National audienceIn this work, we reconstruct the gene regulation networks from the microarray experiments data by Bayesian networks approach. We use the evolutionary algorithm for the search-and-score based structure learning methods. The learned network is tested by the hypothesis testing with two populations of patient data, one with treatment (drugs), other without treatment. The answer of question "How does the treatment influence to gene regulation?" is expected
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
Introduction A central goal of molecular biology is to understand the regulatory interactions of ge...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Bayesian network techniques have been used for discovering causal relationships among large number o...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
International audienceReverse engineering of gene regulatory networks is a key issue for functional ...
Abstract. DNA arrays yield a global view of gene expression and can be used to build genetic network...
Understanding gene interactions in complex living systems can be seen as the ultimate goal of the sy...
Inferring gene regulatory networks from data requires the development of algorithms devoted to struc...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
Motivation: Bayesian networks have been applied to infer genetic regulatory interactions from microa...
A Bayesian network is a graph-based model of joint multivariate probability distributions that captu...
Modern technologies and especially next generation sequencing facilities are giving a cheaper access...
Modern technologies and especially next generation sequencing facilities are giving a cheaper access...
This article deals with the identification of gene regula-tory networks from experimental data using...
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
Introduction A central goal of molecular biology is to understand the regulatory interactions of ge...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Bayesian network techniques have been used for discovering causal relationships among large number o...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
International audienceReverse engineering of gene regulatory networks is a key issue for functional ...
Abstract. DNA arrays yield a global view of gene expression and can be used to build genetic network...
Understanding gene interactions in complex living systems can be seen as the ultimate goal of the sy...
Inferring gene regulatory networks from data requires the development of algorithms devoted to struc...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
Motivation: Bayesian networks have been applied to infer genetic regulatory interactions from microa...
A Bayesian network is a graph-based model of joint multivariate probability distributions that captu...
Modern technologies and especially next generation sequencing facilities are giving a cheaper access...
Modern technologies and especially next generation sequencing facilities are giving a cheaper access...
This article deals with the identification of gene regula-tory networks from experimental data using...
Gene regulatory network is a model of a network that describes the relationships among genes in a gi...
Introduction A central goal of molecular biology is to understand the regulatory interactions of ge...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...