Add to ORKGMany different Bayesian network models have been suggested to reconstruct gene expression networks from microarray data. However, little attention has been payed to the effects of small sample size and the stability of the solution. We engage in a systematic investigation of these issues. As a starting point for further research we introduce the kappa-network. It is a small Bayesian network model (5 nodes with three states) in which a parameter kappa controls the conditional probability distributions of the nodes. With data sampled from this model, we evaluate the effects of different sample sizes and of data being derived from active perturbations on the reconstruction of the origninal network topology
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
Background: Inference of biological networks has become an important tool in Systems Biology. Nowada...
There have been various attempts to reconstruct gene regulatory networks from microarray expression...
Many different Bayesian network models have been suggested to reconstruct gene expression networks f...
We recently developed an approach for testing the accuracy of network inference algorithms by applyi...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior k...
In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from gen...
Abstract Background Recent analysis of the yeast gene network shows that most genes have few inputs,...
Background: Genome-scale metabolic network models have contributed to elucidating biological phenome...
Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior k...
This article deals with the identification of gene regula-tory networks from experimental data using...
There have been various attempts to improve the reconstruction of gene regulatory networks from micr...
Motivation: Genetic networks are often described statistically using graphical models (e.g. Bayesian...
Network inference deals with the reconstruction of biological networks from experimental data. A var...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
Background: Inference of biological networks has become an important tool in Systems Biology. Nowada...
There have been various attempts to reconstruct gene regulatory networks from microarray expression...
Many different Bayesian network models have been suggested to reconstruct gene expression networks f...
We recently developed an approach for testing the accuracy of network inference algorithms by applyi...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior k...
In this paper, we apply Bayesian networks (BN) to infer gene regulatory network (GRN) model from gen...
Abstract Background Recent analysis of the yeast gene network shows that most genes have few inputs,...
Background: Genome-scale metabolic network models have contributed to elucidating biological phenome...
Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior k...
This article deals with the identification of gene regula-tory networks from experimental data using...
There have been various attempts to improve the reconstruction of gene regulatory networks from micr...
Motivation: Genetic networks are often described statistically using graphical models (e.g. Bayesian...
Network inference deals with the reconstruction of biological networks from experimental data. A var...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
Background: Inference of biological networks has become an important tool in Systems Biology. Nowada...
There have been various attempts to reconstruct gene regulatory networks from microarray expression...