Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
The development of structure-learning algorithms for gene regulatory networks depends heavily on the availability of synthetic data sets that contain both the original network and ...
Koenraad Van Leemput, Tim Van den Bulcke, Thomas D...