In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three ma...
Shawn Martin, George Davidson, Elebeoba E. May, Je...
Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time s...
David Oviatt, Mark J. Clement, Quinn Snell, Kennet...
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
The paper presents MRNet, an original method for inferring genetic networks from microarray data. This method is based on maximum relevance/minimum redundancy (MRMR), an effective ...
Patrick Emmanuel Meyer, Kevin Kontos, Gianluca Bon...