Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GR...
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doaj-a863018e50ea4e5499abcb37492cb62a2020-11-24T22:09:35ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/968341968341Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial OptimizationKoichi Kobayashi0Kunihiko Hiraishi1School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, JapanSchool of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa 923-1292, JapanOne of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs.http://dx.doi.org/10.1155/2014/968341 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Koichi Kobayashi Kunihiko Hiraishi |
spellingShingle |
Koichi Kobayashi Kunihiko Hiraishi Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization The Scientific World Journal |
author_facet |
Koichi Kobayashi Kunihiko Hiraishi |
author_sort |
Koichi Kobayashi |
title |
Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization |
title_short |
Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization |
title_full |
Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization |
title_fullStr |
Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization |
title_full_unstemmed |
Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization |
title_sort |
verification and optimal control of context-sensitive probabilistic boolean networks using model checking and polynomial optimization |
publisher |
Hindawi Limited |
series |
The Scientific World Journal |
issn |
2356-6140 1537-744X |
publishDate |
2014-01-01 |
description |
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical
control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. |
url |
http://dx.doi.org/10.1155/2014/968341 |
work_keys_str_mv |
AT koichikobayashi verificationandoptimalcontrolofcontextsensitiveprobabilisticbooleannetworksusingmodelcheckingandpolynomialoptimization AT kunihikohiraishi verificationandoptimalcontrolofcontextsensitiveprobabilisticbooleannetworksusingmodelcheckingandpolynomialoptimization |
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