Novel Biology-driven bioinformatics methods in Cancer genomics

Abstract

In the past decade, numerous groups have reported studies using genome-wide gene expression data generated from microarray. One of the blooming fields for microarray application is cancer research. Despite the promising nature of these initial microarray studies, such conventional approaches are associated with certain limitations. Because of these challenges, it is important to develop new methods to mine the inherent richness of information present in genome-wide expression data, in order to further identify novel, robust, and biologically-relevant molecular signatures for the purposes of tumor classification and patient stratification. We applied the signature analysis (SA), which was designed to overcome the limitations of conventional clustering approaches, to a set of breast cancer expression profiles and successfully defined multiple b