regulatory network melanoma gene-expression data probability mass desirable one finite-horizon control index term average-cost-per-stage problem
