Abstract: Discovering new subclasses of pathologies and expression signatures related to specific phenotypes are challenging problems in the context of gene expression data analysis. To pursue these objectives, we need to estimate the “natural” number and the stability of the discovered clusters. To this end, new approaches based on random subspaces and bootstrap methods have been recently proposed.