Solutions for deriving the most consistent Bayesian gene regulatory network model from given data sets using evolutionary algorithms typically only result in locally optimal solutions
Abstract Background The regulation of gene expression is achieved through gene regulatory networks (...
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
In genetics and systems biology, Bayesian networks (BNs) are used to describe and iden-tify interdep...
Inferring gene regulatory networks from data requires the development of algorithms devoted to struc...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
Gene regulatory network can intuitively reflect the interaction between genes, and an in-depth study...
International audienceReverse engineering of gene regulatory networks is a key issue for functional ...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
This article deals with the identification of gene regula-tory networks from experimental data using...
Dynamic Bayesian networks (DBNs) can be used for the discovery of gene regulatory networks (GRNs) fr...
Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data...
<p>As an example, DM_BN takes as input deletion mutant gene expression profiles. The relative change...
Abstract Background Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling v...
BACKGROUND: Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling various b...
In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from gen...
Abstract Background The regulation of gene expression is achieved through gene regulatory networks (...
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
In genetics and systems biology, Bayesian networks (BNs) are used to describe and iden-tify interdep...
Inferring gene regulatory networks from data requires the development of algorithms devoted to struc...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
Gene regulatory network can intuitively reflect the interaction between genes, and an in-depth study...
International audienceReverse engineering of gene regulatory networks is a key issue for functional ...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
This article deals with the identification of gene regula-tory networks from experimental data using...
Dynamic Bayesian networks (DBNs) can be used for the discovery of gene regulatory networks (GRNs) fr...
Using Dynamic Bayesian Networks (DBN) to model genetic regulatory networks from gene expression data...
<p>As an example, DM_BN takes as input deletion mutant gene expression profiles. The relative change...
Abstract Background Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling v...
BACKGROUND: Dynamic Bayesian network (DBN) is among the mainstream approaches for modeling various b...
In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from gen...
Abstract Background The regulation of gene expression is achieved through gene regulatory networks (...
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
In genetics and systems biology, Bayesian networks (BNs) are used to describe and iden-tify interdep...
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