We can further use the trained AR interaction matrix for each cancer type to obtain different views of each tumour data set via mappings (Fig. 1b): given a tumour sample's (phospho)protein expression levels, we can multiply through the model to infer sample-specific TF activities; conversely, given the gene expression profile, we can multiply through the motif hit matrix and the model to infer ‘(phospho)protein activities' that are more informative than the original noisy RPPA data (Fig. 1b, bottom). The gene discussed is TF; the disease is neoplasm.