In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states to some target states. The objective is to achieve a target state probability distribution with a minimal control cost The model can be formulated as a minimization problem with integer variables and continuous variables. Our experimental results show that the control model and the algorithm are efficient for gene intervention problems in genetic networks. © 2005 IEEE.published_or_final_versio
Motivation: A basic issue for translational genomics is to model gene interaction via gene regulator...
Abstract—The dynamics of a rule-based gene regulatory net-work are determined by the regulatory func...
Probabilistic Boolean Networks (PBN’s), which form a subclass of Markovian Genetic Regulatory Networ...
In this paper, we study a control model for gene intervention in a genetic regulatory network. At ea...
In the post-genomic era, the construction and control of genetic regulatory networks using gene expr...
In recent years Boolean Networks (BN) and Probabilistic Boolean Networks (PBN) have become popular p...
Abstract—A prime objective of modeling genetic regulatory net-works is the identification of potenti...
The construction and control of genetic regulatory networks using gene expression data is an importa...
Motivation: A basic problem of translational systems biology is to utilize gene regulatory networks ...
Motivation: A basic issue for translational genomics is to model gene interaction via gene regulator...
Control of Probabilistic Boolean Networks as models of gene regulation is an important problem; the ...
It is well known that the control/intervention of some genes in a genetic regulatory network is usef...
Motivation: Intervention in a gene regulatory network is used to avoid undesirable states, such as t...
BACKGROUND: Probabilistic Boolean Network (PBN) is a popular model for studying genetic regulatory...
We study the problem of finding optimal control policies for Probabilistic Boolean Networks (PBNs)....
Motivation: A basic issue for translational genomics is to model gene interaction via gene regulator...
Abstract—The dynamics of a rule-based gene regulatory net-work are determined by the regulatory func...
Probabilistic Boolean Networks (PBN’s), which form a subclass of Markovian Genetic Regulatory Networ...
In this paper, we study a control model for gene intervention in a genetic regulatory network. At ea...
In the post-genomic era, the construction and control of genetic regulatory networks using gene expr...
In recent years Boolean Networks (BN) and Probabilistic Boolean Networks (PBN) have become popular p...
Abstract—A prime objective of modeling genetic regulatory net-works is the identification of potenti...
The construction and control of genetic regulatory networks using gene expression data is an importa...
Motivation: A basic problem of translational systems biology is to utilize gene regulatory networks ...
Motivation: A basic issue for translational genomics is to model gene interaction via gene regulator...
Control of Probabilistic Boolean Networks as models of gene regulation is an important problem; the ...
It is well known that the control/intervention of some genes in a genetic regulatory network is usef...
Motivation: Intervention in a gene regulatory network is used to avoid undesirable states, such as t...
BACKGROUND: Probabilistic Boolean Network (PBN) is a popular model for studying genetic regulatory...
We study the problem of finding optimal control policies for Probabilistic Boolean Networks (PBNs)....
Motivation: A basic issue for translational genomics is to model gene interaction via gene regulator...
Abstract—The dynamics of a rule-based gene regulatory net-work are determined by the regulatory func...
Probabilistic Boolean Networks (PBN’s), which form a subclass of Markovian Genetic Regulatory Networ...