A combination of hybrid methods to select informative genes form mixed­lineage leukemia cancer

Abstract

The traditional cancer diagnosis relies on a complex and inexact combination of clinical and histopathological data. This classic approach may fail when dealing with atypical tumours or morphologically indistinguishable tumour subtypes. Advances in the area of microarray-based expression analysis have led to the promise of cancer diagnosis using new molecular-based approaches (Wang et al., 2007). A microarray machine is used to measure the expression levels of thousands of genes simultaneously in a cell mixture, and finally it produces microarray data. The task of cancer classification using microarray data is to classify tissue samples into related classes of phenotypes, e.g., cancer versus normal (Mohamad et al., 2007).