A GMM-IG framework for selecting genes as expression panel biomarkers

We present a conceptually simple framework that enables reliable integration of true differential gene expression signals from multiple microarray experiments. This novel computational method has been shown to generate interesting biomarker panels for lung cancer studies. It is promising as a general strategy for future panel biomarker development, especially for applications that requires integrating experimental results generated from different research centers or with different technology platforms.