Fig. 1.

Schematic view of the proposed method. The first step involves building clinically relevant gene association networks from gene expression data of patients with the same clinical category. These networks are built based on the linear models generated by the model tree induction algorithm called M5P (Witten and Frank, 2005), an extension of regression tree algorithm. The second step involves predicting the clinical category of a new patient through the inferred networks. The prediction is based on the relative error between the true and predicted gene expression values of those genes involved in the inferred networks.